From 36a2242b7315991fc554895c0b3507e6e47606cf Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Sun, 20 Mar 2022 16:30:59 +0000 Subject: [PATCH 01/36] Added Terraform files for GCP --- terraform/google/.terraform.lock.hcl | 21 +++++++++++++ terraform/google/output.tf | 4 +++ terraform/google/provider.tf | 16 ++++++++++ terraform/google/server.tf | 45 ++++++++++++++++++++++++++++ terraform/google/startup_script.sh | 6 ++++ terraform/google/vars.tf | 30 +++++++++++++++++++ 6 files changed, 122 insertions(+) create mode 100644 terraform/google/.terraform.lock.hcl create mode 100644 terraform/google/output.tf create mode 100644 terraform/google/provider.tf create mode 100644 terraform/google/server.tf create mode 100644 terraform/google/startup_script.sh create mode 100644 terraform/google/vars.tf diff --git a/terraform/google/.terraform.lock.hcl b/terraform/google/.terraform.lock.hcl new file mode 100644 index 0000000..ff14b94 --- /dev/null +++ b/terraform/google/.terraform.lock.hcl @@ -0,0 +1,21 @@ +# This file is maintained automatically by "terraform init". +# Manual edits may be lost in future updates. + +provider "registry.terraform.io/hashicorp/google" { + version = "4.14.0" + constraints = "4.14.0" + hashes = [ + "h1:JzIffu+H0h1MX7SuMa1Hheh39xEKaic43fU21twbUrQ=", + "zh:05219b3539e13eeb2bbd8775bfa0644aeaf975c30d734a24e06ec2ae0fa6aea1", + "zh:0d472a9c11d4f91c1fcbe053eca42bd895c400f9e9783c049d8c67e140ed274c", + "zh:2e38c632ac3289b31a4f4868e42f3ced4c9acbb79b43376209d7a51154a94b41", + "zh:7ed048c9c18e9e92836f9a82c2c9aea956a82a178b7a3e33f94a4a94f7e20797", + "zh:8f92259b3c37c1bf161d70048cc1b23517864626f0d277189657f5158da3728c", + "zh:a815b8670808e12a82c1d9fe40f4223138df39e2b9ed70b93647190586f515f0", + "zh:adcee3a69b081cf0da555d344453b3ecbde7bb34770f026fd4ed84d936c48895", + "zh:d2da37422ce3a197fa03d9e96ef9c0dfe3ee5c247ff82c272f2958c5d6cf3396", + "zh:e28be41d19f44c9012fc7909625d4dc67a75fb00f5b69fe1295fe07cb04f1b37", + "zh:ece149ec2e5c7d1727665c1f8834bfa71e99405a60a5f6ea384dced52ace2def", + "zh:f59bac8454a97794d2378393b6bb2cbeb61983306de0f13be06956b87d22efd5", + ] +} diff --git a/terraform/google/output.tf b/terraform/google/output.tf new file mode 100644 index 0000000..4329682 --- /dev/null +++ b/terraform/google/output.tf @@ -0,0 +1,4 @@ +output "public_ipv4" { + value = google_compute_instance.server.network_interface.0.access_config.0.nat_ip +} + diff --git a/terraform/google/provider.tf b/terraform/google/provider.tf new file mode 100644 index 0000000..8186b5f --- /dev/null +++ b/terraform/google/provider.tf @@ -0,0 +1,16 @@ +terraform { + required_providers { + google = { + source = "hashicorp/google" + version = "=4.14.0" + } + } +} + +# Configure the Google Provider +provider "google" { + project = var.project + region = var.region + zone = var.zone + credentials = file("/home/noble/.config/gcloud/gcloud-terraform-key.json") +} diff --git a/terraform/google/server.tf b/terraform/google/server.tf new file mode 100644 index 0000000..8c5799d --- /dev/null +++ b/terraform/google/server.tf @@ -0,0 +1,45 @@ +data "google_compute_image" "image" { + family = "common-cu113-debian-10" + project = "deeplearning-platform-release" +} + +resource "google_compute_instance" "server" { + name = "ml-server" + #machine_type = "f1-micro" + machine_type = var.machine_type + zone = var.zone + + tags = ["ml", "gpu"] + + guest_accelerator { + type = var.guest_accelerator + count = 1 + } + + boot_disk { + initialize_params { + image = data.google_compute_image.image.self_link + # image = "debian-cloud/debian-10" + } + } + + // Local SSD disk + scratch_disk { + interface = "SCSI" + } + + network_interface { + network = "default" + + access_config { + } + } + + scheduling { + on_host_maintenance = "TERMINATE" + } + + #metadata_startup_script = file("${path.module}/startup_script.sh") + metadata_startup_script = templatefile("${path.module}/startup_script.sh", var.startup_script_vars) + +} diff --git a/terraform/google/startup_script.sh b/terraform/google/startup_script.sh new file mode 100644 index 0000000..fc44d88 --- /dev/null +++ b/terraform/google/startup_script.sh @@ -0,0 +1,6 @@ +#!/bin/bash +useradd -m -G sudo -s /bin/bash noble +mkdir /home/noble/.ssh +echo "${SSH_PUBLIC_KEY}" > /home/noble/.ssh/authorized_keys +apt update -y && apt install -y tmux +bash /opt/deeplearning/install-driver.sh \ No newline at end of file diff --git a/terraform/google/vars.tf b/terraform/google/vars.tf new file mode 100644 index 0000000..9075075 --- /dev/null +++ b/terraform/google/vars.tf @@ -0,0 +1,30 @@ +# Name variable definition +variable "name" { + default = "ml" +} + +# Definition of an instance type variable depending on the choice of tariff +variable "machine_type" { + default = "custom-8-30720" +} + +variable "project" { + default = "project" +} + +# Definition of the region in which the instance will be created +variable "region" { + default = "europe-west4" +} + +variable "zone" { + default = "europe-west4-a" +} + +variable "guest_accelerator" { + default = "nvidia-tesla-v100" +} + +variable "startup_script_vars" { + type = map +} From b2f8b7606a47a342a648be0deb030a1126054cd6 Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Sun, 20 Mar 2022 16:38:38 +0000 Subject: [PATCH 02/36] Added CPU dockerfile --- Dockerfile.cpu | 22 ++++++++++++++++++++++ 1 file changed, 22 insertions(+) create mode 100644 Dockerfile.cpu diff --git a/Dockerfile.cpu b/Dockerfile.cpu new file mode 100644 index 0000000..b437e1e --- /dev/null +++ b/Dockerfile.cpu @@ -0,0 +1,22 @@ +FROM python:3.8 + +RUN apt update -y + +RUN apt install libgl1 -y + +RUN pip3 install \ + torch==1.10.2+cpu \ + torchvision==0.11.3+cpu \ + torchaudio==0.10.2+cpu \ + -f https://download.pytorch.org/whl/cpu/torch_stable.html + +RUN pip3 install \ + opencv-python \ + sklearn \ + matplotlib \ + pandas \ + tqdm + +#COPY src /src + +ENTRYPOINT ["bash"] \ No newline at end of file From 123a5d3dde71f452c3c832de267c661b3175acd6 Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Sun, 20 Mar 2022 17:30:02 +0000 Subject: [PATCH 03/36] Added CNN code and tensors --- .gitattributes | 4 + src/autophotographer/__init__.py | 0 src/autophotographer/config.py | 24 ++++ src/autophotographer/dataset.py | 195 ++++++++++++++++++++++++++ src/autophotographer/model.py | 154 ++++++++++++++++++++ src/autophotographer/tensorImages.pt | 3 + src/autophotographer/tensorRatings.pt | 3 + 7 files changed, 383 insertions(+) create mode 100644 .gitattributes create mode 100644 src/autophotographer/__init__.py create mode 100644 src/autophotographer/config.py create mode 100644 src/autophotographer/dataset.py create mode 100644 src/autophotographer/model.py create mode 100644 src/autophotographer/tensorImages.pt create mode 100644 src/autophotographer/tensorRatings.pt diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..2803c07 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,4 @@ +*.mp4 filter=lfs diff=lfs merge=lfs -text +*.webm filter=lfs diff=lfs merge=lfs -text +*.jpg filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text diff --git a/src/autophotographer/__init__.py b/src/autophotographer/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/src/autophotographer/config.py b/src/autophotographer/config.py new file mode 100644 index 0000000..f5a4721 --- /dev/null +++ b/src/autophotographer/config.py @@ -0,0 +1,24 @@ +import torch +import os + +# https://pytorch.org/hub/pytorch_vision_resnet/ +MEAN = [0.485, 0.456, 0.406] +STD = [0.229, 0.224, 0.225] +IMAGE_SIZE = 224 + +VAL_SPLIT = 0.1 +DEVICE = "cuda" if torch.cuda.is_available() else "cpu" + +FEATURE_EXTRACTION_BATCH_SIZE = 256 +FINETUNE_BATCH_SIZE = 64 +PRED_BATCH_SIZE = 4 +EPOCHS = 20 +LR = 0.001 +LR_FINETUNE = 0.0005 # REMOVE +IMAGE_SIZE = 32 + +WARMUP_PLOT = os.path.join("output", "plot.png") +WARMUP_MODEL = os.path.join("output", "plot.pth") + +TENSOR_IMAGES_PATH = "tensorImages.pt" +TENSOR_RATINGS_PATH = "tensorRatings.pt" \ No newline at end of file diff --git a/src/autophotographer/dataset.py b/src/autophotographer/dataset.py new file mode 100644 index 0000000..23fc5ac --- /dev/null +++ b/src/autophotographer/dataset.py @@ -0,0 +1,195 @@ +import pandas as pd +import matplotlib.pyplot as plt +import matplotlib.image as mpimg +import random +import time +from sklearn.preprocessing import MinMaxScaler +import numpy as np +from sklearn.model_selection import train_test_split +import cv2 +from pathlib import Path +import config +from torchvision import transforms +import torch +from torch.utils.data import DataLoader +import os +from os.path import abspath +from PIL import Image, ImageFile +ImageFile.LOAD_TRUNCATED_IMAGES = True + +datasetDir = "/datasets/" +#datasetDir = "" +script_directory = os.path.dirname(__file__) +projectRoot = abspath(os.path.join(script_directory, "../..")) +#projectRoot = "/src/" +print(projectRoot) +tensorImagesPath = os.path.join(projectRoot, "src/autophotographer/tensorImages.pt") +tensorImagesPath = os.path.join(projectRoot, "src/autophotographer/tensorImages.pt") +tensorRatingsPath = os.path.join(projectRoot, "src/autophotographer/tensorRatings.pt") +tensorArrayPath = os.path.join(projectRoot, "src/autophotographer/tensorArray.pt") +filePathRatings = os.path.join(projectRoot, "data/ratings.txt") + +if not datasetDir == "": + filePathStyle = datasetDir + "AVA/style_image_lists/test.multilab" + filePathIds = datasetDir + "AVA/style_image_lists/test.jpgl" + filePathInfoAVA = datasetDir + "AVA/AVA.txt" + imgPath= datasetDir + "AVA/images/images" + + + +def load_aesthetic_attributes(filePathStyle, filePathIds): + columns = ["Complementary Colors", "Duotones", "HDR", "Image Grain", "Light On White", "Long Exposure", "Macro", "Motion Blur", "Negative Image", "Rule of Thirds", "Shallow DOF", "Silhouettes", "Soft Focus" , "Vanishing Point"] + dataFrameStyle = pd.read_csv(filePathStyle, sep=" ", header=None, names=columns) + + columns = ["ID"] + dataFrameId = pd.read_csv(filePathIds, sep=" ", header=None, names=columns) + + dataFrame = dataFrameId.join(dataFrameStyle) + + # return dataframe + return dataFrame + +def get_style_info(imageIndex): + df = load_aesthetic_attributes(filePathStyle, filePathIds) + imageInfo = df.loc[df['ID'] == imageIndex] + styleAttributes = "" + + for i in imageInfo: + if imageInfo[i].values[0] == 1: + if styleAttributes == "": + styleAttributes = i + else: + styleAttributes = styleAttributes + ", " + i + return styleAttributes + +def display_image_with_styles(imageIndex): + styleInfo = get_style_info(imageIndex) + image = mpimg.imread(imgPath + "/" + str(imageIndex) + ".jpg") + plt.imshow(image) + plt.title("ID: " + str(imageIndex) + ", Rating: " + str(calculate_image_rating(imageIndex))) + plt.text(0, 0, styleInfo, ha="center") + plt.axis("off") + plt.show() + +def get_random_image_index(): + df = load_aesthetic_attributes(filePathStyle, filePathIds) + imageIndexes = df["ID"].values + randomId = random.choice(imageIndexes) + return randomId + +def calculate_image_rating(imageIndex): + df = pd.read_csv(filePathInfoAVA, sep=" ", header=None) + imageInfo = df.loc[df[1] == imageIndex] + styleIndex = 2 + numOfRatings = 0 + score = 0 + #print(imageInfo) + while styleIndex <= 11: + score += imageInfo[styleIndex].values[0] * (styleIndex-1) + numOfRatings += imageInfo[styleIndex].values[0] + # print((str(styleIndex-1) + ": " + str(imageInfo[styleIndex].values[0]))) + styleIndex += 1 + #print(numOfRatings) + #print(score) + adjustedScore = score / numOfRatings + #print(adjustedScore) + return adjustedScore + +def get_all_image_ratings(): + imageRatings = {} + df = pd.read_csv(filePathInfoAVA, sep=" ", header=None, index_col=0) + listOfImageIndexes = df[1].values + imageIndex = 1 + startTime = time.time() + for image in listOfImageIndexes: + if imageIndex % 1000 == 0: + endTime = time.time() + timeTaken = endTime - startTime + print(str(imageIndex) + "/" + str(len(listOfImageIndexes)) + ": took " + str(timeTaken) + " seconds.") + rating = calculate_image_rating(image) + imageRatings[image] = rating + # print(str(image) + ": " + str(rating)) + imageIndex += 1 + + df = pd.DataFrame(list(imageRatings.items())) + return df + +def load_image_ratings(): + columns = ["id", "rating"] + df = pd.read_csv(filePathRatings, header=None, sep=" ", names=columns) + return df + +def process_image_ratings(df, train, test): + cs = MinMaxScaler() + trainContinuous = cs.fit_transform(train["rating"]) + testContinuous = cs.fit_transform(test["rating"]) + + return (trainContinuous, testContinuous) + +def load_images(df): + images = [] + for path in df.path.values: + image = cv2.imread(path) + image = cv2.resize(image, (32, 32)) + images.append(image) + return np.array(images) + +def remove_entries_for_missing_images(df, imgPath): + ids = [] + for path in Path(imgPath).glob('*.jpg'): + imgName = path.name + imgId = int(imgName[0:-4]) + ids.append(imgId) + df = df[df.id.isin(ids) == True] + return df + +def build_dataframe(df, imgPath): + imagePaths = [] + for id in df.id.values: + imagePath = imgPath + "/" + str(id) + ".jpg" + imagePaths.append(imagePath) + df['path'] = imagePaths + return df + +df = build_dataframe(remove_entries_for_missing_images(load_image_ratings(), imgPath), imgPath) + +def create_tensor_array(): + tensorArray = [] + for idx, row in df.iterrows(): + rating = row['rating'] + image = cv2.imread(row['path']) + image = cv2.resize(image, (32, 32)) + tensorTuple = (image, rating) + tensorArray.append(tensorTuple) + return tensorArray + +def load_in_tensors(): + print(tensorImagesPath) + print(tensorImagesPath) + print(tensorImagesPath) + tensorImages = torch.load(tensorImagesPath) + tensorRatings = torch.load(tensorRatingsPath) + tensorArray = torch.load(tensorArrayPath) + return (tensorImages, tensorRatings, tensorArray) + +def get_dataloader(df, transforms, batchSize, shuffle=True): + # Create a dataloader for dataset + tensorArray = [] + for idx, row in df.iterrows(): + #load each image path and process the data via transforms + transformedImg = transforms(pil_loader(row['path'])) + rating = row['rating'] + # form a tuple row with rating and the processed data + tensorTuple = (transformedImg, rating) + # append it to the array + tensorArray.append(tensorTuple) + + loader = DataLoader(tensorArray, batch_size=batchSize, shuffle=shuffle, num_workers=os.cpu_count(), + pin_memory=True if config.DEVICE == "cuda" else False) + + return (tensorArray, loader) + +def pil_loader(path): + with open(path, 'rb') as f: + img = Image.open(f) + return img.convert('RGB') \ No newline at end of file diff --git a/src/autophotographer/model.py b/src/autophotographer/model.py new file mode 100644 index 0000000..26f25dc --- /dev/null +++ b/src/autophotographer/model.py @@ -0,0 +1,154 @@ +import torch +import torch.nn as nn +import torch.optim as optim +from torchvision.models import resnet50 +from torchvision import transforms +from torch.utils.data import DataLoader + +from tqdm import tqdm +import time +import os +from os.path import abspath +import matplotlib.pyplot as plt + +import config +import dataset + +# projectRoot = "/src/" +script_directory = os.path.dirname(__file__) +projectRoot = abspath(os.path.join(script_directory, "../..")) +print("Project root: " + projectRoot) +INITIAL_PLOT_PATH = projectRoot + "/src/output/plot.png" +INTIIAL_MODEL_PATH = projectRoot + "/src/output/model.pth" + +# define transformations +trainTransform = transforms.Compose([ + transforms.RandomResizedCrop(config.IMAGE_SIZE), + transforms.RandomHorizontalFlip(), + transforms.RandomRotation(90), + transforms.ToTensor(), + transforms.Normalize(mean=config.MEAN, std=config.STD) +]) +valTransform = transforms.Compose([ + transforms.Resize((config.IMAGE_SIZE, config.IMAGE_SIZE)), + transforms.ToTensor(), + transforms.Normalize(mean=config.MEAN, std=config.STD) +]) + +valSetLen = int(len(dataset.df) * config.VAL_SPLIT) +trainSetLen = len(dataset.df) - valSetLen +trainSet = dataset.df[:trainSetLen] +valSet = dataset.df[trainSetLen:] + +print("Using " + config.DEVICE + "...") +# create data loaders +print("Getting dataloaders...") +#(trainDataset, trainLoader) = dataset.get_dataloader(trainSet, + #transforms=trainTransform, batchSize=config.FEATURE_EXTRACTION_BATCH_SIZE) +#torch.save(trainDataset, 'trainDataset.pt') +#(valDataset, valLoader) = dataset.get_dataloader(valSet, + #transforms=valTransform, batchSize=config.FEATURE_EXTRACTION_BATCH_SIZE, shuffle=False) +#torch.save(valDataset, 'valDataset.pt') + +valDataset = torch.load("/src/src/autophotographer/valDataset.pt") +valLoader = DataLoader(valDataset, batch_size=config.FEATURE_EXTRACTION_BATCH_SIZE, shuffle=False, num_workers=os.cpu_count(), + pin_memory=True if config.DEVICE == "cuda" else False) +trainDataset = torch.load("/src/src/autophotographer/trainDataset.pt") +trainLoader = DataLoader(trainDataset, batch_size=config.FEATURE_EXTRACTION_BATCH_SIZE, shuffle=True, num_workers=os.cpu_count(), + pin_memory=True if config.DEVICE == "cuda" else False) + +# Load the resnet model +model = resnet50(pretrained=True) + +# Freeze all existing layers +for parameter in model.parameters(): + parameter.requires_grad = False + +modelOutputFeatures = model.fc.in_features +model.fc = nn.Linear(modelOutputFeatures, 1) +model = model.to(config.DEVICE) + +# initialize loss function and optimizer +lossFunction = nn.L1Loss() +optimizer = torch.optim.Adam(model.fc.parameters(), lr=config.LR) + + +# calculate steps per epoch for training and validating set +trainSteps = len(trainDataset) // config.FEATURE_EXTRACTION_BATCH_SIZE +valSteps = len(valDataset) // config.FEATURE_EXTRACTION_BATCH_SIZE + +# initialize a dictionary to store training data +H = {"train_loss": [], "val_loss": []} + +# loop over epochs +print("Starting training...") +startTime = time.time() +for epoch in tqdm(range(config.EPOCHS)): + model.train() + + totalTrainLoss = 0 + totalValLoss = 0 + + trainCorrect = 0 + valCorrect = 0 + + for (i, (x, y)) in enumerate(trainLoader): + (x, y) = (x.to(config.DEVICE), y.to(config.DEVICE)) + pred = model(x) + new_shape = (len(y), 1) + y = y.view(new_shape) + loss = lossFunction(pred, y) + + loss.backward() + + if (i + 2) % 2 == 0: + optimizer.step() + optimizer.zero_grad() + + totalTrainLoss += loss + trainCorrect += (pred.argmax(1) == y).type( + torch.float).sum().item() + + with torch.no_grad(): + model.eval() + + for (x, y) in valLoader: + (x, y) = (x.to(config.DEVICE), y.to(config.DEVICE)) + + pred = model(x) + new_shape = (len(y), 1) + y = y.view(new_shape) + totalValLoss += lossFunction(pred, y) + valCorrect += (pred.argmax(1) == y).type( + torch.float).sum().item() + + # calculate the average training and validation loss + avgTrainLoss = totalTrainLoss / trainSteps + avgValLoss = totalValLoss / valSteps + # calculate the training and validation accuracy + #trainCorrect = trainCorrect / len(trainDataset) + #valCorrect = valCorrect / len(valDataset) + # update our training history + H["train_loss"].append(avgTrainLoss.cpu().detach().numpy()) + H["val_loss"].append(avgValLoss.cpu().detach().numpy()) + # print the model training and validation information + print("[INFO] EPOCH: {}/{}".format(epoch + 1, config.EPOCHS)) + print("Train loss: {:.6f}, Val loss: {:.6f}".format( + avgTrainLoss, avgValLoss)) + +# display the total time needed to perform the training +endTime = time.time() +print("[INFO] total time taken to train the model: {:.2f}s".format( + endTime - startTime)) +# plot the training loss and accuracy +plt.style.use("ggplot") +plt.figure() +plt.plot(H["train_loss"], label="train_loss") +plt.plot(H["val_loss"], label="val_loss") +plt.title("Training Loss on Dataset") +plt.xlabel("Epoch #") +plt.ylabel("Loss") +plt.legend(loc="lower left") +plt.savefig(INITIAL_PLOT_PATH) +# serialize the model to disk +torch.save(model, INTIIAL_MODEL_PATH) \ No newline at end of file diff --git a/src/autophotographer/tensorImages.pt b/src/autophotographer/tensorImages.pt new file mode 100644 index 0000000..01c1745 --- /dev/null +++ b/src/autophotographer/tensorImages.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:169231ec08c6a4dea43a6d6c430926fc65df5a2c86100463f7a0505a41f5ba90 +size 784921323 diff --git a/src/autophotographer/tensorRatings.pt b/src/autophotographer/tensorRatings.pt new file mode 100644 index 0000000..6ad5756 --- /dev/null +++ b/src/autophotographer/tensorRatings.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9c29c0fecae3177397bb478e7d542f9acd0f956088805eca001e1f0657cbebe8 +size 2044779 From 9cfdb0b91f0f202ce88b7fe08f4cfa34ff77fd77 Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Sun, 20 Mar 2022 17:48:03 +0000 Subject: [PATCH 04/36] Added val and train dataset tensors --- src/autophotographer/trainDataset.pt | 3 +++ src/autophotographer/valDataset.pt | 3 +++ 2 files changed, 6 insertions(+) create mode 100644 src/autophotographer/trainDataset.pt create mode 100644 src/autophotographer/valDataset.pt diff --git a/src/autophotographer/trainDataset.pt b/src/autophotographer/trainDataset.pt new file mode 100644 index 0000000..f70a6c6 --- /dev/null +++ b/src/autophotographer/trainDataset.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ce00bab2349b117bbb0232fe6d3f6ec425f2cd5e2ea9b1e001db317adc9df1d5 +size 2892879023 diff --git a/src/autophotographer/valDataset.pt b/src/autophotographer/valDataset.pt new file mode 100644 index 0000000..5a57b24 --- /dev/null +++ b/src/autophotographer/valDataset.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5d20c05d588afb13d04a1c08b3c56f29823cf203b94052b4e771eb3dc54dcbad +size 321370441 From eccc80425a17a6a5e75d31871e07cb904755aafe Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Mon, 21 Mar 2022 10:54:29 +0000 Subject: [PATCH 05/36] Refactored for portability --- src/autophotographer/config.py | 2 - src/autophotographer/dataframe.csv | 255509 ++++++++++++++++++++++++++ src/autophotographer/dataset.py | 5 +- src/autophotographer/model.py | 10 +- 4 files changed, 255518 insertions(+), 8 deletions(-) create mode 100644 src/autophotographer/dataframe.csv diff --git a/src/autophotographer/config.py b/src/autophotographer/config.py index f5a4721..52b6857 100644 --- a/src/autophotographer/config.py +++ b/src/autophotographer/config.py @@ -10,11 +10,9 @@ VAL_SPLIT = 0.1 DEVICE = "cuda" if torch.cuda.is_available() else "cpu" FEATURE_EXTRACTION_BATCH_SIZE = 256 -FINETUNE_BATCH_SIZE = 64 PRED_BATCH_SIZE = 4 EPOCHS = 20 LR = 0.001 -LR_FINETUNE = 0.0005 # REMOVE IMAGE_SIZE = 32 WARMUP_PLOT = os.path.join("output", "plot.png") diff --git a/src/autophotographer/dataframe.csv b/src/autophotographer/dataframe.csv new file mode 100644 index 0000000..3d1bc5c --- /dev/null +++ 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"src/autophotographer/tensorImages.pt") -tensorImagesPath = os.path.join(projectRoot, "src/autophotographer/tensorImages.pt") tensorRatingsPath = os.path.join(projectRoot, "src/autophotographer/tensorRatings.pt") tensorArrayPath = os.path.join(projectRoot, "src/autophotographer/tensorArray.pt") filePathRatings = os.path.join(projectRoot, "data/ratings.txt") +dataframePath = os.path.join(projectRoot, "src/autophotographer/dataframe.csv") if not datasetDir == "": filePathStyle = datasetDir + "AVA/style_image_lists/test.multilab" @@ -151,7 +151,8 @@ def build_dataframe(df, imgPath): df['path'] = imagePaths return df -df = build_dataframe(remove_entries_for_missing_images(load_image_ratings(), imgPath), imgPath) +#df = build_dataframe(remove_entries_for_missing_images(load_image_ratings(), imgPath), imgPath) +df = pd.read_csv(dataframePath, index_col = 0) def create_tensor_array(): tensorArray = [] diff --git a/src/autophotographer/model.py b/src/autophotographer/model.py index 26f25dc..1824fc4 100644 --- a/src/autophotographer/model.py +++ b/src/autophotographer/model.py @@ -18,8 +18,10 @@ import dataset script_directory = os.path.dirname(__file__) projectRoot = abspath(os.path.join(script_directory, "../..")) print("Project root: " + projectRoot) -INITIAL_PLOT_PATH = projectRoot + "/src/output/plot.png" -INTIIAL_MODEL_PATH = projectRoot + "/src/output/model.pth" +INITIAL_PLOT_PATH = os.path.join(projectRoot, "src/output/plot.png") +INTIIAL_MODEL_PATH = os.path.join(projectRoot, "src/output/model.pth") +valDatasetPath = os.path.join(projectRoot, "src/autophotographer/valDataset.pt") +trainDatasetPath = os.path.join(projectRoot, "src/autophotographer/trainDataset.pt") # define transformations trainTransform = transforms.Compose([ @@ -50,10 +52,10 @@ print("Getting dataloaders...") #transforms=valTransform, batchSize=config.FEATURE_EXTRACTION_BATCH_SIZE, shuffle=False) #torch.save(valDataset, 'valDataset.pt') -valDataset = torch.load("/src/src/autophotographer/valDataset.pt") +valDataset = torch.load(valDatasetPath) valLoader = DataLoader(valDataset, batch_size=config.FEATURE_EXTRACTION_BATCH_SIZE, shuffle=False, num_workers=os.cpu_count(), pin_memory=True if config.DEVICE == "cuda" else False) -trainDataset = torch.load("/src/src/autophotographer/trainDataset.pt") +trainDataset = torch.load(trainDatasetPath) trainLoader = DataLoader(trainDataset, batch_size=config.FEATURE_EXTRACTION_BATCH_SIZE, shuffle=True, num_workers=os.cpu_count(), pin_memory=True if config.DEVICE == "cuda" else False) From e1b7a87bf2444decbcd03c0f2b0eba86bc7e0ac4 Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Wed, 23 Mar 2022 04:46:35 +0000 Subject: [PATCH 06/36] Added initial training models and results --- .gitattributes | 2 + docs/mid-project.odp | Bin 0 -> 447282 bytes src/__init__.py | 0 src/autophotographer/dataset.py | 2 +- src/autophotographer/model.py | 2 +- src/output/21-03-2022/model.pth | 3 + 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literal 0 HcmV?d00001 diff --git a/src/__init__.py b/src/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/src/autophotographer/dataset.py b/src/autophotographer/dataset.py index 5114978..f26e52c 100644 --- a/src/autophotographer/dataset.py +++ b/src/autophotographer/dataset.py @@ -8,7 +8,7 @@ import numpy as np from sklearn.model_selection import train_test_split import cv2 from pathlib import Path -import config +from . import config from torchvision import transforms import torch from torch.utils.data import DataLoader diff --git a/src/autophotographer/model.py b/src/autophotographer/model.py index 1824fc4..53794e5 100644 --- a/src/autophotographer/model.py +++ b/src/autophotographer/model.py @@ -71,7 +71,7 @@ model.fc = nn.Linear(modelOutputFeatures, 1) model = model.to(config.DEVICE) # initialize loss function and optimizer -lossFunction = nn.L1Loss() +lossFunction = nn.L1Loss() # mean absolute error optimizer = torch.optim.Adam(model.fc.parameters(), lr=config.LR) diff --git a/src/output/21-03-2022/model.pth b/src/output/21-03-2022/model.pth new file mode 100644 index 0000000..8ddc489 --- /dev/null +++ b/src/output/21-03-2022/model.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:87b34729f1394caaf71f3264087063180b639b8c4177df440447557762a6ace3 +size 94375425 diff --git a/src/output/21-03-2022/plot.png b/src/output/21-03-2022/plot.png new file mode 100644 index 0000000..fdbfa39 --- /dev/null +++ b/src/output/21-03-2022/plot.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:72405c4fbd139e5018cdacdcd5edf614d2d418ef3313d6e5c1e9fb659be8a5b4 +size 37653 diff --git a/src/output/22-03-2022/model.pth b/src/output/22-03-2022/model.pth new file mode 100644 index 0000000..97cfe87 --- /dev/null +++ b/src/output/22-03-2022/model.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:be062cf212cfbbb20386e705b48340885b468872bd8b81c3ce11c7eb3a3efe62 +size 94375425 diff --git a/src/output/22-03-2022/plot.png b/src/output/22-03-2022/plot.png new file mode 100644 index 0000000..1002b80 --- /dev/null +++ b/src/output/22-03-2022/plot.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:91959decf7d6a2a7dec7c4f6b99eea7a4d8ef8dd504b290e516024b48d171e64 +size 33199 diff --git a/src/output/22-03-2022/slurm-3608.out b/src/output/22-03-2022/slurm-3608.out new file mode 100644 index 0000000..29e16b7 --- /dev/null +++ b/src/output/22-03-2022/slurm-3608.out @@ -0,0 +1,4007 @@ +/home/osp1/mmp-osp1 +Project root: /home/osp1/mmp-osp1 +Using cuda... +Getting dataloaders... +Starting training... + 0%| | 0/2000 [00:00 gtRating: + percentage = round(((pred/gtRating) - 1) * 100, 5) + diff = "+" + str(percentage) + else: + percentage = round(((gtRating/pred) - 1) * 100, 5) + diff = "-" + str(percentage) + # add the results and image to the plot + info = "Ground Truth: {}, Predicted: {}, Diff: {}%".format(gtRating, + pred, diff) + plt.imshow(image) + plt.title(info) + plt.axis("off") + # show the plot + plt.tight_layout() + date = datetime.datetime.now() + dateString = str(date.year) + "-" + str(date.month) + "-" + str(date.day) + "_" + str(date.hour) + "-" + str(date.minute) + "-" + str(date.second) + PLOT_PATH = os.path.join(PLOT_PATH, "predict-plot-" + dateString + ".png") + plt.savefig(PLOT_PATH) + plt.show() From 68ff4ea0ad9079a69977ec18f8a5c83e80589519 Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Wed, 23 Mar 2022 10:32:11 +0000 Subject: [PATCH 07/36] Refactored and removed dead code in model and predict --- src/autophotographer/model.py | 54 ++++++++++++++++------------------- src/predict.py | 42 ++++++++++++++------------- 2 files changed, 47 insertions(+), 49 deletions(-) diff --git a/src/autophotographer/model.py b/src/autophotographer/model.py index 53794e5..071c229 100644 --- a/src/autophotographer/model.py +++ b/src/autophotographer/model.py @@ -23,7 +23,7 @@ INTIIAL_MODEL_PATH = os.path.join(projectRoot, "src/output/model.pth") valDatasetPath = os.path.join(projectRoot, "src/autophotographer/valDataset.pt") trainDatasetPath = os.path.join(projectRoot, "src/autophotographer/trainDataset.pt") -# define transformations +# Declare transformations trainTransform = transforms.Compose([ transforms.RandomResizedCrop(config.IMAGE_SIZE), transforms.RandomHorizontalFlip(), @@ -37,12 +37,14 @@ valTransform = transforms.Compose([ transforms.Normalize(mean=config.MEAN, std=config.STD) ]) +# Split dataset into val and train valSetLen = int(len(dataset.df) * config.VAL_SPLIT) trainSetLen = len(dataset.df) - valSetLen trainSet = dataset.df[:trainSetLen] valSet = dataset.df[trainSetLen:] print("Using " + config.DEVICE + "...") + # create data loaders print("Getting dataloaders...") #(trainDataset, trainLoader) = dataset.get_dataloader(trainSet, @@ -52,6 +54,7 @@ print("Getting dataloaders...") #transforms=valTransform, batchSize=config.FEATURE_EXTRACTION_BATCH_SIZE, shuffle=False) #torch.save(valDataset, 'valDataset.pt') +# Load datasets tensors from disk valDataset = torch.load(valDatasetPath) valLoader = DataLoader(valDataset, batch_size=config.FEATURE_EXTRACTION_BATCH_SIZE, shuffle=False, num_workers=os.cpu_count(), pin_memory=True if config.DEVICE == "cuda" else False) @@ -66,24 +69,25 @@ model = resnet50(pretrained=True) for parameter in model.parameters(): parameter.requires_grad = False +# Replace last layer with a FC single output layer modelOutputFeatures = model.fc.in_features model.fc = nn.Linear(modelOutputFeatures, 1) model = model.to(config.DEVICE) -# initialize loss function and optimizer -lossFunction = nn.L1Loss() # mean absolute error +# Initialize otimizer and loss function optimizer = torch.optim.Adam(model.fc.parameters(), lr=config.LR) +lossFunction = nn.L1Loss() # mean absolute error -# calculate steps per epoch for training and validating set +# Calculate steps for train and validation trainSteps = len(trainDataset) // config.FEATURE_EXTRACTION_BATCH_SIZE valSteps = len(valDataset) // config.FEATURE_EXTRACTION_BATCH_SIZE -# initialize a dictionary to store training data -H = {"train_loss": [], "val_loss": []} +# Store training data +dataDict = {"train_loss": [], "val_loss": []} -# loop over epochs -print("Starting training...") +# Loop over epochs +print("Training...") startTime = time.time() for epoch in tqdm(range(config.EPOCHS)): model.train() @@ -91,8 +95,6 @@ for epoch in tqdm(range(config.EPOCHS)): totalTrainLoss = 0 totalValLoss = 0 - trainCorrect = 0 - valCorrect = 0 for (i, (x, y)) in enumerate(trainLoader): (x, y) = (x.to(config.DEVICE), y.to(config.DEVICE)) @@ -108,8 +110,6 @@ for epoch in tqdm(range(config.EPOCHS)): optimizer.zero_grad() totalTrainLoss += loss - trainCorrect += (pred.argmax(1) == y).type( - torch.float).sum().item() with torch.no_grad(): model.eval() @@ -121,36 +121,32 @@ for epoch in tqdm(range(config.EPOCHS)): new_shape = (len(y), 1) y = y.view(new_shape) totalValLoss += lossFunction(pred, y) - valCorrect += (pred.argmax(1) == y).type( - torch.float).sum().item() - # calculate the average training and validation loss + # Calculate the average training and validation loss avgTrainLoss = totalTrainLoss / trainSteps avgValLoss = totalValLoss / valSteps - # calculate the training and validation accuracy - #trainCorrect = trainCorrect / len(trainDataset) - #valCorrect = valCorrect / len(valDataset) - # update our training history - H["train_loss"].append(avgTrainLoss.cpu().detach().numpy()) - H["val_loss"].append(avgValLoss.cpu().detach().numpy()) - # print the model training and validation information - print("[INFO] EPOCH: {}/{}".format(epoch + 1, config.EPOCHS)) + + # Add to history + dataDict["train_loss"].append(avgTrainLoss.cpu().detach().numpy()) + dataDict["val_loss"].append(avgValLoss.cpu().detach().numpy()) + # Print end of epoch progress + print("EPOCH: {}/{}".format(epoch + 1, config.EPOCHS)) print("Train loss: {:.6f}, Val loss: {:.6f}".format( avgTrainLoss, avgValLoss)) -# display the total time needed to perform the training +# Display time taken for training endTime = time.time() -print("[INFO] total time taken to train the model: {:.2f}s".format( +print("Total time taken to train the model: {:.2f}s".format( endTime - startTime)) -# plot the training loss and accuracy +# Plot the training and validation loss plt.style.use("ggplot") plt.figure() -plt.plot(H["train_loss"], label="train_loss") -plt.plot(H["val_loss"], label="val_loss") +plt.plot(dataDict["train_loss"], label="train_loss") +plt.plot(dataDict["val_loss"], label="val_loss") plt.title("Training Loss on Dataset") plt.xlabel("Epoch #") plt.ylabel("Loss") plt.legend(loc="lower left") plt.savefig(INITIAL_PLOT_PATH) -# serialize the model to disk +# Save model torch.save(model, INTIIAL_MODEL_PATH) \ No newline at end of file diff --git a/src/predict.py b/src/predict.py index 5768c34..4782d1a 100644 --- a/src/predict.py +++ b/src/predict.py @@ -24,19 +24,18 @@ parser.add_argument('image', type=os.path.abspath, metavar='image-location', nar help='path(s) to input image(s)') args = vars(parser.parse_args()) +# Load model model = torch.load(args["model"], config.DEVICE) model.to(config.DEVICE) # Declare transforms -# build our data pre-processing pipeline valTransform = transforms.Compose([ transforms.Resize((config.IMAGE_SIZE, config.IMAGE_SIZE)), transforms.ToTensor(), transforms.Normalize(mean=config.MEAN, std=config.STD) ]) -# calulate the std dev and inverse mean -# calculate the inverse mean and standard deviation +# Calulate the inverse std and inverse mean invMean = [-m/s for (m, s) in zip(config.MEAN, config.STD)] invStd = [1/s for s in config.STD] @@ -44,7 +43,7 @@ invStd = [1/s for s in config.STD] deNormalize = transforms.Normalize(mean=invMean, std=invStd) # load dataset and dataloader -print("[INFO] loading the dataset...") +print("Loading dataset...") valSetLen = int(len(dataset.df) * config.VAL_SPLIT) trainSetLen = len(dataset.df) - valSetLen valSet = dataset.df[trainSetLen:] @@ -57,55 +56,58 @@ if torch.cuda.is_available(): else: map_location = "cpu" -print("[INFO] loading the model...") +# Load in model +print("Loading model...") model = torch.load(args["model"], map_location=map_location) model.to(config.DEVICE) model.eval() +# Process batch batch = next(iter(valLoader)) (images, ratings) = (batch[0], batch[1]) +# Declare figure fig = plt.figure("Results", figsize=(10, 10)) with torch.no_grad(): - # send the images to the device + # Send the images to CPU/GPU images = images.to(config.DEVICE) - # make the predictions - print("[INFO] predicting...") + + # Make a prediction on the images + print("Predicting...") preds = model(images) - # loop over all the batch + + # Loop over each element in the batch for i in range(0, config.PRED_BATCH_SIZE): - # initalize a subplot + # Initalize a subplot ax = plt.subplot(config.PRED_BATCH_SIZE, 1, i + 1) - # grab the image, de-normalize it, scale the raw pixel - # intensities to the range [0, 255], and change the channel - # ordering from channels first tp channels last + + # De-normalize image, scale the pixel range to 255 image = images[i] image = deNormalize(image).cpu().numpy() image = (image * 255).astype("uint8") image = image.transpose((1, 2, 0)) - # grab the ground truth label 5 decimal places + # Retrieve the ground truth to 5 decimal places gtRating = round(ratings[i].cpu().numpy().tolist(), 5) - # grab the predicted label 5 decimal places + # Retrieve the prediction to 5 decimal places pred = round(preds[i].cpu().numpy().tolist()[0], 5) - # calculate percentage difference + # Calculate percentage difference if pred > gtRating: percentage = round(((pred/gtRating) - 1) * 100, 5) diff = "+" + str(percentage) else: percentage = round(((gtRating/pred) - 1) * 100, 5) diff = "-" + str(percentage) - # add the results and image to the plot + # Add the ground truth, prediction and % diff to the plot info = "Ground Truth: {}, Predicted: {}, Diff: {}%".format(gtRating, pred, diff) plt.imshow(image) plt.title(info) plt.axis("off") - # show the plot + # Save plot to disk plt.tight_layout() date = datetime.datetime.now() dateString = str(date.year) + "-" + str(date.month) + "-" + str(date.day) + "_" + str(date.hour) + "-" + str(date.minute) + "-" + str(date.second) PLOT_PATH = os.path.join(PLOT_PATH, "predict-plot-" + dateString + ".png") - plt.savefig(PLOT_PATH) - plt.show() + plt.savefig(PLOT_PATH) \ No newline at end of file From e29bf123f1c7d9af76cc14734a7dcecf0abccdc5 Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Wed, 23 Mar 2022 10:41:09 +0000 Subject: [PATCH 08/36] Added prediction batch size to config --- src/autophotographer/config.py | 1 + 1 file changed, 1 insertion(+) diff --git a/src/autophotographer/config.py b/src/autophotographer/config.py index 52b6857..bfc5c68 100644 --- a/src/autophotographer/config.py +++ b/src/autophotographer/config.py @@ -14,6 +14,7 @@ PRED_BATCH_SIZE = 4 EPOCHS = 20 LR = 0.001 IMAGE_SIZE = 32 +PRED_BATCH_SIZE = 4 WARMUP_PLOT = os.path.join("output", "plot.png") WARMUP_MODEL = os.path.join("output", "plot.pth") From 9846c60f2c25e0e02e844982e375a88b572fca33 Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Wed, 23 Mar 2022 13:11:46 +0000 Subject: [PATCH 09/36] Update original pipline to compare CNN and Conventional --- docs/mid-project.odp | Bin 447282 -> 483436 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/docs/mid-project.odp b/docs/mid-project.odp index c2e4eab221b6639cbff07abe178d1f6cae44a945..9bbacd7926309724733ab4b5c03f18436f1b4a6d 100644 GIT binary patch delta 296417 zcmcG!byQU0`!5Po15!gtNelu~(%mqWq=1ApNH<8wCS?F=>5>o-q`Ol(rMslN8_(eP zch)(7-Su5}-OHKM5 z*&zOFNfrFp&V>pBf#COw(|tw(=v2-d>9|;x4C|p7j5~zyK+;sXKN!Cx(nyZ)gCB%Hnx>5!h+^|PUL&M;DN{(8W5tF{__RrRaN_V6 z$3ajjK>!!K_MP}R23zr3hf9!EGMd;=x-jtoklcl05&i(orC!cBj|6r8Kw~il`lw7P z&8IBaE-$b);rMlG#WVsi#%<@@n8-*4%cSyAeasMihS>InmPT)~GG#FyKVLDJx(lyt 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zp!bg;$d?)h2gGCmi)8jU@jvIye@n<(2@R%fY2xDQWaiAm_95W^FQ&!6M(Cd+ ogE9<0dR6-z8dU8C!;SL462T2W5?_5_KxBrnQZR0#FdstvACwqAssI20 From 868473e2844c0afb69fe7e1b1bfdc214cabf387d Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Sat, 26 Mar 2022 03:50:02 +0000 Subject: [PATCH 10/36] Added basic pipeline --- src/autophotographer.py | 87 +++++++++++++++++++++++++++++++++++++++++ 1 file changed, 87 insertions(+) create mode 100644 src/autophotographer.py diff --git a/src/autophotographer.py b/src/autophotographer.py new file mode 100644 index 0000000..09c8650 --- /dev/null +++ b/src/autophotographer.py @@ -0,0 +1,87 @@ +import cv2 +import sys +import argparse +import os +import pathlib +import numpy +import time + +# Process arguments +def parse_arguments(argv=None): + parser = argparse.ArgumentParser() + parser.add_argument('-i', '--input', dest='inputfile', type=pathlib.Path, help='Specify a video file') + parser.add_argument('-o', '--output', dest='outputfolder', type=pathlib.Path, help='Specify a folder to save frames to') + return parser.parse_args() + +# Convert video to frames +def video_to_frames(): + startTime = time.time() + print("Converting video to frames...") + capture = cv2.VideoCapture(str(inputfile)) + success,image = capture.read() + count = 0 + while success: + outputfile = outputfolder + "/frame%d.jpg" % count + # print(outputfile) + cv2.imwrite(outputfile, image) + success,image = capture.read() + count +=1 + endTime = time.time() + totalTime = endTime - startTime + print("Exported " + str(count) + " frames in " + str(totalTime) + " seconds.") + +# Shrink set based on filesize +def display_file_sizes(): + filesizes = [] + for filename in os.listdir(outputfolder): + filepath = outputfolder + "/" + filename + filesize = os.path.getsize(filepath) + print(filepath + ": " + str(filesize)) + filesizes.append(filesize) + # work out average + average = sum(filesizes)/len(filesizes) + print ("Average is: " + str(average)) + # delete files below average + count = 0 + for filename in os.listdir(outputfolder): + filepath = outputfolder + "/" + filename + if filesizes[count] < average: + # print(filepath + ": " + str(filesizes[count])) + os.remove(filepath) + count += 1 + +#def remove_similar_frames(): +def order_frames_by_filesize(): + frames = os.listdir(outputfolder) + frames = sorted(frames, key = lambda x: os.stat(os.path.join(outputfolder, x)).st_size, reverse = True) + for frame in frames: + filesize = os.stat(os.path.join(outputfolder, frame)).st_size + if filesize > 1024: + filesize = filesize / 1024 + print(frame + ": " + str(filesize) + " KB") + else: + print(frame + ": " + str(filesize)) + +def order_frames_by_brightness(): + frames_path = os.listdir(outputfolder) + frames_path = sorted(frames_path, key = return_frame_brightness) + for frame_path in frames_path: + print(frame_path + ": " + str(return_frame_brightness(frame_path))) + +def return_frame_brightness(frame_path): + frame = cv2.imread(os.path.join(outputfolder, frame_path)) + hsv_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) + h, s, v = cv2.split(hsv_frame) + average_v = numpy.average(v) + return average_v + +args = parse_arguments() +inputfile = str(args.inputfile.absolute()) +outputfolder = str(args.outputfolder.absolute()) + +# Convert video to frames +video_to_frames() + +display_file_sizes() +#order_frames_by_filesize() +#order_frames_by_brightness() \ No newline at end of file From 8258b225ceb2dc3ffa081273cb38fd44a3036d7e Mon Sep 17 00:00:00 2001 From: oscarpocock Date: Tue, 5 Apr 2022 12:25:27 +0100 Subject: [PATCH 11/36] Added general pipeline and config file --- README.md | 12 ++ src/autophotographer.py | 300 ++++++++++++++++++++++++++++++---------- src/config.yml | 29 ++++ 3 files changed, 267 insertions(+), 74 deletions(-) create mode 100644 README.md create mode 100644 src/config.yml diff --git a/README.md b/README.md new file mode 100644 index 0000000..4b34f33 --- /dev/null +++ b/README.md @@ -0,0 +1,12 @@ +# Autophotographer + +Autophotographer is a tool that helps users filter the best images from a video. + +``` +. +├── docs Report and Project proposal +├── img images for the repository +├── README.md +├── src project source code +└── terraform terraform IaC +``` \ No newline at end of file diff --git a/src/autophotographer.py b/src/autophotographer.py index 09c8650..6b94504 100644 --- a/src/autophotographer.py +++ b/src/autophotographer.py @@ -1,87 +1,239 @@ import cv2 -import sys import argparse import os -import pathlib -import numpy -import time +from os.path import abspath +import pandas +import matplotlib.pyplot as plt +import numpy as np +from skimage.exposure import is_low_contrast +import yaml -# Process arguments -def parse_arguments(argv=None): - parser = argparse.ArgumentParser() - parser.add_argument('-i', '--input', dest='inputfile', type=pathlib.Path, help='Specify a video file') - parser.add_argument('-o', '--output', dest='outputfolder', type=pathlib.Path, help='Specify a folder to save frames to') - return parser.parse_args() +# Import local packages +from focusdetection.focusdetection import fast_fourier -# Convert video to frames -def video_to_frames(): - startTime = time.time() - print("Converting video to frames...") - capture = cv2.VideoCapture(str(inputfile)) - success,image = capture.read() - count = 0 - while success: - outputfile = outputfolder + "/frame%d.jpg" % count - # print(outputfile) - cv2.imwrite(outputfile, image) - success,image = capture.read() - count +=1 - endTime = time.time() - totalTime = endTime - startTime - print("Exported " + str(count) + " frames in " + str(totalTime) + " seconds.") +#import sys +#import pathlib +#import numpy +#import time -# Shrink set based on filesize -def display_file_sizes(): - filesizes = [] - for filename in os.listdir(outputfolder): - filepath = outputfolder + "/" + filename - filesize = os.path.getsize(filepath) - print(filepath + ": " + str(filesize)) - filesizes.append(filesize) - # work out average - average = sum(filesizes)/len(filesizes) - print ("Average is: " + str(average)) - # delete files below average - count = 0 - for filename in os.listdir(outputfolder): - filepath = outputfolder + "/" + filename - if filesizes[count] < average: - # print(filepath + ": " + str(filesizes[count])) - os.remove(filepath) - count += 1 +# accepted image formats +image_formats = (".jpg", ".jpeg", ".png") -#def remove_similar_frames(): -def order_frames_by_filesize(): - frames = os.listdir(outputfolder) - frames = sorted(frames, key = lambda x: os.stat(os.path.join(outputfolder, x)).st_size, reverse = True) - for frame in frames: - filesize = os.stat(os.path.join(outputfolder, frame)).st_size - if filesize > 1024: - filesize = filesize / 1024 - print(frame + ": " + str(filesize) + " KB") +# accepted video formats +video_formats = (".mp4", ".mov", ".avi", ".flv", ".mkv") + +# load config file +def load_config(path=os.path.join(os.path.dirname(__file__), "./config.yml")): + abs_path = os.path.abspath(path) + + # check if file exists + if os.path.exists(abs_path): + if abs_path.lower().endswith((".yml", ".yaml")): + print("[INFO] Loading config...") + # attempt to open file + with open(abs_path) as file: + return yaml.safe_load(file) else: - print(frame + ": " + str(filesize)) + print("[ERRO] Please specify a file with extension '.yml' or '.yaml'.") + quit() + else: + print("[ERRO] Path does not exist") + quit() -def order_frames_by_brightness(): - frames_path = os.listdir(outputfolder) - frames_path = sorted(frames_path, key = return_frame_brightness) - for frame_path in frames_path: - print(frame_path + ": " + str(return_frame_brightness(frame_path))) +def filter_to_function(imagefilter, prettyName=False): + if imageFilter == "brightness": + # filter_brightness() + print("[INFO] Filtering based on brightness...") + elif imageFilter == "filesize": + # filter_filesize() + print("[INFO] Filtering based on filesize...") + elif imageFilter == "contrast": + # filter_contrast() + print("[INFO] Filtering based on contrast...") + elif imageFilter == "focus": + # filter_focus() + print("[INFO] Filtering based on focus...") + else: + print("[WARN] Filter not recognised. Ignoring...") -def return_frame_brightness(frame_path): - frame = cv2.imread(os.path.join(outputfolder, frame_path)) - hsv_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) - h, s, v = cv2.split(hsv_frame) - average_v = numpy.average(v) - return average_v +# filter paths by accepted file extensions +def filter_paths(paths): + print("[INFO] Filtering paths by filetype...") + filtered_paths = [] + for path in paths: + if path.lower().endswith(video_formats + image_formats): + filtered_paths.append(path) + return filtered_paths -args = parse_arguments() -inputfile = str(args.inputfile.absolute()) -outputfolder = str(args.outputfolder.absolute()) +# load frames from images +def load_video(path): + print("[INFO] Loading video...") + stream = cv2.VideoCapture(path) + frames = [] + while True: + (retrieved, frame) = stream.read() + if not retrieved: + break + frames.append(frame) + return frames -# Convert video to frames -video_to_frames() +# load images +def load_image(path): + print("[INFO] Loading image...") + image = cv2.imread(path) + return image -display_file_sizes() -#order_frames_by_filesize() -#order_frames_by_brightness() \ No newline at end of file +# load images respective of their file type +def load_files(paths): + print("[INFO] Loading files...") + # set loaded counters to 0 + images_loaded = 0 + videos_loaded = 0 + videos = [] + images = [] + + # load in all image/video files + for path in paths: + # if file is an image, just load it + if path.lower().endswith(image_formats): + image = load_image(path) + images_loaded += 1 + images.append(image) + # if file is a video, break into frames and load them + elif path.lower().endswith(video_formats): + frames = load_video(path) + videos.append(frames) + videos_loaded += 1 + else: + print("[INFO] Skipped non-image/non-video file.") + + # return information on number of files loaded + if videos_loaded == 0 and images_loaded == 0: + print("[INFO] No valid images or videos found.") + else: + print("[INFO] {} image(s) and {} video(s) loaded.".format(images_loaded, videos_loaded)) + + total_frames = 0 + for video in videos: + total_frames += len(video) + total_images = total_frames + len(images) + print("[INFO] Total images loaded (including video frames): {}".format(total_images)) + + return (images, videos) + +# filter images based on filesize +def filter_filesize(paths): + print("[INFO] Filtering by filesize...") + filesizes = [] + filtered_paths = [] + # calculate avg filesize + for path in paths: + filesize = os.path.getsize(path) + filesizes.append(filesize) + filesize_avg = sum(filesizes)/len(filesizes) + filesize_std = pandas.Series(filesizes).std(ddof=0) + filesize_min = min(filesizes) + filesize_max = max(filesizes) + filesize_filter = filesize_avg - filesize_std + print("[INFO] min size: {}, max size: {}, avg size: {}, std size: {}".format( + filesize_min, filesize_max, filesize_avg, filesize_std)) + + # remove images that are 3 std below mean + for path in paths: + if os.path.getsize(path) > filesize_filter: + filtered_paths.append(path) + + return filtered_paths + +# plot the distribution of file sizes for data insight +def plot_filesizes(paths): + filesizes = [] + for path in paths: + if path.lower().endswith(image_formats): + filesize = os.path.getsize(path) + filesizes.append(filesize) + sorted_fs = sorted(filesizes) + data = np.array(sorted_fs) + fig = plt.figure(figsize =(10, 7)) + plt.boxplot(data) + plt.show() + +# resize image and turn to greyscale +def process_image(path, width): + print("[INFO] Processing image...") + image = cv2.imread(path) + height = int(image.shape[0] * (width / image.shape[0])) + image = cv2.resize(image, (width, height)) + image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) + return image + +# filter images based on contrast +def filter_contrast(paths, thresh=0.35): + print("[INFO] Filtering by contrast...") + filtered_paths = [] + for path in paths: + if path.lower().endswith(video_formats): + continue + print(path) + image = process_image(path, 500) + if is_low_contrast(image, thresh): + print("[INFO] Low contrast") + else: + print("[INFO] High contrast") + filtered_paths.append(path) + return filtered_paths + +# filter images based on brightness +def filter_brightness(paths): + print("[INFO] Filtering by brightness...") + +# filter images based on focus/blurriness +def filter_focus(paths): + print("[INFO] Filtering by focus/blurriness...") + filtered_paths = [] + # read images in greyscale + for path in paths: + if path.lower().endswith(video_formats): + continue + print(path) + image = process_image(path, 500) + (mean, blurry) = fast_fourier(image, size=60, thresh=30) + blurStats = "Blurry ({:.4f})" if blurry else "Not blurry ({:.4f})" + if blurry: + print(("[INFO] {}: " + blurStats).format(path, mean)) + else: + filtered_paths.append(path) + return filtered_paths + +# rank remaining images using a CNN +def rank_images(): + print("[INFO] Ranking images using machine learning...") + +# parse commande line arguments +parser = argparse.ArgumentParser() +parser.add_argument("-i", "--input", type=os.path.abspath, required=True, nargs="+", + help="path to video or image folder") +parser.add_argument("-c", "--config", type=os.path.abspath, help="path to config file") +args = vars(parser.parse_args()) + +paths = filter_paths(args["input"]) + +# load in config file +if args["config"] is not None: + autophotoConf = load_config(args["config"]) +else: + autophotoConf = load_config() + +# Order and selection of operations from config file +for imageFilter in autophotoConf["filters"]: + n_of_images_before = len(paths) + filter_to_function(imageFilter) + n_of_images_after = len(paths) + + # calculate set difference after filtering + diff = n_of_images_before - n_of_images_after + print("[INFO] Filtered {}/{} images via {} filtering.".format( + n_of_images_after, n_of_images_before, imageFilter)) + +if autophotoConf["CNNrank"]: + print("[INFO] Running CNN ranking...") \ No newline at end of file diff --git a/src/config.yml b/src/config.yml new file mode 100644 index 0000000..38992a8 --- /dev/null +++ b/src/config.yml @@ -0,0 +1,29 @@ +--- +# Config file for autophotographer + +# List of filters to apply in order +filters: + - brightness + - filesize + - contrast + - focus + +# Whether or not to apply CNN ranking +CNNrank: True + +# Options for focus filter +brightness_options: + threshold: 0.35 + +# Options for focus filter +filesize_options: + threshold: 0.35 + +# Options for focus filter +contrast_options: + threshold: 0.35 + +# Options for focus filter +focus_options: + threshold: 0.35 +... \ No newline at end of file From 36310909ee02860ed966968f60953d67b6156a2c Mon Sep 17 00:00:00 2001 From: oscarpocock Date: Tue, 5 Apr 2022 17:21:54 +0100 Subject: [PATCH 12/36] Implemented basic focus detection, closes #5 --- src/focusdetection/__init__.py | 0 src/focusdetection/focusdetection.py | 49 ++++++++++++++++++++++++++++ 2 files changed, 49 insertions(+) create mode 100644 src/focusdetection/__init__.py create mode 100644 src/focusdetection/focusdetection.py diff --git a/src/focusdetection/__init__.py b/src/focusdetection/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/src/focusdetection/focusdetection.py b/src/focusdetection/focusdetection.py new file mode 100644 index 0000000..af3696d --- /dev/null +++ b/src/focusdetection/focusdetection.py @@ -0,0 +1,49 @@ +import argparse +import os +from os.path import abspath +import cv2 +import pandas +import numpy +import matplotlib.pyplot as plt + +#parser = argparse.ArgumentParser() +#parser.add_argument('images', type=os.path.abspath, metavar='image-location', nargs='+', +# help='path(s) to input image(s)') +#args = vars(parser.parse_args()) +# +#imagePaths = args["images"] + +def laplacian_variance(image): + return cv2.Laplacian(image, cv2.CV_64F).var() + +def fast_fourier(image, size=60, thresh=10): + (h, w) = image.shape + (xCenter, yCenter) = (int(w/ 2), int(h/2)) + fft = numpy.fft.fft2(image) + fftShift = numpy.fft.fftshift(fft) + fftShift[yCenter -size:yCenter + size, xCenter - size:xCenter + size] = 0 + fftShift = numpy.fft.ifftshift(fftShift) + recon = numpy.fft.ifft2(fftShift) + magnitude = 20 * numpy.log(numpy.abs(recon)) + mean = numpy.mean(magnitude) + return (mean, mean <= thresh) + +def laplacian_variance_method(): + column_labels = ['Path', 'Laplacian Variance'] + df = pandas.DataFrame(columns = column_labels) + index = 0 + + for imagePath in imagePaths: + index += 1 + if index % 10 == 0: + print("Processing image " + str(index) + "/" + str(len(imagePaths))) + image = cv2.imread(imagePath) + image_grey = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) + var = laplacian_variance(image_grey) + df.loc[len(df.index)] = [imagePath, var] + + mean_lap_var = df["Laplacian Variance"].mean() + df_not_blurred = df[df['Laplacian Variance']>mean_lap_var] + df_blurred = df[df['Laplacian Variance']<=mean_lap_var] + +#def fast_fourier_transform_method(): From 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https://download.pytorch.org/whl/cpu/torch_stable.html -RUN pip3 install \ - opencv-python \ - sklearn \ - matplotlib \ - pandas \ - tqdm +COPY requirements.txt /requirements.txt -#COPY src /src +RUN pip3 install -r requirements.txt ENTRYPOINT ["bash"] \ No newline at end of file diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..c9b69a2 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,29 @@ +cycler==0.11.0 +fonttools==4.33.2 +imageio==2.17.0 +joblib==1.1.0 +kiwisolver==1.4.2 +matplotlib==3.5.1 +networkx==2.8 +numpy==1.22.3 +opencv-python==4.5.5.64 +packaging==21.3 +pandas==1.4.2 +Pillow==9.0.1 +pyparsing==3.0.8 +python-dateutil==2.8.2 +pytz==2022.1 +PyWavelets==1.3.0 +PyYAML==6.0 +scikit-image==0.19.2 +scikit-learn==1.0.2 +scipy==1.8.0 +six==1.16.0 +sklearn==0.0 +threadpoolctl==3.1.0 +tifffile==2022.4.22 +torch==1.10.2+cpu +torchaudio==0.10.2+cpu +torchvision==0.11.3+cpu +tqdm==4.64.0 +typing_extensions==4.1.1 From 5a7128a4d654be1359f8033150f77432951a0746 Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Sat, 23 Apr 2022 16:25:09 +0100 Subject: [PATCH 15/36] Removed personal log --- personal-log.md | 34 ---------------------------------- 1 file changed, 34 deletions(-) delete mode 100644 personal-log.md diff --git a/personal-log.md b/personal-log.md deleted file mode 100644 index 6ddbc01..0000000 --- a/personal-log.md +++ /dev/null @@ -1,34 +0,0 @@ -# WC 2021-01-31 - -This week is the first week of the project. I researched academic papers, existing code and dataset relating to the topic of determining aesthetics. - -**Papers:** - -[Photo Aesthetics Analysis via DCNN Feature Encoding](https://ieeexplore.ieee.org/document/7886320) - Predicting aesthetic performance using a bespoke CNN solution -> H. -J. Lee, K. -S. Hong, H. Kang and S. Lee, "Photo Aesthetics Analysis via DCNN Feature Encoding," in IEEE Transactions on Multimedia, vol. 20, no. 8, pp. 1921-1932, Aug. 2017, doi: 10.1109/TMM.2017.2687759. - -[AVA: A large-scale database for aesthetic visual analysis](https://ieeexplore.ieee.org/document/6247954) - Making of an aestehtic visual analysis dataset -> N. Murray, L. Marchesotti and F. Perronnin, "AVA: A large-scale database for aesthetic visual analysis," 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012, pp. 2408-2415, doi: 10.1109/CVPR.2012.6247954. - -**Code:** - -[Image Quality Assessment](https://github.com/idealo/image-quality-assessment) - Convolutional Neural Networks to predict the aesthetic and technical quality of images. - -**Datasets:** - -[AADB](https://github.com/aimerykong/deepImageAestheticsAnalysis) - -AVA: https://github.com/imfing/ava_downloader, https://github.com/ylogx/aesthetics/tree/master/data/ava - -## Project idea from research -Based on the research, I decided a machine learning approach would result in higher quality outputs. Although, I was slightly concerned that following a deep-learning would limit interesting discussion in my report. - -The idea was to create a program that can take a video, break it down into frames and use a trained CNN to predict the most aesthetic frames and return them to the user. - -## Weekly 1:1 meeting -During the meeting I mentioned my concerns following a deep learning approach. Although this approach might provide quality results, it doesn't provide much room to discuss or develop interesting solutions. Instead, as Hannah put, it mostly depends on throwing the problem at powerful hardware to get the best output which doesn't make for an interesting project. Hannah suggested I take a hybrid approach where I could use deep-learning for the last step in the pipeline, depending more on conventional engineering techniques to reduce the input data before passing it to the deep-learning stage. - -She mentioned 'dumb' ways in which I could reduce the set of input frames: -- Comparing file sizes and removing the small ones (might infer single colour images / less complex images) -- Fourier frequency analysis -- Brightness and contrast analysis \ No newline at end of file From 43e69ca91952cb6f4d20a802af553aa0dd120fe1 Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Sat, 23 Apr 2022 16:27:05 +0100 Subject: [PATCH 16/36] Fixed LFS on icon --- img/icon.png | Bin 363772 -> 131 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/img/icon.png b/img/icon.png index 0ee82ad86b561b328abfba18f28698d27cb81e12..c8a4ee27723a791df1f7b3023e4c42581cdfcc52 100644 GIT binary patch literal 131 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z_{A2p?40GqXta6bnULRZAo&&Nz%(2j?hzZ-tr5s^C7HvsHpki*6aj11m#y5ZjE=9A zgRlS)E1-s;>}%pO(9iIw*4)t`g@ z&13#0D^M443Z|wxNYAAMhF{F=mdc@xDlXhwlcYmABt$0$p((iEHnAYk*LwwgN7@N5 z?vVtHn3f$O)TgQRUyB~LRn?) zuQIPzujWQJ)-oL-@&g*-QzKw0&3lI80I^TbQF#fAT(B{FUfx(Za?a*`iGJCuGP`7& zRcG{7u&ywQ%mKW+nmFwEf9&Hw-a07*qoM6N<$f{2lV(*OVf From ca5619c3d54f31073fce3bb2bf1523cccfe9bc0d Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Sun, 24 Apr 2022 10:30:14 +0100 Subject: [PATCH 17/36] Added woodpecker config file --- .woodpecker.yml | 7 +++++++ 1 file changed, 7 insertions(+) create mode 100644 .woodpecker.yml diff --git a/.woodpecker.yml b/.woodpecker.yml new file mode 100644 index 0000000..60e538c --- /dev/null +++ b/.woodpecker.yml @@ -0,0 +1,7 @@ +pipeline: + flake8: + image: python:3.8 + commands: + - pip install flake8 + - flake8 /src ++branches: dev \ No newline at end of file From 6ae51c648bbfef6a2927c4b781f7195085b43a20 Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Sun, 24 Apr 2022 10:34:11 +0100 Subject: [PATCH 18/36] Fixed src location --- .woodpecker.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.woodpecker.yml b/.woodpecker.yml index 60e538c..47cbe14 100644 --- a/.woodpecker.yml +++ b/.woodpecker.yml @@ -3,5 +3,5 @@ pipeline: image: python:3.8 commands: - pip install flake8 - - flake8 /src + - flake8 src/ +branches: dev \ No newline at end of file From 6b54d44959808414b44ad32c74cb918471c86b79 Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Mon, 25 Apr 2022 13:29:34 +0100 Subject: [PATCH 19/36] Refactored and modified the project structure --- .woodpecker.yml | 7 +- docker-compose.yaml | 13 + environment.yml | 5 + src/.gitignore | 160 ++++++++++++ src/autophotographer.py | 229 +++++++++++++----- src/{autophotographer => cnn}/__init__.py | 0 .../autophotographer.py | 0 src/{autophotographer => cnn}/config.py | 0 src/{autophotographer => cnn}/dataframe.csv | 0 src/{autophotographer => cnn}/dataset.py | 12 +- .../export}/tensorImages.pt | 0 .../export}/tensorRatings.pt | 0 .../export}/trainDataset.pt | 0 .../export}/valDataset.pt | 0 src/{autophotographer => cnn}/model.py | 0 src/config.yml | 19 +- .../brightness}/__init__.py | 0 src/filters/brightness/brightness.py | 10 + src/filters/contrast/__init__.py | 0 src/filters/filesize/__init__.py | 0 src/filters/focusdetection/__init__.py | 0 .../focusdetection/focusdetection.py | 0 src/predict.py | 4 +- 23 files changed, 383 insertions(+), 76 deletions(-) create mode 100644 docker-compose.yaml create mode 100644 environment.yml create mode 100644 src/.gitignore rename src/{autophotographer => cnn}/__init__.py (100%) rename src/{autophotographer => cnn}/autophotographer.py (100%) rename src/{autophotographer => cnn}/config.py (100%) rename src/{autophotographer => cnn}/dataframe.csv (100%) rename src/{autophotographer => cnn}/dataset.py (92%) rename src/{autophotographer => cnn/export}/tensorImages.pt (100%) rename src/{autophotographer => cnn/export}/tensorRatings.pt (100%) rename src/{autophotographer => cnn/export}/trainDataset.pt (100%) rename src/{autophotographer => cnn/export}/valDataset.pt (100%) rename src/{autophotographer => cnn}/model.py (100%) rename src/{focusdetection => filters/brightness}/__init__.py (100%) create mode 100644 src/filters/brightness/brightness.py create mode 100644 src/filters/contrast/__init__.py create mode 100644 src/filters/filesize/__init__.py create mode 100644 src/filters/focusdetection/__init__.py rename src/{ => filters}/focusdetection/focusdetection.py (100%) diff --git a/.woodpecker.yml b/.woodpecker.yml index 47cbe14..f1cd3ef 100644 --- a/.woodpecker.yml +++ b/.woodpecker.yml @@ -2,6 +2,11 @@ pipeline: flake8: image: python:3.8 commands: - - pip install flake8 + - python3.8 -m pip install flake8 - flake8 src/ + mypy: + image: python:3.8 + commands: + - python3.8 -m pip install mypy + - mypy src/ +branches: dev \ No newline at end of file diff --git a/docker-compose.yaml b/docker-compose.yaml new file mode 100644 index 0000000..705144c --- /dev/null +++ b/docker-compose.yaml @@ -0,0 +1,13 @@ +version: "3.3" + +services: + autophotographer: + build: + context: . + dockerfile: Dockerfile.cpu + image: noble/autophotographer + volumes: + # Source of project + - ./src:/src + # Location of dataset + - $HOME/Documents/Datasets:/datasets \ No newline at end of file diff --git a/environment.yml b/environment.yml new file mode 100644 index 0000000..4e0f912 --- /dev/null +++ b/environment.yml @@ -0,0 +1,5 @@ +name: autophotographer +dependencies: + - numpy + - pandas + - python=3.8 \ No newline at end of file diff --git a/src/.gitignore b/src/.gitignore new file mode 100644 index 0000000..6769e21 --- /dev/null +++ b/src/.gitignore @@ -0,0 +1,160 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +cover/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +.pybuilder/ +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +# For a library or package, you might want to ignore these files since the code is +# intended to run in multiple environments; otherwise, check them in: +# .python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# poetry +# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. +# This is especially recommended for binary packages to ensure reproducibility, and is more +# commonly ignored for libraries. +# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control +#poetry.lock + +# pdm +# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. +#pdm.lock +# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it +# in version control. +# https://pdm.fming.dev/#use-with-ide +.pdm.toml + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# pytype static type analyzer +.pytype/ + +# Cython debug symbols +cython_debug/ + +# PyCharm +# JetBrains specific template is maintained in a separate JetBrains.gitignore that can +# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore +# and can be added to the global gitignore or merged into this file. For a more nuclear +# option (not recommended) you can uncomment the following to ignore the entire idea folder. +#.idea/ \ No newline at end of file diff --git a/src/autophotographer.py b/src/autophotographer.py index 6b94504..30243b0 100644 --- a/src/autophotographer.py +++ b/src/autophotographer.py @@ -1,27 +1,40 @@ +# IMPORTS +# import from +from tqdm import tqdm +from skimage.exposure import is_low_contrast +from os.path import abspath + +# import as +import pandas as pd +import matplotlib.pyplot as plt +import numpy as np + +# imports import cv2 import argparse import os -from os.path import abspath -import pandas -import matplotlib.pyplot as plt -import numpy as np -from skimage.exposure import is_low_contrast import yaml +import math -# Import local packages -from focusdetection.focusdetection import fast_fourier - -#import sys -#import pathlib -#import numpy -#import time +# local imports for filters +import filters.focusdetection.focusdetection as focusdetection +import filters.brightness.brightness as brightness +# GLOBAL VARIABLES # accepted image formats image_formats = (".jpg", ".jpeg", ".png") # accepted video formats video_formats = (".mp4", ".mov", ".avi", ".flv", ".mkv") +# default options +brightness_thresh = 0.35 +focus_thresh = 0.35 +filesize_thresh = 0.35 +contrast_thresh = 0.35 +ignore_video = False + +# FUNCTIONS # load config file def load_config(path=os.path.join(os.path.dirname(__file__), "./config.yml")): abs_path = os.path.abspath(path) @@ -40,33 +53,50 @@ def load_config(path=os.path.join(os.path.dirname(__file__), "./config.yml")): print("[ERRO] Path does not exist") quit() -def filter_to_function(imagefilter, prettyName=False): - if imageFilter == "brightness": - # filter_brightness() - print("[INFO] Filtering based on brightness...") - elif imageFilter == "filesize": - # filter_filesize() - print("[INFO] Filtering based on filesize...") - elif imageFilter == "contrast": - # filter_contrast() - print("[INFO] Filtering based on contrast...") - elif imageFilter == "focus": - # filter_focus() - print("[INFO] Filtering based on focus...") - else: - print("[WARN] Filter not recognised. Ignoring...") +# load the correct filter function from filter name +def filter_to_function(imagefilter: str, paths: list) -> list: + if imageFilter == "brightness": + paths = filter_brightness(paths, brightness_thresh) + print("[INFO] Filtering based on brightness...") + elif imageFilter == "filesize": + paths = filter_filesize(paths, filesize_thresh) + print("[INFO] Filtering based on filesize...") + elif imageFilter == "contrast": + paths = filter_contrast(paths, contrast_thresh) + print("[INFO] Filtering based on contrast...") + elif imageFilter == "focus": + paths = filter_focus(paths, focus_thresh) + print("[INFO] Filtering based on focus...") + else: + print("[WARN] Filter not recognised. Ignoring...") + return paths # filter paths by accepted file extensions -def filter_paths(paths): +def filter_paths(paths: list) -> list: print("[INFO] Filtering paths by filetype...") filtered_paths = [] - for path in paths: - if path.lower().endswith(video_formats + image_formats): - filtered_paths.append(path) + + # if input location is a directory then fetch all files in that directory + if len(paths) == 1 and os.path.isdir(paths[0]): + list_dir = os.listdir(paths[0]) + new_paths = [] + for filename in list_dir: + new_paths.append(os.path.join(args["input"][0], filename)) + paths = new_paths + + # if ignore_video is set to true then filter out video files + if ignore_video: + for path in paths: + if path.lower().endswith(image_formats): + filtered_paths.append(path) + else: + for path in paths: + if path.lower().endswith(video_formats + image_formats): + filtered_paths.append(path) return filtered_paths # load frames from images -def load_video(path): +def load_video(path: str) -> list: print("[INFO] Loading video...") stream = cv2.VideoCapture(path) frames = [] @@ -78,8 +108,9 @@ def load_video(path): return frames # load images -def load_image(path): - print("[INFO] Loading image...") +# note although trivial, a method was created so the way in which a file is loaded can be easily changed +def load_image(path: str): + # print("[INFO] Loading image...") image = cv2.imread(path) return image @@ -122,7 +153,7 @@ def load_files(paths): return (images, videos) # filter images based on filesize -def filter_filesize(paths): +def filter_filesize(paths, thresh=0.35): print("[INFO] Filtering by filesize...") filesizes = [] filtered_paths = [] @@ -131,7 +162,7 @@ def filter_filesize(paths): filesize = os.path.getsize(path) filesizes.append(filesize) filesize_avg = sum(filesizes)/len(filesizes) - filesize_std = pandas.Series(filesizes).std(ddof=0) + filesize_std = pd.Series(filesizes).std(ddof=0) filesize_min = min(filesizes) filesize_max = max(filesizes) filesize_filter = filesize_avg - filesize_std @@ -157,10 +188,11 @@ def plot_filesizes(paths): fig = plt.figure(figsize =(10, 7)) plt.boxplot(data) plt.show() + return plt # resize image and turn to greyscale def process_image(path, width): - print("[INFO] Processing image...") + # print("[INFO] Processing image...") image = cv2.imread(path) height = int(image.shape[0] * (width / image.shape[0])) image = cv2.resize(image, (width, height)) @@ -169,38 +201,63 @@ def process_image(path, width): # filter images based on contrast def filter_contrast(paths, thresh=0.35): - print("[INFO] Filtering by contrast...") + # print("[INFO] Filtering by contrast...") filtered_paths = [] - for path in paths: + for path in tqdm(paths, desc="Filtering contrast"): if path.lower().endswith(video_formats): continue - print(path) + # print(path) image = process_image(path, 500) if is_low_contrast(image, thresh): - print("[INFO] Low contrast") + # print("[INFO] Low contrast") + continue else: - print("[INFO] High contrast") + # print("[INFO] High contrast") filtered_paths.append(path) return filtered_paths # filter images based on brightness -def filter_brightness(paths): - print("[INFO] Filtering by brightness...") +def filter_brightness(paths, thresh=0.35): + filtered_paths = [] + for path in tqdm(paths, desc="Filtering brightness"): + image = load_image(path) + # width = 20 + # height = int(image.shape[0] * (width / image.shape[0])) + # image = cv2.resize(image, (width, height)) + # L, A, B = cv2.split(cv2.cvtColor(image, cv2.COLOR_BGR2LAB)) + # L = L/np.max(L) + luminance = brightness.get_luminance_value(image) + if luminance > thresh: + filtered_paths.append(path) + return filtered_paths + + + # print("[INFO] Filtering by brightness...") + +def filter_brightness_dataframe(paths): + df = pd.DataFrame(paths, columns =['path']) + for path in tqdm(paths, desc="Filtering brightness"): + image = load_image(path) + luminance = brightness.get_luminance_value(image) + row = (df.index[df["path"] == path])[0] + df.at[row, "brightness"] = luminance + return df # filter images based on focus/blurriness -def filter_focus(paths): +def filter_focus(paths, thresh=0.35): print("[INFO] Filtering by focus/blurriness...") filtered_paths = [] # read images in greyscale - for path in paths: + for path in tqdm(paths, desc="Filtering focus"): if path.lower().endswith(video_formats): continue - print(path) + # print(path) image = process_image(path, 500) - (mean, blurry) = fast_fourier(image, size=60, thresh=30) + (mean, blurry) = focusdetection.fast_fourier(image, size=60, thresh=30) blurStats = "Blurry ({:.4f})" if blurry else "Not blurry ({:.4f})" if blurry: - print(("[INFO] {}: " + blurStats).format(path, mean)) + # print(("[INFO] {}: " + blurStats).format(path, mean)) + continue else: filtered_paths.append(path) return filtered_paths @@ -209,31 +266,81 @@ def filter_focus(paths): def rank_images(): print("[INFO] Ranking images using machine learning...") -# parse commande line arguments +def display_images(paths, location): + # create figure + + row = math.ceil(math.sqrt(len(paths))) + width = 100 + size = width * row + fig = plt.figure(figsize=(50, 50)) + + index = 1 + for path in tqdm(paths): + image = cv2.imread(path) + image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) + height = int(image.shape[0] * (width / image.shape[0])) + image = cv2.resize(image, (width, height)) + fig.add_subplot(row, row, index) + plt.imshow(image) + plt.axis('off') + filename = os.path.split(path)[1] + print(filename) + plt.title(filename) + index += 1 + + plt.savefig(location) + +# parse command line arguments parser = argparse.ArgumentParser() parser.add_argument("-i", "--input", type=os.path.abspath, required=True, nargs="+", help="path to video or image folder") parser.add_argument("-c", "--config", type=os.path.abspath, help="path to config file") args = vars(parser.parse_args()) -paths = filter_paths(args["input"]) - # load in config file if args["config"] is not None: autophotoConf = load_config(args["config"]) else: autophotoConf = load_config() -# Order and selection of operations from config file -for imageFilter in autophotoConf["filters"]: - n_of_images_before = len(paths) - filter_to_function(imageFilter) - n_of_images_after = len(paths) +# Load values for options +if autophotoConf["brightness_options"]["threshold"] is not None: + brightness_thresh = autophotoConf["brightness_options"]["threshold"] +if autophotoConf["focus_options"]["threshold"] is not None: + focus_thresh = autophotoConf["focus_options"]["threshold"] +if autophotoConf["contrast_options"]["threshold"] is not None: + contrast_thresh = autophotoConf["contrast_options"]["threshold"] +if autophotoConf["filesize_options"]["threshold"] is not None: + filesize_thresh = autophotoConf["filesize_options"]["threshold"] +if autophotoConf["ignore_video"] is not None: + ignore_video = autophotoConf["ignore_video"] - # calculate set difference after filtering - diff = n_of_images_before - n_of_images_after - print("[INFO] Filtered {}/{} images via {} filtering.".format( - n_of_images_after, n_of_images_before, imageFilter)) +paths = filter_paths(args["input"]) +print("[INFO] Loaded {} objects.".format(len(paths))) +prior_paths = [] +path_diff = [] + +# Order and selection of operations from config file +if autophotoConf["filters"] is not None: + + # iterate over all chosen filters + for imageFilter in autophotoConf["filters"]: + prior_paths = paths + + # run given filter + paths = filter_to_function(imageFilter, paths) + + path_diff = list(set(paths) - set(prior_paths)) + list(set(prior_paths) - set(paths)) + diff = len(prior_paths) - len(paths) + # filename = "/src/fig" + "-" + str(imageFilter) + ".png" + # display_images(path_diff, filename) + + # calculate set difference after filtering + if diff == 0: + print("[INFO] No images were filtered.") + else: + print("[INFO] Filtered {}/{} images via {} filtering.".format( + len(paths), len(prior_paths), imageFilter)) if autophotoConf["CNNrank"]: print("[INFO] Running CNN ranking...") \ No newline at end of file diff --git a/src/autophotographer/__init__.py b/src/cnn/__init__.py similarity index 100% rename from src/autophotographer/__init__.py rename to src/cnn/__init__.py diff --git a/src/autophotographer/autophotographer.py b/src/cnn/autophotographer.py similarity index 100% rename from src/autophotographer/autophotographer.py rename to src/cnn/autophotographer.py diff --git a/src/autophotographer/config.py b/src/cnn/config.py similarity index 100% rename from src/autophotographer/config.py rename to src/cnn/config.py diff --git a/src/autophotographer/dataframe.csv b/src/cnn/dataframe.csv similarity index 100% rename from src/autophotographer/dataframe.csv rename to src/cnn/dataframe.csv diff --git a/src/autophotographer/dataset.py b/src/cnn/dataset.py similarity index 92% rename from src/autophotographer/dataset.py rename to src/cnn/dataset.py index f26e52c..16d94a8 100644 --- a/src/autophotographer/dataset.py +++ b/src/cnn/dataset.py @@ -22,12 +22,14 @@ datasetDir = "/datasets/" script_directory = os.path.dirname(__file__) projectRoot = abspath(os.path.join(script_directory, "../..")) #projectRoot = "/src/" -print(projectRoot) -tensorImagesPath = os.path.join(projectRoot, "src/autophotographer/tensorImages.pt") -tensorRatingsPath = os.path.join(projectRoot, "src/autophotographer/tensorRatings.pt") -tensorArrayPath = os.path.join(projectRoot, "src/autophotographer/tensorArray.pt") +# tensorImagesPath = os.path.join(projectRoot, "src/autophotographer/tensorImages.pt") +# tensorRatingsPath = os.path.join(projectRoot, "src/autophotographer/tensorRatings.pt") +# tensorArrayPath = os.path.join(projectRoot, "src/autophotographer/tensorArray.pt") +tensorImagesPath = os.path.join(script_directory, "tensorImages.pt") +tensorRatingsPath = os.path.join(script_directory, "tensorRatings.pt") +tensorArrayPath = os.path.join(script_directory, "tensorArray.pt") filePathRatings = os.path.join(projectRoot, "data/ratings.txt") -dataframePath = os.path.join(projectRoot, "src/autophotographer/dataframe.csv") +dataframePath = os.path.join(script_directory, "dataframe.csv") if not datasetDir == "": filePathStyle = datasetDir + "AVA/style_image_lists/test.multilab" diff --git a/src/autophotographer/tensorImages.pt b/src/cnn/export/tensorImages.pt similarity index 100% rename from src/autophotographer/tensorImages.pt rename to src/cnn/export/tensorImages.pt diff --git a/src/autophotographer/tensorRatings.pt b/src/cnn/export/tensorRatings.pt similarity index 100% rename from src/autophotographer/tensorRatings.pt rename to src/cnn/export/tensorRatings.pt diff --git a/src/autophotographer/trainDataset.pt b/src/cnn/export/trainDataset.pt similarity index 100% rename from src/autophotographer/trainDataset.pt rename to src/cnn/export/trainDataset.pt diff --git a/src/autophotographer/valDataset.pt b/src/cnn/export/valDataset.pt similarity index 100% rename from src/autophotographer/valDataset.pt rename to src/cnn/export/valDataset.pt diff --git a/src/autophotographer/model.py b/src/cnn/model.py similarity index 100% rename from src/autophotographer/model.py rename to src/cnn/model.py diff --git a/src/config.yml b/src/config.yml index 38992a8..8f8ce19 100644 --- a/src/config.yml +++ b/src/config.yml @@ -1,7 +1,8 @@ --- -# Config file for autophotographer +# Configuration file for the autophographer tool # List of filters to apply in order +# Note: Possible filters include: brightness, filesize, contrast, focus filters: - brightness - filesize @@ -9,21 +10,25 @@ filters: - focus # Whether or not to apply CNN ranking -CNNrank: True +CNNrank: False -# Options for focus filter +# Ignore video files and don't bother processing them into frames +# Note: Useful if directory contains original video and indivual frames from video (prevents processing the same frames more than once) +ignore_video: True + +# Options for brightness filter brightness_options: - threshold: 0.35 + threshold: 0.25 -# Options for focus filter +# Options for filesize filter filesize_options: threshold: 0.35 -# Options for focus filter +# Options for contrast filter contrast_options: threshold: 0.35 # Options for focus filter focus_options: - threshold: 0.35 + threshold: 0.5 ... \ No newline at end of file diff --git a/src/focusdetection/__init__.py b/src/filters/brightness/__init__.py similarity index 100% rename from src/focusdetection/__init__.py rename to src/filters/brightness/__init__.py diff --git a/src/filters/brightness/brightness.py b/src/filters/brightness/brightness.py new file mode 100644 index 0000000..93de728 --- /dev/null +++ b/src/filters/brightness/brightness.py @@ -0,0 +1,10 @@ +import numpy as np +import cv2 + +def get_luminance_value(image): + width = 20 + height = int(image.shape[0] * (width / image.shape[0])) + image = cv2.resize(image, (width, height)) + L, A, B = cv2.split(cv2.cvtColor(image, cv2.COLOR_BGR2LAB)) + L = L/np.max(L) + return np.mean(L) \ No newline at end of file diff --git a/src/filters/contrast/__init__.py b/src/filters/contrast/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/src/filters/filesize/__init__.py b/src/filters/filesize/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/src/filters/focusdetection/__init__.py b/src/filters/focusdetection/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/src/focusdetection/focusdetection.py b/src/filters/focusdetection/focusdetection.py similarity index 100% rename from src/focusdetection/focusdetection.py rename to src/filters/focusdetection/focusdetection.py diff --git a/src/predict.py b/src/predict.py index 4782d1a..890ca28 100644 --- a/src/predict.py +++ b/src/predict.py @@ -1,8 +1,8 @@ import argparse import os from os.path import abspath -from autophotographer import config -from autophotographer import dataset +from cnn import config +from cnn import dataset from torchvision import transforms import matplotlib.pyplot as plt from torch import nn From 0cb40572af1b4005e1930d9444a4f963e23a9e8d Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Thu, 28 Apr 2022 21:39:56 +0100 Subject: [PATCH 20/36] Added cleaned terraform files for Linode --- terraform/linode/.terraform.lock.hcl | 24 ++++++++++++++++ terraform/linode/output.tf | 7 +++++ terraform/linode/provider.tf | 13 +++++++++ terraform/linode/server.tf | 11 +++++++ terraform/linode/vars.tf | 43 ++++++++++++++++++++++++++++ 5 files changed, 98 insertions(+) create mode 100644 terraform/linode/.terraform.lock.hcl create mode 100644 terraform/linode/output.tf create mode 100644 terraform/linode/provider.tf create mode 100644 terraform/linode/server.tf create mode 100644 terraform/linode/vars.tf diff --git a/terraform/linode/.terraform.lock.hcl b/terraform/linode/.terraform.lock.hcl new file mode 100644 index 0000000..c718117 --- /dev/null +++ b/terraform/linode/.terraform.lock.hcl @@ -0,0 +1,24 @@ +# This file is maintained automatically by "terraform init". +# Manual edits may be lost in future updates. + +provider "registry.terraform.io/linode/linode" { + version = "1.26.1" + constraints = "1.26.1" + hashes = [ + "h1:VmElcG8265XBqKK/bqqY6FuknULiTt1qzmJzRhJHxEY=", + "zh:06e676a5934f37fc4639bb06ffe44444035041ab2518044b0f2d993d8d503dca", + "zh:0de1589e3d1bcc5ba50b3638275c87b49c8a68dbd750efc0f288adde649dd6d6", + "zh:54b648e049a53edefa0479fb28af5148d82bce9871a31e02571f93b2fae1bb85", + "zh:7e5c05530100908f1f9634dc997568934d9dde9e67049ad4598ea6e41dd1dde7", + "zh:88ea1d1f80d0dbc03ed74968f197d9b09edaabd57373b9606e9f3df6b10dcf98", + "zh:92fdfd496972cba77ed2c1ba60bd1f7ff5bbc6ea017a67ce702d817ea766bace", + "zh:a9f256b49fd2a34c822bba60d23d29a547d4f326488ef116c30aae5a085b5831", + "zh:cab86347062f374819a45539e61e286215fedc98471693474630924edc0d8296", + "zh:d0361b36eaa1f3aea8be03cae641d6ce4bc4b313abb718857aa3d125aae74349", + "zh:d049e8e7cb51e39119ff5e7a795d5444787149b6ac814421673260135b73820f", + "zh:d424fb536efd07fcfabae402a90392f05e98af2c4681c843ef702e2624d101bb", + "zh:de9661c4ef29f5cc38702b5cca092f087b4ad202775164c7d5ad41f618f8cbd8", + "zh:e3adc13f3d6d243eec42e2589b195910443966cdd0664b03cfb6dfdf15cc30bf", + "zh:ecd7eafeb35b226b03c03b7044b9a8914ffad4e6307a922e193eb7e0d4d52f9b", + ] +} diff --git a/terraform/linode/output.tf b/terraform/linode/output.tf new file mode 100644 index 0000000..a6258d3 --- /dev/null +++ b/terraform/linode/output.tf @@ -0,0 +1,7 @@ +output "ip" { + value = linode_instance.server.ip_address +} + +output "status" { + value = linode_instance.server.status +} diff --git a/terraform/linode/provider.tf b/terraform/linode/provider.tf new file mode 100644 index 0000000..6389f24 --- /dev/null +++ b/terraform/linode/provider.tf @@ -0,0 +1,13 @@ +terraform { + required_providers { + linode = { + source = "linode/linode" + version = "1.26.1" + } + } +} + +# Configure the Linode API token +provider "linode" { + token = var.linode_token +} diff --git a/terraform/linode/server.tf b/terraform/linode/server.tf new file mode 100644 index 0000000..25dc0a6 --- /dev/null +++ b/terraform/linode/server.tf @@ -0,0 +1,11 @@ +resource "linode_instance" "server" { + label = "${local.name}-${var.server_type}-${var.region}" + image = var.image + region = var.region + type = var.server_type + authorized_keys = var.authorized_keys + root_pass = var.root_pass + + group = "University" + tags = ["major_project", "university"] +} diff --git a/terraform/linode/vars.tf b/terraform/linode/vars.tf new file mode 100644 index 0000000..25b88b7 --- /dev/null +++ b/terraform/linode/vars.tf @@ -0,0 +1,43 @@ +# Token variable definition +variable "linode_token" {} + +# Root password variable defintion +variable "root_pass" {} + +# SSH Public key variable definition +variable "authorized_keys" { + type = list(string) +} + +# Name variable definition +variable "name" { + default = "ml" +} + +# Environment variable definition +variable "env" { + default = "dev" +} + +# Defining a variable source OS image for an instance +variable "image" { + default = "linode/debian11" +} + +# Definition of an instance type variable depending on the choice of tariff +variable "server_type" { + # default = "g1-gpu-rtx6000-1" + default = "g6-dedicated-32" +} + +# Definition of the region in which the instance will be created +variable "region" { + default = "eu-central" +} + +# LOCALS + +# Server name +locals { + name = "${var.name}-${var.env}" +} From 7aaad9e8342ca32a317c567c8b1f65c36d793d03 Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Thu, 28 Apr 2022 21:41:13 +0100 Subject: [PATCH 21/36] Added terraform .gitignore file --- terraform/.gitignore | 7 +++++++ 1 file changed, 7 insertions(+) create mode 100644 terraform/.gitignore diff --git a/terraform/.gitignore b/terraform/.gitignore new file mode 100644 index 0000000..ac1c9aa --- /dev/null +++ b/terraform/.gitignore @@ -0,0 +1,7 @@ +**/.terraform/* +*.tfstate +*.tfstate.* +crash.log +crash.*.log +*.tfvars +*.tfvars.json \ No newline at end of file From 971cd62bb4bf65d6ecb938bb63e65aa92656bcb3 Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Thu, 28 Apr 2022 21:45:39 +0100 Subject: [PATCH 22/36] Added project .gitignore --- .gitignore | 160 +++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 160 insertions(+) create mode 100644 .gitignore diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..6769e21 --- /dev/null +++ b/.gitignore @@ -0,0 +1,160 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +cover/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +.pybuilder/ +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +# For a library or package, you might want to ignore these files since the code is +# intended to run in multiple environments; otherwise, check them in: +# .python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# poetry +# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. +# This is especially recommended for binary packages to ensure reproducibility, and is more +# commonly ignored for libraries. +# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control +#poetry.lock + +# pdm +# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. +#pdm.lock +# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it +# in version control. +# https://pdm.fming.dev/#use-with-ide +.pdm.toml + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# pytype static type analyzer +.pytype/ + +# Cython debug symbols +cython_debug/ + +# PyCharm +# JetBrains specific template is maintained in a separate JetBrains.gitignore that can +# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore +# and can be added to the global gitignore or merged into this file. For a more nuclear +# option (not recommended) you can uncomment the following to ignore the entire idea folder. +#.idea/ \ No newline at end of file From 484e481d88036574090ced07fb19ab3b8cf29fea Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Thu, 28 Apr 2022 22:11:56 +0100 Subject: [PATCH 23/36] Restructured project as a package --- src/{cnn => autophotographer}/__init__.py | 0 .../autophotographer_main.py} | 147 ++++++++++-------- .../cnn}/__init__.py | 0 .../cnn/autophotographer.py | 6 +- src/{ => autophotographer}/cnn/config.py | 3 +- src/{ => autophotographer}/cnn/dataframe.csv | 0 src/{ => autophotographer}/cnn/dataset.py | 29 ++-- src/autophotographer/cnn/export/.gitignore | 2 + .../cnn/export/tensorImages.pt | 0 .../cnn/export/tensorRatings.pt | 0 .../cnn/export/trainDataset.pt | 0 .../cnn/export/valDataset.pt | 0 src/{ => autophotographer}/cnn/model.py | 19 ++- src/{ => autophotographer}/config.yml | 0 .../filters/brightness}/__init__.py | 0 .../filters/brightness/brightness.py | 20 +++ .../filters/contrast}/__init__.py | 0 .../filters/contrast/contrast.py} | 0 .../filters/filesize/__init__.py | 0 .../filters/focusdetection/__init__.py | 0 .../filters/focusdetection/focusdetection.py | 9 +- src/{ => autophotographer}/predict.py | 18 +-- src/filters/brightness/brightness.py | 10 -- .../predict-plot-2022-3-23_13-20-21.png | 3 + .../predict-plot-2022-3-23_13-24-49.png | 3 + .../predict-plot-2022-3-23_13-27-30.png | 3 + .../predict-plot-2022-3-23_13-30-59.png | 3 + 27 files changed, 160 insertions(+), 115 deletions(-) rename src/{cnn => autophotographer}/__init__.py (100%) rename src/{autophotographer.py => autophotographer/autophotographer_main.py} (69%) rename src/{filters/brightness => autophotographer/cnn}/__init__.py (100%) rename src/{ => autophotographer}/cnn/autophotographer.py (99%) rename src/{ => autophotographer}/cnn/config.py (99%) rename src/{ => autophotographer}/cnn/dataframe.csv (100%) rename src/{ => autophotographer}/cnn/dataset.py (99%) create mode 100644 src/autophotographer/cnn/export/.gitignore rename src/{ => autophotographer}/cnn/export/tensorImages.pt (100%) rename src/{ => autophotographer}/cnn/export/tensorRatings.pt (100%) rename src/{ => autophotographer}/cnn/export/trainDataset.pt (100%) rename src/{ => autophotographer}/cnn/export/valDataset.pt (100%) rename src/{ => autophotographer}/cnn/model.py (99%) rename src/{ => autophotographer}/config.yml (100%) rename src/{filters/contrast => autophotographer/filters/brightness}/__init__.py (100%) create mode 100644 src/autophotographer/filters/brightness/brightness.py rename src/{filters/filesize => autophotographer/filters/contrast}/__init__.py (100%) rename src/{filters/focusdetection/__init__.py => autophotographer/filters/contrast/contrast.py} (100%) create mode 100644 src/autophotographer/filters/filesize/__init__.py create mode 100644 src/autophotographer/filters/focusdetection/__init__.py rename src/{ => autophotographer}/filters/focusdetection/focusdetection.py (94%) rename src/{ => autophotographer}/predict.py (98%) delete mode 100644 src/filters/brightness/brightness.py create mode 100644 src/output/predict-plot-2022-3-23_13-20-21.png create mode 100644 src/output/predict-plot-2022-3-23_13-24-49.png create mode 100644 src/output/predict-plot-2022-3-23_13-27-30.png create mode 100644 src/output/predict-plot-2022-3-23_13-30-59.png diff --git a/src/cnn/__init__.py b/src/autophotographer/__init__.py similarity index 100% rename from src/cnn/__init__.py rename to src/autophotographer/__init__.py diff --git a/src/autophotographer.py b/src/autophotographer/autophotographer_main.py similarity index 69% rename from src/autophotographer.py rename to src/autophotographer/autophotographer_main.py index 30243b0..3745809 100644 --- a/src/autophotographer.py +++ b/src/autophotographer/autophotographer_main.py @@ -1,24 +1,16 @@ -# IMPORTS -# import from -from tqdm import tqdm -from skimage.exposure import is_low_contrast -from os.path import abspath - -# import as -import pandas as pd -import matplotlib.pyplot as plt -import numpy as np - -# imports -import cv2 +import math import argparse import os +from os.path import abspath +import cv2 +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd import yaml -import math - -# local imports for filters -import filters.focusdetection.focusdetection as focusdetection -import filters.brightness.brightness as brightness +from skimage.exposure import is_low_contrast +from tqdm import tqdm +import autophotographer.filters.brightness.brightness as brightness +import autophotographer.filters.focusdetection.focusdetection as focusdetection # GLOBAL VARIABLES # accepted image formats @@ -37,6 +29,13 @@ ignore_video = False # FUNCTIONS # load config file def load_config(path=os.path.join(os.path.dirname(__file__), "./config.yml")): + """ + The load_config function loads a YAML configuration file from the specified path. + + :param path=os.path.join(os.path.dirname(__file__): Used to Specify the path of the config. + :param "./config.yml"): Used to Specify the path to the config file. + :return: A dictionary of the config file. + """ abs_path = os.path.abspath(path) # check if file exists @@ -50,11 +49,28 @@ def load_config(path=os.path.join(os.path.dirname(__file__), "./config.yml")): print("[ERRO] Please specify a file with extension '.yml' or '.yaml'.") quit() else: - print("[ERRO] Path does not exist") - quit() + raise FileNotFoundError("[ERRO] Path does not exist") # load the correct filter function from filter name def filter_to_function(imagefilter: str, paths: list) -> list: + """ + The filter_to_function function filters a list of image paths based on the filter type. + + Args: + imagefilter (str): The type of filter to apply. Can be "brightness", "contrast", or "focus". + + paths (list): A list of filepaths to images that will be filtered. + + brightness_thresh (int, optional): The threshold for filtering out images with low brightness levels. Defaults to 100 if not specified by user in config file or command line arguments. + + contrast_thresh (float, optional): The threshold for filtering out images with low contrast levels. Defaults to 1 if not specified by user in config file or command line arguments.. + + focus_thresh (float, optional): The threshold for filtering out blurry images based on the variance in blurriness across all pixels within an image's bounding box as determined using OpenCV's Laplacian method and Gaussian Blur method respectively . Defaults to 0 if not specified by user in config file or command line arguments.. + + :param imagefilter:str: Used to Determine which filter to apply. + :param paths:list: Used to Store the paths of all images that have been filtered. + :return: The filtered list of paths. + """ if imageFilter == "brightness": paths = filter_brightness(paths, brightness_thresh) print("[INFO] Filtering based on brightness...") @@ -291,56 +307,57 @@ def display_images(paths, location): plt.savefig(location) # parse command line arguments -parser = argparse.ArgumentParser() -parser.add_argument("-i", "--input", type=os.path.abspath, required=True, nargs="+", - help="path to video or image folder") -parser.add_argument("-c", "--config", type=os.path.abspath, help="path to config file") -args = vars(parser.parse_args()) +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("-i", "--input", type=os.path.abspath, required=True, nargs="+", + help="path to video or image folder") + parser.add_argument("-c", "--config", type=os.path.abspath, help="path to config file") + args = vars(parser.parse_args()) -# load in config file -if args["config"] is not None: - autophotoConf = load_config(args["config"]) -else: - autophotoConf = load_config() + # load in config file + if args["config"] is not None: + autophotoConf = load_config(args["config"]) + else: + autophotoConf = load_config() -# Load values for options -if autophotoConf["brightness_options"]["threshold"] is not None: - brightness_thresh = autophotoConf["brightness_options"]["threshold"] -if autophotoConf["focus_options"]["threshold"] is not None: - focus_thresh = autophotoConf["focus_options"]["threshold"] -if autophotoConf["contrast_options"]["threshold"] is not None: - contrast_thresh = autophotoConf["contrast_options"]["threshold"] -if autophotoConf["filesize_options"]["threshold"] is not None: - filesize_thresh = autophotoConf["filesize_options"]["threshold"] -if autophotoConf["ignore_video"] is not None: - ignore_video = autophotoConf["ignore_video"] + # Load values for options + if autophotoConf["brightness_options"]["threshold"] is not None: + brightness_thresh = autophotoConf["brightness_options"]["threshold"] + if autophotoConf["focus_options"]["threshold"] is not None: + focus_thresh = autophotoConf["focus_options"]["threshold"] + if autophotoConf["contrast_options"]["threshold"] is not None: + contrast_thresh = autophotoConf["contrast_options"]["threshold"] + if autophotoConf["filesize_options"]["threshold"] is not None: + filesize_thresh = autophotoConf["filesize_options"]["threshold"] + if autophotoConf["ignore_video"] is not None: + ignore_video = autophotoConf["ignore_video"] -paths = filter_paths(args["input"]) -print("[INFO] Loaded {} objects.".format(len(paths))) -prior_paths = [] -path_diff = [] + paths = filter_paths(args["input"]) + print("[INFO] Loaded {} objects.".format(len(paths))) + prior_paths = [] + path_diff = [] -# Order and selection of operations from config file -if autophotoConf["filters"] is not None: + # Order and selection of operations from config file + if autophotoConf["filters"] is not None: - # iterate over all chosen filters - for imageFilter in autophotoConf["filters"]: - prior_paths = paths - - # run given filter - paths = filter_to_function(imageFilter, paths) + # iterate over all chosen filters + for imageFilter in autophotoConf["filters"]: + prior_paths = paths - path_diff = list(set(paths) - set(prior_paths)) + list(set(prior_paths) - set(paths)) - diff = len(prior_paths) - len(paths) - # filename = "/src/fig" + "-" + str(imageFilter) + ".png" - # display_images(path_diff, filename) + # run given filter + paths = filter_to_function(imageFilter, paths) - # calculate set difference after filtering - if diff == 0: - print("[INFO] No images were filtered.") - else: - print("[INFO] Filtered {}/{} images via {} filtering.".format( - len(paths), len(prior_paths), imageFilter)) + path_diff = list(set(paths) - set(prior_paths)) + list(set(prior_paths) - set(paths)) + diff = len(prior_paths) - len(paths) + # filename = "/src/fig" + "-" + str(imageFilter) + ".png" + # display_images(path_diff, filename) -if autophotoConf["CNNrank"]: - print("[INFO] Running CNN ranking...") \ No newline at end of file + # calculate set difference after filtering + if diff == 0: + print("[INFO] No images were filtered.") + else: + print("[INFO] Filtered {}/{} images via {} filtering.".format( + len(paths), len(prior_paths), imageFilter)) + + if autophotoConf["CNNrank"]: + print("[INFO] Running CNN ranking...") \ No newline at end of file diff --git a/src/filters/brightness/__init__.py b/src/autophotographer/cnn/__init__.py similarity index 100% rename from src/filters/brightness/__init__.py rename to src/autophotographer/cnn/__init__.py diff --git a/src/cnn/autophotographer.py b/src/autophotographer/cnn/autophotographer.py similarity index 99% rename from src/cnn/autophotographer.py rename to src/autophotographer/cnn/autophotographer.py index 9bd87f8..0e2b4f4 100644 --- a/src/cnn/autophotographer.py +++ b/src/autophotographer/cnn/autophotographer.py @@ -1,8 +1,10 @@ -import cv2 -import sys import argparse import os import pathlib +import sys + +import cv2 + # Process arguments def parse_arguments(argv=None): diff --git a/src/cnn/config.py b/src/autophotographer/cnn/config.py similarity index 99% rename from src/cnn/config.py rename to src/autophotographer/cnn/config.py index bfc5c68..60975f3 100644 --- a/src/cnn/config.py +++ b/src/autophotographer/cnn/config.py @@ -1,6 +1,7 @@ -import torch import os +import torch + # https://pytorch.org/hub/pytorch_vision_resnet/ MEAN = [0.485, 0.456, 0.406] STD = [0.229, 0.224, 0.225] diff --git a/src/cnn/dataframe.csv b/src/autophotographer/cnn/dataframe.csv similarity index 100% rename from src/cnn/dataframe.csv rename to src/autophotographer/cnn/dataframe.csv diff --git a/src/cnn/dataset.py b/src/autophotographer/cnn/dataset.py similarity index 99% rename from src/cnn/dataset.py rename to src/autophotographer/cnn/dataset.py index 16d94a8..b8a7537 100644 --- a/src/cnn/dataset.py +++ b/src/autophotographer/cnn/dataset.py @@ -1,20 +1,23 @@ -import pandas as pd -import matplotlib.pyplot as plt -import matplotlib.image as mpimg +import os import random import time -from sklearn.preprocessing import MinMaxScaler -import numpy as np -from sklearn.model_selection import train_test_split -import cv2 -from pathlib import Path -from . import config -from torchvision import transforms -import torch -from torch.utils.data import DataLoader -import os from os.path import abspath +from pathlib import Path + +import cv2 +import matplotlib.image as mpimg +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd +import torch from PIL import Image, ImageFile +from sklearn.model_selection import train_test_split +from sklearn.preprocessing import MinMaxScaler +from torch.utils.data import DataLoader +from torchvision import transforms + +from . import config + ImageFile.LOAD_TRUNCATED_IMAGES = True datasetDir = "/datasets/" diff --git a/src/autophotographer/cnn/export/.gitignore b/src/autophotographer/cnn/export/.gitignore new file mode 100644 index 0000000..47c473a --- /dev/null +++ b/src/autophotographer/cnn/export/.gitignore @@ -0,0 +1,2 @@ +tensorArray.pt +testTensorArrayFile.pt diff --git a/src/cnn/export/tensorImages.pt b/src/autophotographer/cnn/export/tensorImages.pt similarity index 100% rename from src/cnn/export/tensorImages.pt rename to src/autophotographer/cnn/export/tensorImages.pt diff --git a/src/cnn/export/tensorRatings.pt b/src/autophotographer/cnn/export/tensorRatings.pt similarity index 100% rename from src/cnn/export/tensorRatings.pt rename to src/autophotographer/cnn/export/tensorRatings.pt diff --git a/src/cnn/export/trainDataset.pt b/src/autophotographer/cnn/export/trainDataset.pt similarity index 100% rename from src/cnn/export/trainDataset.pt rename to src/autophotographer/cnn/export/trainDataset.pt diff --git a/src/cnn/export/valDataset.pt b/src/autophotographer/cnn/export/valDataset.pt similarity index 100% rename from src/cnn/export/valDataset.pt rename to src/autophotographer/cnn/export/valDataset.pt diff --git a/src/cnn/model.py b/src/autophotographer/cnn/model.py similarity index 99% rename from src/cnn/model.py rename to src/autophotographer/cnn/model.py index 071c229..3440ad4 100644 --- a/src/cnn/model.py +++ b/src/autophotographer/cnn/model.py @@ -1,18 +1,17 @@ -import torch -import torch.nn as nn -import torch.optim as optim -from torchvision.models import resnet50 -from torchvision import transforms -from torch.utils.data import DataLoader - -from tqdm import tqdm -import time import os +import time from os.path import abspath -import matplotlib.pyplot as plt import config import dataset +import matplotlib.pyplot as plt +import torch +import torch.nn as nn +import torch.optim as optim +from torch.utils.data import DataLoader +from torchvision import transforms +from torchvision.models import resnet50 +from tqdm import tqdm # projectRoot = "/src/" script_directory = os.path.dirname(__file__) diff --git a/src/config.yml b/src/autophotographer/config.yml similarity index 100% rename from src/config.yml rename to src/autophotographer/config.yml diff --git a/src/filters/contrast/__init__.py b/src/autophotographer/filters/brightness/__init__.py similarity index 100% rename from src/filters/contrast/__init__.py rename to src/autophotographer/filters/brightness/__init__.py diff --git a/src/autophotographer/filters/brightness/brightness.py b/src/autophotographer/filters/brightness/brightness.py new file mode 100644 index 0000000..2505f0a --- /dev/null +++ b/src/autophotographer/filters/brightness/brightness.py @@ -0,0 +1,20 @@ +import cv2 +import numpy as np + + +def get_luminance_value(image): + """ + The get_luminance_value function takes an image as input and returns the luminance value of that image. + The function first resizes the image to a width of 20 pixels, then converts it to LAB color space, + and finally normalizes the L channel by dividing it by its maximum value. The function returns this normalized + L channel. + + :param image: Used to Get the image that is being processed. + :return: The value of the luminance channel. + """ + width = 20 + height = int(image.shape[0] * (width / image.shape[0])) + image = cv2.resize(image, (width, height)) + L, A, B = cv2.split(cv2.cvtColor(image, cv2.COLOR_BGR2LAB)) + L = L/np.max(L) + return np.mean(L) \ No newline at end of file diff --git a/src/filters/filesize/__init__.py b/src/autophotographer/filters/contrast/__init__.py similarity index 100% rename from src/filters/filesize/__init__.py rename to src/autophotographer/filters/contrast/__init__.py diff --git a/src/filters/focusdetection/__init__.py b/src/autophotographer/filters/contrast/contrast.py similarity index 100% rename from src/filters/focusdetection/__init__.py rename to src/autophotographer/filters/contrast/contrast.py diff --git a/src/autophotographer/filters/filesize/__init__.py b/src/autophotographer/filters/filesize/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/src/autophotographer/filters/focusdetection/__init__.py b/src/autophotographer/filters/focusdetection/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/src/filters/focusdetection/focusdetection.py b/src/autophotographer/filters/focusdetection/focusdetection.py similarity index 94% rename from src/filters/focusdetection/focusdetection.py rename to src/autophotographer/filters/focusdetection/focusdetection.py index af3696d..a073332 100644 --- a/src/filters/focusdetection/focusdetection.py +++ b/src/autophotographer/filters/focusdetection/focusdetection.py @@ -1,10 +1,11 @@ import argparse import os from os.path import abspath + import cv2 -import pandas -import numpy import matplotlib.pyplot as plt +import numpy +import pandas #parser = argparse.ArgumentParser() #parser.add_argument('images', type=os.path.abspath, metavar='image-location', nargs='+', @@ -44,6 +45,4 @@ def laplacian_variance_method(): mean_lap_var = df["Laplacian Variance"].mean() df_not_blurred = df[df['Laplacian Variance']>mean_lap_var] - df_blurred = df[df['Laplacian Variance']<=mean_lap_var] - -#def fast_fourier_transform_method(): + df_blurred = df[df['Laplacian Variance']<=mean_lap_var] \ No newline at end of file diff --git a/src/predict.py b/src/autophotographer/predict.py similarity index 98% rename from src/predict.py rename to src/autophotographer/predict.py index 890ca28..178629f 100644 --- a/src/predict.py +++ b/src/autophotographer/predict.py @@ -1,14 +1,14 @@ import argparse -import os -from os.path import abspath -from cnn import config -from cnn import dataset -from torchvision import transforms -import matplotlib.pyplot as plt -from torch import nn -import torch -import argparse import datetime +import os +from os.path import abspath + +import matplotlib.pyplot as plt +import torch +from torch import nn +from torchvision import transforms + +from cnn import config, dataset # set project root for fetching files using relative file paths script_directory = os.path.dirname(__file__) diff --git a/src/filters/brightness/brightness.py b/src/filters/brightness/brightness.py deleted file mode 100644 index 93de728..0000000 --- a/src/filters/brightness/brightness.py +++ /dev/null @@ -1,10 +0,0 @@ -import numpy as np -import cv2 - -def get_luminance_value(image): - width = 20 - height = int(image.shape[0] * (width / image.shape[0])) - image = cv2.resize(image, (width, height)) - L, A, B = cv2.split(cv2.cvtColor(image, cv2.COLOR_BGR2LAB)) - L = L/np.max(L) - return np.mean(L) \ No newline at end of file diff --git a/src/output/predict-plot-2022-3-23_13-20-21.png b/src/output/predict-plot-2022-3-23_13-20-21.png new file mode 100644 index 0000000..b53a359 --- /dev/null +++ b/src/output/predict-plot-2022-3-23_13-20-21.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4ec851089f8f84eadc2d8ba4a558b8e6016c44884e827113b0de05c5aedff3cc +size 58724 diff --git a/src/output/predict-plot-2022-3-23_13-24-49.png b/src/output/predict-plot-2022-3-23_13-24-49.png new file mode 100644 index 0000000..1e6777f --- /dev/null +++ b/src/output/predict-plot-2022-3-23_13-24-49.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:49795c27aba3a9538129d716f73c6582559ca78a4e0947203977452d7c2ee7bb +size 77512 diff --git a/src/output/predict-plot-2022-3-23_13-27-30.png b/src/output/predict-plot-2022-3-23_13-27-30.png new file mode 100644 index 0000000..ffda1b4 --- /dev/null +++ b/src/output/predict-plot-2022-3-23_13-27-30.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d5c556f34b0aea99a94cce1bc331d9a6114ff83a3ce4507432cecae3c2cc26ba +size 339468 diff --git a/src/output/predict-plot-2022-3-23_13-30-59.png b/src/output/predict-plot-2022-3-23_13-30-59.png new file mode 100644 index 0000000..6acb73f --- /dev/null +++ b/src/output/predict-plot-2022-3-23_13-30-59.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c8c2478616842c1ed150a7932e8015a351788a28518462380942417ab6ee4204 +size 172019 From 74875553d52e92ec2629b0d67256e4f6392c6840 Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Thu, 28 Apr 2022 22:15:33 +0100 Subject: [PATCH 24/36] Dockerfile installs from requirements.txt --- Dockerfile.cpu | 2 +- docker-compose.yaml | 2 +- requirements.txt | 27 ++------------------------- 3 files changed, 4 insertions(+), 27 deletions(-) diff --git a/Dockerfile.cpu b/Dockerfile.cpu index f59efe9..f59600c 100644 --- a/Dockerfile.cpu +++ b/Dockerfile.cpu @@ -2,7 +2,7 @@ FROM python:3.8 RUN apt update -y -RUN apt install libgl1 -y +RUN apt install libgl1 -y # or install opencv opencv-python-headless instead RUN pip3 install \ torch==1.10.2+cpu \ diff --git a/docker-compose.yaml b/docker-compose.yaml index 705144c..657ce6c 100644 --- a/docker-compose.yaml +++ b/docker-compose.yaml @@ -8,6 +8,6 @@ services: image: noble/autophotographer volumes: # Source of project - - ./src:/src + - .:/mmp-osp1 # Location of dataset - $HOME/Documents/Datasets:/datasets \ No newline at end of file diff --git a/requirements.txt b/requirements.txt index c9b69a2..fa7f531 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,29 +1,6 @@ -cycler==0.11.0 -fonttools==4.33.2 -imageio==2.17.0 -joblib==1.1.0 -kiwisolver==1.4.2 -matplotlib==3.5.1 -networkx==2.8 -numpy==1.22.3 opencv-python==4.5.5.64 -packaging==21.3 +matplotlib==3.5.1 pandas==1.4.2 -Pillow==9.0.1 -pyparsing==3.0.8 -python-dateutil==2.8.2 -pytz==2022.1 -PyWavelets==1.3.0 PyYAML==6.0 scikit-image==0.19.2 -scikit-learn==1.0.2 -scipy==1.8.0 -six==1.16.0 -sklearn==0.0 -threadpoolctl==3.1.0 -tifffile==2022.4.22 -torch==1.10.2+cpu -torchaudio==0.10.2+cpu -torchvision==0.11.3+cpu -tqdm==4.64.0 -typing_extensions==4.1.1 +tqdm==4.64.0 \ No newline at end of file From f35bd807671cec6f7d7307a55a076582c1177c4c Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Thu, 28 Apr 2022 22:17:20 +0100 Subject: [PATCH 25/36] Packaged autophotographer and added tests and test pipelines --- .woodpecker.yml => .woodpecker/.lint.yml | 7 ++++++- .woodpecker/.test.yml | 8 ++++++++ pyproject.toml | 3 +++ requirements_dev.txt | 4 ++++ setup.cfg | 26 ++++++++++++++++++++++++ setup.py | 3 +++ test/pytest.ini | 2 ++ test/unit/test_autophotographer.py | 6 ++++++ test/unit/test_dataset.py | 0 9 files changed, 58 insertions(+), 1 deletion(-) rename .woodpecker.yml => .woodpecker/.lint.yml (63%) create mode 100644 .woodpecker/.test.yml create mode 100644 pyproject.toml create mode 100644 requirements_dev.txt create mode 100644 setup.cfg create mode 100644 setup.py create mode 100644 test/pytest.ini create mode 100644 test/unit/test_autophotographer.py create mode 100644 test/unit/test_dataset.py diff --git a/.woodpecker.yml b/.woodpecker/.lint.yml similarity index 63% rename from .woodpecker.yml rename to .woodpecker/.lint.yml index f1cd3ef..b6b057b 100644 --- a/.woodpecker.yml +++ b/.woodpecker/.lint.yml @@ -9,4 +9,9 @@ pipeline: commands: - python3.8 -m pip install mypy - mypy src/ -+branches: dev \ No newline at end of file + isort: + image: python:3.8 + commands: + - python3.8 -m pip install isort + - isort --diff src/ +branches: dev \ No newline at end of file diff --git a/.woodpecker/.test.yml b/.woodpecker/.test.yml new file mode 100644 index 0000000..c39f634 --- /dev/null +++ b/.woodpecker/.test.yml @@ -0,0 +1,8 @@ +pipeline: + unit-tests: + image: python:3.8 + commands: + - python3.8 -m pip install -r ./requirements_dev.txt -r ./requirements.txt + - python3.8 -m pip install -e . + - pytest test/ -v +branches: dev \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..b28f77b --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,3 @@ +[build-system] +requires = ["setuptools >= 43.0.0", "wheel"] +build-backend = "setuptools.build_meta" \ No newline at end of file diff --git a/requirements_dev.txt b/requirements_dev.txt new file mode 100644 index 0000000..3f4cde1 --- /dev/null +++ b/requirements_dev.txt @@ -0,0 +1,4 @@ +flake8==4.0.1 +pytest==7.1.2 +pytest-cov==3.0.0 +mypy==0.950 \ No newline at end of file diff --git a/setup.cfg b/setup.cfg new file mode 100644 index 0000000..85d2e19 --- /dev/null +++ b/setup.cfg @@ -0,0 +1,26 @@ +[metadata] +name = autophotographer +description = Select aesthetic frames from a video file +long_description = README.md +author = Oscar Pocock +author_email = osp1@aber.ac.uk +license = GPLv3+ +license_files = LICENSE.txt + +[options] +packages = + autophotographer +python_requires = >=3.8 +package_dir = + =src +zip_safe = no + +[options.extras_require] +testing = + flake8>=4.0 + pytest>=7.1 + pytest-cov>=3.0 + mypy>=0.950 + +[flake8] +max-line-length = 160 \ No newline at end of file diff --git a/setup.py b/setup.py new file mode 100644 index 0000000..483e332 --- /dev/null +++ b/setup.py @@ -0,0 +1,3 @@ +from setuptools import setup +if __name__ == "__main__": + setup() \ No newline at end of file diff --git a/test/pytest.ini b/test/pytest.ini new file mode 100644 index 0000000..90815a2 --- /dev/null +++ b/test/pytest.ini @@ -0,0 +1,2 @@ +[pytest] +addopts = "--cov=autophotographer" \ No newline at end of file diff --git a/test/unit/test_autophotographer.py b/test/unit/test_autophotographer.py new file mode 100644 index 0000000..82a7ead --- /dev/null +++ b/test/unit/test_autophotographer.py @@ -0,0 +1,6 @@ +from autophotographer import autophotographer_main +import pytest + +def test_load_config_nonexistent_file(): + with pytest.raises(FileNotFoundError): + autophotographer_main.load_config("blahblahblah") diff --git a/test/unit/test_dataset.py b/test/unit/test_dataset.py new file mode 100644 index 0000000..e69de29 From 879f40d76f4cfd946af4891a19685d9e5350d5ae Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Thu, 28 Apr 2022 22:19:59 +0100 Subject: [PATCH 26/36] Added step to install libgl for testing with opencv --- .woodpecker/.test.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/.woodpecker/.test.yml b/.woodpecker/.test.yml index c39f634..e528c4c 100644 --- a/.woodpecker/.test.yml +++ b/.woodpecker/.test.yml @@ -2,6 +2,7 @@ pipeline: unit-tests: image: python:3.8 commands: + - apt update -y && apt install libgl1 - python3.8 -m pip install -r ./requirements_dev.txt -r ./requirements.txt - python3.8 -m pip install -e . - pytest test/ -v From 8449d16441a4f15e98acc4b64b783ce4b4ea44bb Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Thu, 28 Apr 2022 22:21:24 +0100 Subject: [PATCH 27/36] Added autoconfirm to installation of libgl --- .woodpecker/.test.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.woodpecker/.test.yml b/.woodpecker/.test.yml index e528c4c..338a00c 100644 --- a/.woodpecker/.test.yml +++ b/.woodpecker/.test.yml @@ -2,7 +2,7 @@ pipeline: unit-tests: image: python:3.8 commands: - - apt update -y && apt install libgl1 + - apt update -y && apt install libgl1 -y - python3.8 -m pip install -r 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create mode 100644 Dockerfile.nvidia-gpu diff --git a/Dockerfile.amd-gpu b/Dockerfile.amd-gpu new file mode 100644 index 0000000..1c94b67 --- /dev/null +++ b/Dockerfile.amd-gpu @@ -0,0 +1,15 @@ +FROM python:3.8 + +RUN apt update -y + +RUN apt install libgl1 -y # or install opencv opencv-python-headless instead + +RUN pip3 install torch \ + torchvision==0.11.3 \ + -f https://download.pytorch.org/whl/rocm4.2/torch_stable.html + +COPY requirements.txt /requirements.txt + +RUN pip3 install -r requirements.txt + +ENTRYPOINT ["bash"] \ No newline at end of file diff --git a/Dockerfile.nvidia-gpu b/Dockerfile.nvidia-gpu new file mode 100644 index 0000000..45938af --- /dev/null +++ b/Dockerfile.nvidia-gpu @@ -0,0 +1,17 @@ +FROM python:3.8 + +RUN apt update -y + +RUN apt install libgl1 -y # or install opencv opencv-python-headless instead + +RUN pip3 install \ + torch==1.11.0+cu113 \ + torchvision==0.12.0+cu113 \ + torchaudio==0.11.0+cu113 \ + -f https://download.pytorch.org/whl/cu113/torch_stable.html + +COPY requirements.txt /requirements.txt + +RUN pip3 install -r requirements.txt + +ENTRYPOINT ["bash"] \ No newline at end of file From 05edb5598a7ca8ddb871de774f11a260d191f81a Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Thu, 5 May 2022 16:48:37 +0100 Subject: [PATCH 30/36] Added comments to docker-compose.yaml --- docker-compose.yaml | 1 + 1 file changed, 1 insertion(+) diff --git a/docker-compose.yaml b/docker-compose.yaml index 657ce6c..808b643 100644 --- a/docker-compose.yaml +++ b/docker-compose.yaml @@ -10,4 +10,5 @@ services: # Source of project - .:/mmp-osp1 # Location of dataset + # - /location/of/AVA:/datasets/AVA - $HOME/Documents/Datasets:/datasets \ No newline at end of file From 523f518aa83019fc607ba753184308d1ced73cf4 Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Sat, 14 May 2022 17:44:05 +0100 Subject: [PATCH 31/36] Final submission commit A few changes: - Added report - Added mid project demo content - Added README.txt - Added Experiments - Added ratings.txt file - Added unit tests - Simplified the prediction code - Added single prediction --- README.md | 12 - README.txt | 78 + data/ratings.txt | 255530 +++++++++++++++ docs/mid-project-demo/HL-Diagram.drawio | 1 + docs/mid-project-demo/HL-Diagram.svg | 3 + docs/{ => mid-project-demo}/mid-project.odp | Bin docs/report/.gitignore | 303 + docs/report/Appendices/appendixA.tex | 34 + docs/report/Appendices/appendixB.tex | 90 + .../background-and-objectives.tex | 169 + docs/report/Chapters_Research/evaluation.tex | 55 + .../Chapters_Research/experiment-methods.tex | 13 + .../results-and-conclusions.tex | 128 + ...software-design-implementation-testing.tex | 283 + docs/report/FrontMatter/abstract.tex | 15 + docs/report/FrontMatter/acknowledgements.tex | 14 + docs/report/FrontMatter/cover.tex | 32 + docs/report/FrontMatter/declaration.tex | 54 + docs/report/README.md | 40 + docs/report/StylesAndReferences/IEEEannot.bst | 2655 + .../report/StylesAndReferences/IEEEannotU.bst | 2474 + .../StylesAndReferences/authordate2annot.bst | 1364 + .../report/StylesAndReferences/mmp-report.sty | 358 + .../report/StylesAndReferences/references.bib | 576 + docs/report/img/AVA-entry.pdf | 3 + docs/report/img/HL-Architecture-Diagram.pdf | 3 + .../img/HL-Architecture-Diagram.pdf_tex | 58 + docs/report/img/HL-Architecture-Diagram.svg | 3962 + docs/report/img/HL-Diagram-CNN-Simplified.pdf | 3 + .../img/HL-Diagram-CNN-Simplified.pdf_tex | 58 + docs/report/img/HL-Diagram-CNN-Simplified.svg | 2761 + docs/report/img/HL-Diagram-CNN.pdf | 3 + docs/report/img/HL-Diagram-CNN.pdf_tex | 58 + docs/report/img/HL-Diagram-CNN.svg | 6675 + docs/report/img/aadb.png | 3 + docs/report/img/aqa-on-ava.png | 3 + docs/report/img/archillect.png | 3 + docs/report/img/calculate_image_rating.pdf | 3 + docs/report/img/cnn-testing.png | 3 + docs/report/img/diagrams/.svg | 0 .../img/diagrams/brightness_filter.drawio | 1 + .../report/img/diagrams/filter_brightness.pdf | 3 + .../report/img/diagrams/filter_brightness.uml | 16 + docs/report/img/diagrams/filter_paths.pdf | 3 + docs/report/img/diagrams/filter_paths.svg | 28 + docs/report/img/diagrams/filter_paths.uml | 16 + docs/report/img/diagrams/load_config.pdf | 3 + docs/report/img/diagrams/load_config.svg | 29 + docs/report/img/diagrams/load_config.uml | 17 + docs/report/img/diagrams/load_video.svg | 0 docs/report/img/diagrams/load_video.uml | 0 docs/report/img/diagrams/umlToPdf.sh | 9 + docs/report/img/dof.jpg | 3 + .../exp-3-overcastjuly-melindwr1.png | 3 + .../exp-3-overcastjuly-melindwr2.png | 3 + .../exp-3-sunnyaugust-camels_hump.png | 3 + .../exp-3-sunnyaugust-diggers_end.png | 3 + .../exp-3-sunnyaugust-drunken_druid.png | 3 + .../exp-3-sunnyaugust-hippety_hop.png | 3 + .../exp-3-sunnyaugust-melindwr1.png | 3 + .../exp-3-sunnyaugust-melindwr2.png | 3 + .../exp-3-sunnyaugust-spaghetti_junction.png | 3 + docs/report/img/experiments/experiment-1.png | 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/dev/null +++ b/README.txt @@ -0,0 +1,78 @@ +Autophotographer is a tool that helps users filter the best aesthetic quality images from a video. + +. +├── data/ Generated data +├── docker-compose.yaml Docker-compose file for quick configuration of mount points +├── Dockerfile.amd-gpu Dockerfile for AMD GPUs +├── Dockerfile.cpu Dockerfile for CPU +├── Dockerfile.nvidia-gpu Dockerfile for Nvidia GPUs +├── docs/ Report and project proposal documents +├── environment.yml Anaconda environment dependencies +├── .git Git configuration +├── .gitattributes Git LFS tracking file +├── .gitignore Git ignore file +├── img/ Repository images +├── pyproject.toml Project's package build system requirements and information +├── README.txt Information about the project's structure +├── requirements_dev.txt Python package requirements for testing +├── requirements.txt Python package requirements +├── setup.cfg Python package configuration file +├── setup.py Python package configuration file +├── src/ Project source code +├── terraform/ Terraform IaC +├── test/ Tests +└── .woodpecker/ Pipeline declarations for WoodpeckerCI + +data/ +└── ratings.txt Single-value calculated ratings for AVA dataset + +terraform/ +├── google Terraform IaC for google cloud compute +├── linode Terraform IaC for linode cloud platform + +tests/ +├── integration/ Integrations tests +├── pytest.ini Pytest configuration file +└── unit/ Unit tests + +.woodpecker/ +├── .lint.yml Linting pipeline +└── .test.yml Testing pipeline + +src/ +├── autophotographer/ Main project source code +├── experiments/ Experiments to test the project +├── __init__.py +├── output CNN model output and training graphs + +src/autophotographer/ +├── autophotographer_main.py Code for main pipeline +├── cnn/ CNN code +├── config.yml configuration file for autophotographer_main.py +├── filters/ source code for filters (only some were extracted here) +├── __init__.py +├── predict.py Predict and graph a random batch of AVA images + +src/autophotographer/cnn/ +├── config.py Config python file holding variables like batch size and validation split +├── dataframe.csv Exported dataframe of AVA image path locations, ratings and IDs +├── dataset.py Functions for working with the AVA dataset +├── export/ Exported tensors (might be removed to meet the file size requirements of submission) +├── __init__.py +├── model.py CNN training script +├── predict.py Use to predict a rating given an image and a model +└── __pycache__ + +To use the docker container environment (which includes all dependencies): + +In the project root type: +"docker-compose build" to build the docker file +"docker-compose run autophotographer" to run and exec into the environment +inside the container run "pip install -e ." to install the package +you can then run "python /mmp-osp1/src/autophotographer/autophotographer_main.py -i path_to_input_video_or_images" to run the pipeline. + +If using docker, make sure to check the docker-compose file to configure the mount points of the project. The reason why mount points were use instead of copying the source into the container on build was to reduce image sizes and speed up development. + +Downloading the AVA dataset: +The dataset used in the project was downloaded from here: https://mega.nz/folder/9b520Lzb#2gIa1fgAzr677dcHKxjmtQ +This was featured on a GitHub page (https://github.com/imfing/ava_downloader) which also includes a script to scrape the images and generate the dataset yourself or there's also a torrent link. diff --git a/data/ratings.txt b/data/ratings.txt new file mode 100644 index 0000000..2b65104 --- /dev/null +++ b/data/ratings.txt @@ -0,0 +1,255530 @@ +953619 5.637097 +953958 4.698413 +954184 5.674603 +954113 5.773438 +953980 5.209302 +954175 5.6 +953349 6.101562 +953645 6.007874 +953897 6.523438 +953841 5.984496 +953417 6.112903 +953777 6.59375 +953756 5.796875 +954195 5.040984 +953903 5.943548 +954222 6.579365 +953889 6.553846 +953844 5.914062 +954104 5.95935 +954229 5.653226 +953550 6.746154 +953726 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average pool, 1000-d fc, softmax
average pool, 1000-d...
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ResNet50
ResNet50
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FC 1, Relu
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Freeze the weights on these layers
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ResNet50
(Pre-trained on ImageNet)

ResNet50...
Modified Model
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Replace softmax layer with
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1 Output: Predicted Aesthetic Rating
1 Output: Predi...
1000 Outputs:
Probability of each class
1000 Outputs:...Text is not SVG - cannot display \ No newline at end of file diff --git a/docs/mid-project.odp b/docs/mid-project-demo/mid-project.odp similarity index 100% rename from docs/mid-project.odp rename to docs/mid-project-demo/mid-project.odp diff --git a/docs/report/.gitignore b/docs/report/.gitignore new file mode 100644 index 0000000..360474b --- /dev/null +++ b/docs/report/.gitignore @@ -0,0 +1,303 @@ +## Core latex/pdflatex auxiliary files: +*.aux +*.lof +*.log +*.lot +*.fls +*.out +*.toc +*.fmt +*.fot +*.cb +*.cb2 +.*.lb + +## Intermediate documents: +*.dvi +*.xdv +*-converted-to.* +# these rules might exclude image files for figures etc. +# *.ps +# *.eps +# *.pdf + +## Generated if empty string is given at "Please type another file name for output:" +.pdf + +## Bibliography auxiliary files (bibtex/biblatex/biber): +*.bbl +*.bcf +*.blg +*-blx.aux +*-blx.bib +*.run.xml + +## Build tool auxiliary files: +*.fdb_latexmk +*.synctex +*.synctex(busy) +*.synctex.gz +*.synctex.gz(busy) +*.pdfsync + +## Build tool directories for auxiliary files +# latexrun +latex.out/ + +## Auxiliary and intermediate files from other packages: +# algorithms +*.alg +*.loa + +# achemso +acs-*.bib + +# amsthm +*.thm + +# beamer +*.nav +*.pre +*.snm +*.vrb + +# changes +*.soc + +# comment +*.cut + +# cprotect +*.cpt + +# elsarticle (documentclass of Elsevier journals) +*.spl + +# endnotes +*.ent + +# fixme +*.lox + +# feynmf/feynmp +*.mf +*.mp +*.t[1-9] +*.t[1-9][0-9] +*.tfm + +#(r)(e)ledmac/(r)(e)ledpar +*.end +*.?end +*.[1-9] +*.[1-9][0-9] +*.[1-9][0-9][0-9] +*.[1-9]R +*.[1-9][0-9]R +*.[1-9][0-9][0-9]R +*.eledsec[1-9] +*.eledsec[1-9]R +*.eledsec[1-9][0-9] +*.eledsec[1-9][0-9]R +*.eledsec[1-9][0-9][0-9] +*.eledsec[1-9][0-9][0-9]R + +# glossaries +*.acn +*.acr +*.glg +*.glo +*.gls +*.glsdefs +*.lzo +*.lzs +*.slg +*.slo +*.sls + +# uncomment this for glossaries-extra (will ignore makeindex's style files!) +# *.ist + +# gnuplot +*.gnuplot +*.table + +# gnuplottex +*-gnuplottex-* + +# gregoriotex +*.gaux +*.glog +*.gtex + +# htlatex +*.4ct +*.4tc +*.idv +*.lg +*.trc +*.xref + +# hyperref +*.brf + +# knitr +*-concordance.tex +# TODO Uncomment the next line if you use knitr and want to ignore its generated tikz files +# *.tikz +*-tikzDictionary + +# listings +*.lol + +# luatexja-ruby +*.ltjruby + +# makeidx +*.idx +*.ilg +*.ind + +# minitoc +*.maf +*.mlf +*.mlt +*.mtc[0-9]* +*.slf[0-9]* +*.slt[0-9]* +*.stc[0-9]* + +# minted +_minted* +*.pyg + +# morewrites +*.mw + +# newpax +*.newpax + +# nomencl +*.nlg +*.nlo +*.nls + +# pax +*.pax + +# pdfpcnotes +*.pdfpc + +# sagetex +*.sagetex.sage +*.sagetex.py +*.sagetex.scmd + +# scrwfile +*.wrt + +# svg +svg-inkscape/ + +# sympy +*.sout +*.sympy +sympy-plots-for-*.tex/ + +# pdfcomment +*.upa +*.upb + +# pythontex +*.pytxcode +pythontex-files-*/ + +# tcolorbox +*.listing + +# thmtools +*.loe + +# TikZ & PGF +*.dpth +*.md5 +*.auxlock + +# titletoc +*.ptc + +# todonotes +*.tdo + +# vhistory +*.hst +*.ver + +# easy-todo +*.lod + +# xcolor +*.xcp + +# xmpincl +*.xmpi + +# xindy +*.xdy + +# xypic precompiled matrices and outlines +*.xyc +*.xyd + +# endfloat +*.ttt +*.fff + +# Latexian +TSWLatexianTemp* + +## Editors: +# WinEdt +*.bak +*.sav + +# Texpad +.texpadtmp + +# LyX +*.lyx~ + +# Kile +*.backup + +# gummi +.*.swp + +# KBibTeX +*~[0-9]* + +# TeXnicCenter +*.tps + +# auto folder when using emacs and auctex +./auto/* +*.el + +# expex forward references with \gathertags +*-tags.tex + +# standalone packages +*.sta + +# Makeindex log files +*.lpz + +# xwatermark package +*.xwm + +# REVTeX puts footnotes in the bibliography by default, unless the nofootinbib +# option is specified. Footnotes are the stored in a file with suffix Notes.bib. +# Uncomment the next line to have this generated file ignored. +#*Notes.bib + +.sync_* \ No newline at end of file diff --git a/docs/report/Appendices/appendixA.tex b/docs/report/Appendices/appendixA.tex new file mode 100755 index 0000000..875c916 --- /dev/null +++ b/docs/report/Appendices/appendixA.tex @@ -0,0 +1,34 @@ +\chapter{Third-Party Code and Libraries} +% +%If you have made use of any third party code or software libraries, i.e. any code that you have not designed and written yourself, then you must include this appendix. +% +%As has been said in lectures, it is acceptable and likely that you will make use of third-party code and software libraries. If third party code or libraries are used, your work will build on that to produce notable new work. The key requirement is that we understand what your original work is and what work is based on that of other people. +% +%Therefore, you need to clearly state what you have used and where the original material can be found. Also, if you have made any changes to the original versions, you must explain what you have changed. +% +%The following is an example of what you might say. +% +%Apache POI library - The project has been used to read and write Microsoft Excel files (XLS) as part of the interaction with the client's existing system for processing data. Version 3.10-FINAL was used. The library is open source and it is available from the Apache Software Foundation +%\cite{apache_poi}. The library is released using the Apache License +%\cite{apache_license}. This library was used without modification. +% +%Include as many declarations as appropriate for your work. The specific wording is less important than the fact that you are declaring the relevant work. + +The following third party code and libraries were used to support this project\footnote{This list does not include the libraries pulled down as dependencies of entries in this list.}: +\begin{itemize} +\item \textbf{opencv-python} - provides many useful functions for working with images and video +\item \textbf{numpy} - provides multi-dementional arrays and mathematical functions which can be applied to said arrays +\item \textbf{matplotlib} - provides functions for plotting and exporting graphs +\item \textbf{pandas} - provides advanced table data structures and mathematical functions to apply to them +\item \textbf{PyYAML} - provides functions to read and write YAML files +\item \textbf{scikit-image} - provides many functions for analysing images +\item \textbf{tqdm} - provides progress bars +\item \textbf{flake8} - (used in testing) provides linting, helping find inconsistencies with style +\item \textbf{pytest} - (used in testing) a python-based testing framework +\item \textbf{pytest-cov} - (used in testing) a plugin for pytest which will provide a report on test coverage +\item \textbf{unittest} - (used in testing) the mock module of unittest was used to use mocks in testing +\item \textbf{mypy} - (used in testing) provides linting for type checking +\item \textbf{torch} - machine learning framework that provides tools for building and training models +\item \textbf{torchvision} - library that contains datasets and models for neural networks +\end{itemize} + diff --git a/docs/report/Appendices/appendixB.tex b/docs/report/Appendices/appendixB.tex new file mode 100755 index 0000000..f0e4433 --- /dev/null +++ b/docs/report/Appendices/appendixB.tex @@ -0,0 +1,90 @@ +\chapter{Code Examples} + +%For some projects, it might be relevant to include some code extracts in an appendix. You are not expected to put all of your code here - the correct place for all of your code is in the technical submission that is made in addition to the Project Report. However, if there are some notable aspects of the code that you discuss, including that in an appendix might be useful to make it easier for your readers to access. +% +%As a general guide, if you are discussing short extracts of code then you are advised to include such code in the body of the report. If there is a longer extract that is relevant, then you might include it as shown in the following section. +% +%Only include code in the appendix if that code is discussed and referred to in the body of the report. + +\section{Woodpecker pipelines} +\subsection{Lint pipeline} +The lint pipeline was use to automatically report back on any linting issues with the code after a commit. +\begin{verbatim} +pipeline: + flake8: + image: python:3.8 + commands: + - python3.8 -m pip install flake8 + - flake8 src/ + mypy: + image: python:3.8 + commands: + - python3.8 -m pip install mypy + - mypy src/ + isort: + image: python:3.8 + commands: + - python3.8 -m pip install isort + - isort --diff src/ +branches: dev +\end{verbatim} +\subsection{Test pipeline} +\begin{verbatim} +pipeline: + unit-tests: + image: python:3.8 + commands: + - apt update -y && apt install libgl1 -y + - python3.8 -m pip install -r ./requirements.txt + - python3.8 -m pip install -r ./requirements_dev.txt + - python3.8 -m pip install -e . + - pytest test/ -v +branches: dev +\end{verbatim} +\subsection{Configuration file}\label{config file} +\begin{verbatim} +--- +# Configuration file for the autophographer tool + +# List of filters to apply in order +# Note: Possible filters include: brightness, filesize, contrast, focus +filters: + - brightness + - filesize + - contrast + - focus + +# Whether or not to apply CNN ranking +CNNrank: False + +# Ignore video files and don't bother processing them into frames +# Note: Useful if directory contains original video and indivual +# frames from video (prevents processing the same frames more than once) +ignore_video: True + +# Options for brightness filter +brightness_options: + threshold: 0.25 + +# Options for filesize filter +filesize_options: + threshold: 0.35 + +# Options for contrast filter +contrast_options: + threshold: 0.35 + +# Options for focus filter +focus_options: + threshold: 0.5 +... +\end{verbatim} + +\subsection{pil\_loader() method} +This method was taken from a GitHub issue comment \href{https://github.com/python-pillow/Pillow/issues/835\#issuecomment-53999355}{https://github.com/python-pillow/Pillow/issues/835\#issuecomment-53999355} +\begin{verbatim} +def pil_loader(path): + with open(path, 'rb') as f: + image = Image.open(f) + return image.convert('RGB') +\end{verbatim} diff --git a/docs/report/Chapters_Research/background-and-objectives.tex b/docs/report/Chapters_Research/background-and-objectives.tex new file mode 100755 index 0000000..bf37114 --- /dev/null +++ b/docs/report/Chapters_Research/background-and-objectives.tex @@ -0,0 +1,169 @@ +\chapter{Background \& Objectives} + +%This section should discuss your preparation for the project, including background reading, your analysis of the problem and the process or method you have followed to help structure your work. It is likely that you will reuse part of your outline project specification, but at the end of the project you should have more to discuss. +% +%\textbf{Note}: +% +%\begin{itemize} +% \item All of the sections and text in this example are for illustration purposes. The main Chapters are a good starting point, but the content and actual sections that you include are likely to be different. +% +% \item Look at the document MMP\_S08 Project Report and Technical Work \cite{ProjectReportTechicalWork} for additional guidance. +% +%\end {itemize} + +\section{Background} +%What was your background preparation for the project? What similar systems or research techniques did you assess? What was your motivation and interest in this project? +\subsection{Context} +In a world where most people have a camera in their pocket, the number of pictures being taken every minute has exponentially increased in the last few decades. Smartphones cameras have reached the point where they can rival their fully-fledged counterparts. The necessity\footnote{Both \textit{Google} and \textit{Apple} accounts are required to use their respective app stores and \textit{Apple} doesn't support alternatives app stores.} of online accounts on \textit{Android} and \textit{iOS}, which both include cloud storage (\textit{Google Drive / Google Photos} and \textit{iCloud} respectively) have made automatic cloud backup for photographs the norm. Together, these aspects have lowered the entry requirements and have enabled an entire generation to produce large quantities of high-resolution photographs, which have been previously limited to professional and hobbyist photographers. + +The upsurge of data produced and people's reliance on free cloud storage has started to create storage concerns for providers. To combat this, certain providers have taken measures to reduce the load by reducing or introducing service limits\cite{google_photos}\cite{google_workspace}. In turn, this had led people to reconsider how they manage their data. People have had to return to the tedious and manual practise of filtering through their old photographs in order to free up space for new content. + +The significance of photo selection isn't limited to storage issues. The rise of social media and influencer-culture has culminated in entire businesses that require carefully selected photographs. \textit{Instagram}, a photo-sharing social media platform, has become the most prominent hub for influencer-based marketing. Its popularity has spawned many Instagram curation apps\cite{instagram_planner}\cite{unum}, which helps users and businesses plan out their posts to work towards a cohesive profile aesthetic\cite{instagram_aesthetic}. This has also caught the attention of data scientists who have investigated what makes certain images perform better online than others\cite{intrinsic_image_popularity}. + +Image aesthethic quality assessment is the process of automatically assessing the visual aesthetic rating of an image. This area of research has seen recent improvements in the last 5 years due to the advancements in AI, computer vision, and machine learning. On the AVA dataset\footnote{The AVA (Aesthetic Visual Assessment) dataset is the most common dataset used for aesthetic quality assessment.} alone we have seen accuracy rates of up to 83\% when predicting the aesthetic quality rating of images, See figure \ref{fig:aqa-on-ava}. + +\begin{figure}[H] +\centering +\includegraphics[width=\textwidth]{aqa-on-ava} +\caption{Accuracy of models trained on the AVA dataset\cite{aqa-on-ava}} +\label{fig:aqa-on-ava} +\end{figure} +\subsection{Related Work} +\paragraph{Trophy Camera} +In 2017, fine artist Dries Depoorter and professional photographer Max Pinckers developed a camera ``that can only make award winning pictures''\cite{trophy_camera}. This camera was built using a Raspberry Pi and was programmed to only save award-winning photographs, which were subsequently uploaded to a website: \href{https://trophy.camera}{trophy.camera}\cite{trophy_camera_site}. The AI was trained using previous winning photographs from the WPPY (World Press Photo’s of the Year) contest (\textit{Warning: Website includes images some might find disturbing, including death, extreme violence, and suffering})\cite{wpp}. By comparing the photos featured on \href{https://trophy.camera}{\textit{trophy.camera}} and the previous winning photographs of WPPY, you can see the effectiveness of the project is questionable. This isn't surprising, given the stark difference in subject matter and the photography skills of the general public versus the award-winning photographers. The majority of the photographs submitted to the WPPY are taken by professional photographers using high-end cameras (See figure \ref{fig:trophy camera train photo}) and mostly depict global conflict. In contrast, the Trophy Camera is limited to the walls of a gallery, using a low-end camera, and the photos are taken by the general public (See figure \ref{fig:trophy camera photo}). This is an example where the data used for training doesn't match the desired use-case of the project, resulting in images that fail to achieve an ``award winning'' appearance. +\begin{figure}[H] +\begin{subfigure}[b]{0.3\textwidth} +\centering +\includegraphics[width=\textwidth]{trophy-camera} +\caption{Trophy Camera\cite{trophy_camera}} +\label{fig:trophy camera} +\end{subfigure} +\hfill +\begin{subfigure}[b]{0.3\textwidth} +\centering +\includegraphics[width=\textwidth]{trophy-camera-image} +\caption{Photo taken with Trophy Camera\cite{trophy_camera_site}} +\label{fig:trophy camera photo} +\end{subfigure} +\hfill +\begin{subfigure}[b]{0.3\textwidth} +\centering +\includegraphics[width=\textwidth]{wpp} +\caption{Example of photo used to train Trophy Camera\cite{wpp-spencer}} +\label{fig:trophy camera train photo} +\end{subfigure} +\caption{Trophy Camera} +\label{fig:trophy camera photos} +\end{figure} +\paragraph{Archillect} A combination of the words ``archive'' and ``intellect'', Archillect\cite{archillect} is an AI that automatically curates visually stimulating content found online. To do this, Archillect uses an algorithm and a list of of keywords that searches for posts and pages, then crawls pages linked from original results to find new images and gain relevant contextual knowledge and learn new keywords. Ultimiately, Archillect learns what images create visual stimulation for people on social media, reposting them and updating the algorithm according "likes" and other user engagement metrics. + +\begin{figure}[H] +\centering +\includegraphics[width=\textwidth]{archillect} +\caption{\href{https://archillect.com}{archillect.com} homepage\cite{archillect}} +\label{fig:archillect} +\end{figure} + +\subsection{Motivation} +Historically, the most common and successful approaches to grading the aesthetic quality of images has been through machine learning. This involves creating a neural network, typtically a CNN (Convulution Neural Network), and training it with professional photography based datasets. The most common of these datasets being AVA (Aesthetic Visual Analysis), which is comprised of a set of professionally taken photographs and an aesthetic rating provided by numerous professional photographers that acts as a ground truth for aesthetic quality. + + +Many people believe aesthetics are subjective. We can observe this when the aesthetics of certain art pieces can often be contested and contraversial. Considering the percieved subjective nature of aesthetics, there seems to be certain ideas that are almost universally accepted as aesthetic. In art we often hear about composition rules like the golden ratio, rule of thirds, and symmetry which are meant to invoke a positive sentiment. See figure \ref{fig:common photographic techniques}. For others, aesthetics can't be reduced down to a set of predifined rules and many people welcome images that break the natural conventions of professional photography. +\begin{figure}[H] +\centering + +\begin{subfigure}[b]{0.45\textwidth} +\centering +\includegraphics[width=\textwidth]{golden-ratio} +\caption{Golden Ratio\cite{golden_ratio}} +\label{fig:golden ratio} +\end{subfigure} +\hfill +\begin{subfigure}[b]{0.45\textwidth} +\centering +\includegraphics[width=\textwidth]{symmetry} +\caption{Symmetry\cite{symmetry}} +\label{fig:symmetry} +\end{subfigure} +\begin{subfigure}[b]{0.45\textwidth} +\centering +\includegraphics[width=\textwidth]{rule-of-thirds} +\caption{Rule of Thirds\cite{rule-of-thirds}} +\label{fig:rule of thirds} +\end{subfigure} +\hfill +\begin{subfigure}[b]{0.45\textwidth} +\centering +\includegraphics[width=\textwidth]{dof} +\caption{Shallow Depth of Field\cite{dof}} +\label{fig:y equals x} +\end{subfigure} +\caption{Common photographic techniques} +\label{fig:common photographic techniques} +\end{figure} + +\subsubsection{Applications} +Automatic image selection is a useful concept that can be used in many applications. The main motivation for the project was to use the system as a acessibility tool, allowing those who are less technically or physically abled to take good aesthetic-quality images. They use a head-mounted camera and record a journey our outing and the tool could automatically reduce the footage into an album of good-looking photos for them to enjoy. + +Professional photographers could use automatic image selection to remove technically poor images from a large collection of images from a photoshoot. This process would help alleviate much of the manual filter photographers have to do post photoshoot. + +\subsubsection{Personal motivations} +An important motivation for this project and it's direction is my interest in machine learning. The CS36220 Machine Learning\cite{ml-module} module acted as a good introduction to the topic, but I wanted to get some personal experience with deep learning as it's an area of computer science I find really interesting. +\section{Analysis} +%Taking into account the problem and what you learned from the background work, what was your analysis of the problem? How did your analysis help to decompose the problem into the main tasks that you would undertake? Were there alternative approaches? Why did you choose one approach compared to the alternatives? +% +%There should be a clear statement of the research questions, which you will evaluate at the end of the work. +% +%In most cases, the agreed objectives or requirements will be the result of a compromise between what would ideally have been produced and what was felt to be possible in the time available. A discussion of the process of arriving at the final list is usually appropriate. +% + + +% When processing video files, each frame should be the same resolution +\subsection{Problem Description} +This project aims to explore the question of "Can we use a computer to make accurate aesthetic judgements on images?". +In order to create a program to detect and select aesthetics images from a video file, the video file needs to be broken down into individual frames, then each frame needs to be analysed against certain aesthetic features and rules like (rule of thirds, contrast, brightness, focus). Each of these filters will need to be implemented in such a way that allows any order and combination of filters to be used. Lastly, a machine learning approach will be taken to rate and rank the remaining images. For this we can use a CNN (Convolution Neural Network) which will need to be trained on professional photographs as they can be considered a good base for what is considered a good ``aesthetic'' quality. + +\subsection{Approach} +The specific approach taken for this project is to use a combination of machine learning and conventional image processing techniques. This is a good balance between performance and accuracy as the conventional image processing techniques can filter out the poor technical images (blurry, low contrast, extreme exposure etc.) therefore limiting the amount of processing required by the machine learning model at the end of the pipeline. + +\subsection{Alternative Approaches} +This project could also be approached from an exclusively coventional computer vision approach, which would require writing specific code to recognise aesthetic photographic techniques (like rule of thirds and vanishing point: see figure \ref{fig:common photographic techniques}) and using those to help determine the aesthethic quality of an image. + +A machine learning only approach could also be taken but for the context of this project this would be computationally wasteful. Due to the nature of a continous video recording, many frames will be blurry or under exposed due to lighting changes. These images are technically poor in quality and processing hundres of them using a CNN would be wasteful when they could be more easily discarded using conventional image processing techniques. + +\subsection{Aim} +The aim of the project is to develop a piece of software that will take a video or a set of images as an input, process them through filtering, and output a subset of "aesthetic" images or frames. The set will be processed through filters which will be implementated as part of the project. +\subsection{Objectives} +\begin{itemize} +\item Context specific research into machine learning + \begin{itemize} + \item Research suitable machine learning frameworks + \item Research how to start building a CNN + \end{itemize} +\item Setup tools for development + \begin{itemize} + \item Host a Gitea instance to hsot the project's repository + \item Create repository for project + \item Mirror repository to GitLab.com for availability + \item Setup WoodpeckerCI for CI/CD workloads and connect it to the project repository + \item Setup pipelines for automated testing in WoodpeckerCI + \end{itemize} +\item Research convential image processing techniques + \begin{itemize} + \item Quantify brightness + \item Quantify contrast + \item Quantify focus + \item Depth of field detection + \item Vanishing point detection + \end{itemize} +\end{itemize} +\subsubsection{Research Questions} +\begin{itemize} +\item How effective is the machine learning approach compared to a more conventional one? +\item Which order of filtering is most effective? +\item Can a CNN be used to make aesthetic judgements of an image? +\end{itemize} + +%You need to describe briefly the life cycle model or research method that you used. You do not need to write about all of the different process models that you are aware of. Focus on the process model or research method that you have used. It is possible that you needed to adapt an existing method to suit your project; clearly identify what you used and how you adapted it for your needs. +% +%For the research-oriented projects, there needs to be a suitable process for the construction of the software elements that support your work. diff --git a/docs/report/Chapters_Research/evaluation.tex b/docs/report/Chapters_Research/evaluation.tex new file mode 100755 index 0000000..c23bcab --- /dev/null +++ b/docs/report/Chapters_Research/evaluation.tex @@ -0,0 +1,55 @@ +\chapter{Evaluation} % 1818 WORDS +% +%Examiners expect to find a section addressing questions such as: +% +%\begin{itemize} +% \item Were the requirements correctly identified? +% \item Were the design decisions correct? +% \item Could a more suitable set of tools have been chosen? +% \item How well did the software meet the needs of those who were expecting to use it? +% \item How well were any other project aims achieved? +% \item If you were starting again, what would you do differently? +%\end{itemize} +% +%Other questions can be addressed as appropriate for a project. +% +%Such material is regarded as an important part of your work; it should demonstrate that you are capable not only of carrying out a piece of work but also of thinking critically about how you did it and how you might have done it better. This is seen as an important part of an honours degree. +% +%There will be good things and room for improvement with any project. As you write this section, identify and discuss the parts of the work that went well and also consider ways in which the work could be improved. +% +%In the latter stages of the module, we will discuss the evaluation. That will probably be around week 9, although that differs each year. + +\section{Design Decisions} + + +\section{Development Process} +Due to the lack of a strict development process, tasks weren't evaluated and took more effort than expected. This lead to the project pulling back its scope over the course of development. A stricter development process would have enabled the project to grow at a steadier pace and evaluating the work and time taken for each work item at the end of each week would have helped with the prioritising of tasks and adapting of scope. + +\section{Approach} +The machine learning approach was chosen due to the attractiveness of the possible output rather than it's context as part of a major project. Going down the machine learning path required a lot learning a getting a good grasp of complex topics which took up a large portion of the project. In the end, more time was spent learning about CNNs than expected which lead to less time developing. + +\section{Project State} +The project is considered as unfinished as there was much more planned to implement. The filters are basic in concept and in implementation and require using a manually determining a "good" threshold and applying it. If the work were to be continued, the pipeline would process each frame of a video and use the distribution of values from a given filter to determine lower and upper bound outliers which would thn be removed automatically. + +\subsection{Implementation} +The overall implementation of the project is incomplete, most of the code was hard-coded and static which made it difficult to work with. With more time the project would be restructured and refactorer to make the code easier to work with and develop further. +\subsection{Testing} +One of the biggest issues with the project is a lack of testing. Due to maining of the bad decisions with the approach of the project and the lack of a strict development process, testing was left until the very end. +\subsection{Experiments} +Many of the experiments only give artificial insight into the level of success of the project rather than providing meaningful metrics. + +\section{Report} +The overall quality of the report is quite poor and many of its sections are limited in detail and scope. One of the difficulties that was presented in writing this report was a lack of experience in research-based approaches and report writing. This made it difficult to give the project a research-based context. Much of the detailed design is missing from the report and there's a lack of detail when talking about specific implementation issues. + +\section{Time management} +The time management for the project was very poor and it was a struggle to finish everything that was intially planned. This mostly due to a lack detailed planning and a strict development process. This led to an ambiguity of how much work was required to finish the project which became clearer towards the deadline. Near the end of the project, it was difficult to balance project work and other areas of life and personal issues. + +\section{Futher Work} +This technical work achieved in this project is a good foundation for further work. Alterations can be made to the CNN to attempt to improve it's accuracy with later iterations. One way that this can be done is to explore fine-tuning the CNN, potentially unfreezing all the layers and training the model again. + +If composition filters were implemented (golden ratio, rule of thirds, symmetry etc.) they could be used to boost the detected aesthetic features. If rule of thirds is loosely detected in an image, the option could be added to automatically crop the image in a non-destructive way\footnote{Saving the result as a new image, rather than overwriting the original} so that the rule of thirds has a stronger presence in the image. This could also be applied to filters like brightness and contrast but might be less successful due to the sensitivity in artificially enhancing them. + +A good next step would be to refactor and restructure the code to allow plug-in filters, making filter development easier but also allowing other developers to write their own that can be dropped into the pipeline. + +\section{Personal conclusion} +Overall this project has been more of a learning experience and an opportunity to work with new technology for me than a well planned experiment. I feel like I have gained a lot while also not having much to show for it. diff --git a/docs/report/Chapters_Research/experiment-methods.tex b/docs/report/Chapters_Research/experiment-methods.tex new file mode 100755 index 0000000..c164c93 --- /dev/null +++ b/docs/report/Chapters_Research/experiment-methods.tex @@ -0,0 +1,13 @@ +%\addcontentsline{toc}{chapter}{Development Process} +\chapter{Experiment Methods} +% +%This section should discuss the overall hypothesis being tested and justify the approach selected in the context of the research area. Describe the experiment design that has been selected and how measurements and comparisons of results are to be made. +% +%You should concentrate on the more important aspects of the method. Present an overview before going into detail. As well as describing the methods adopted, discuss other approaches that were considered. You might also discuss areas that you had to revise after some investigation. +% +%You should also identify any support tools that you used. You should discuss your choice of implementation tools or simulation tools. For any code that you have written, you can talk about languages and related tools. For any simulation and analysis tools, identify the tools and how they are used on the project. +% +%For the parts of your project that need some engineering (hardware, software, firmware, or a mixture) to support the experiments, include details in your report about your design and implementation. You should discuss with your supervisor whether it is better to include a different top-level section to describe any engineering work. In this template, Chapter 3 is suggested as a place for that discussion. + +\section{Hypothesis} +Hypothesis: Can a CNN and an a set of image processors make accurate aesthetic judgments on images. diff --git a/docs/report/Chapters_Research/results-and-conclusions.tex b/docs/report/Chapters_Research/results-and-conclusions.tex new file mode 100755 index 0000000..fa30f32 --- /dev/null +++ b/docs/report/Chapters_Research/results-and-conclusions.tex @@ -0,0 +1,128 @@ +\chapter{Results and Conclusions} +% +%This section should discuss issues you encountered as you tried to implement your experiments. What were the results of running the experiments? What conclusions can you draw from these results? What graphs or other information have you assessed regarding your experiments? Discuss those. +% +%During the work, you might have found that elements of your experiments were unnecessary or overly complex; perhaps third-party libraries were available that simplified some of the functions that you intended to implement. If things were easier in some areas, then how did you adapt your project to take account of your findings? +% +%It is more likely that things were more complex than you first thought. In particular, were there any problems or difficulties that you found during implementation that you had to address? Did such problems simply delay you or were they more significant? +% +%If you had multiple experiments to run, it may be sensible to discuss each experiment in separate sections. + +\section{CNN} +\subsection{Training} +The first training attempt for the CNN was only run for 20 epochs on a CPU to check for runtime errors. During these 20 epochs the loss gradients didn't plateau meaning the model could benefit from longer training. The next attempt was run for 2000 epochs on a GPU. Figure \ref{fig: 2000 epochs} shows that the training loss started to slow down around 30 epochs and plateaued at around 60. While the validation loss also plateaued around 60 epochs, the variance in loss was much greater. This most likely means the model has converged on an concept of aesthetic quality that doesn't match the concept it was set out to learn. As shown in figure \ref{fig: terminal-loss} the resulting training loss was 0.576810 and the validation loss was 0.604089, this means that on average the model is roughly 60\% off the ground truth with quite a high variance. +\begin{figure}[H] +\begin{subfigure}[b]{0.48\textwidth} +\centering +\includegraphics[width=\textwidth]{plot-20-epochs} +\caption{20 epochs} +\label{fig: 20 epochs} +\end{subfigure} +\hfill +\begin{subfigure}[b]{0.48\textwidth} +\centering +\includegraphics[width=\textwidth]{plot-2000-epochs} +\caption{2000 Epochs} +\label{fig: 2000 epochs} +\end{subfigure} +\caption{Training loss for model} +\label{fig:training loss} +\end{figure} +\begin{figure}[H] +\centering +\includegraphics[width=\textwidth]{terminal-loss} +\caption{Terminal output when training} +\label{fig: terminal-loss} +\end{figure} + +\subsection{Testing} +\subsubsection{Experiment 1} +Due to the lack of tuning in the pipeline: experiment 1 is non-functional. +The aim of experiment 1 is to pass a batch of of AVA images and their ratings and compared the average rating of the batch before and after filter. If the average rating has increased it tells us that the pipeline is doing some for of effective filtering. It's not a well thought out experiment so the results are difficult to quantify. +\begin{figure}[H] +\centering +\includegraphics[width=\textwidth]{experiments/experiment-1} +\caption{Experiment 1} +\label{fig: experiment 1} +\end{figure} + +\subsubsection{Experiment 2} +Due to the lack of tuning in the pipeline: experiment 2 is non-functional. +The aim of this experiment was to see which filter could reduce the set the largest amount. The same set of images is passed through each filter once and the remaining images are plotted. +\begin{figure}[H] +\centering +\includegraphics[width=\textwidth]{experiments/experiment-2} +\caption{Experiment 2} +\label{fig: experiment 2} +\end{figure} +\subsubsection{Experiment 3} +During the third experiment, there was an attempt to visualize how the model performed on real data. The model was used to predict the aesthetic quality rating of the frames in the videos provided by Dr Hannah Dee. The ratings were then ranked and the top 5 ranking and lowest 5 ranking entries were plotted. This experiment isn't an accurate metric of how well the model performs, but it useful to see how it performed on data that wasn't from the AVA dataset. Common accross all of the following examples is that the top 5 ranking images lay in the low-6s while the bottom 5 images lay in the high-5s. There doesn't seem to be as much variance as expected from the data, which includes a few shots in very poor lighting conditions and very blurry frames. This might possibly be an architecture issue with the training of the CNN resulting in most images being predicted in the range of 5-6. +\begin{figure}[H] +\centering +\includegraphics[width=\textwidth]{experiments/exp-3-overcastjuly-melindwr1} +\caption{overcastjuly-melindwr1} +\label{fig: overcastjuly-melindwr1} +\end{figure} +\begin{figure}[H] +\centering +\includegraphics[width=\textwidth]{experiments/exp-3-overcastjuly-melindwr2} +\caption{overcastjuly-melindwr2} +\label{fig: overcastjuly-melindwr2} +\end{figure} +\begin{figure}[H] +\centering +\includegraphics[width=\textwidth]{experiments/exp-3-sunnyaugust-camels_hump} +\caption{sunnyaugust-camels\_hump} +\label{fig:sunnyaugust-camels_hump} +\end{figure} +\begin{figure}[H] +\centering +\includegraphics[width=\textwidth]{experiments/exp-3-sunnyaugust-diggers_end} +\caption{sunnyaugust-diggers\_end} +\label{fig: sunnyaugust-diggers_end} +\end{figure} +\begin{figure}[H] +\centering +\includegraphics[width=\textwidth]{experiments/exp-3-sunnyaugust-drunken_druid} +\caption{sunnyaugust-drunken\_druid} +\label{fig: sunnyaugust-drunken_druid} +\end{figure} +\begin{figure}[H] +\centering +\includegraphics[width=\textwidth]{experiments/exp-3-sunnyaugust-hippety_hop} +\caption{sunnyaugust-hippety\_hop} +\label{fig: sunnyaugust-hippety_hop} +\end{figure} +\begin{figure}[H] +\centering +\includegraphics[width=\textwidth]{experiments/exp-3-sunnyaugust-melindwr1} +\caption{sunnyaugust-melindwr1} +\label{fig: sunnyaugust-melindwr1} +\end{figure} +\begin{figure}[H] +\centering +\includegraphics[width=\textwidth]{experiments/exp-3-sunnyaugust-melindwr2} +\caption{sunnyaugust-melindwr2} +\label{fig: sunnyaugust-melindwr2} +\end{figure} +\begin{figure}[H] +\centering +\includegraphics[width=\textwidth]{experiments/exp-3-sunnyaugust-spaghetti_junction} +\caption{sunnyaugust-spaghetti\_junction} +\label{fig: sunnyaugust-spaghetti_junction} +\end{figure} +\subsubsection{Experiment 4} +\begin{figure}[H] +\centering +\includegraphics[width=\textwidth]{experiments/experiment-4.png} +\caption{Artificial modifications and their ratings} +\label{fig: experiment 4} +\end{figure} + +In the 4\textsuperscript{th} experiment. Aritificial data was used to test the model's performance. A base image\cite{unsplash} was used and then artificially edited with GIMP\cite{gimp} to lower it's aesthetic quality. The first image image in figure \ref{fig: experiment 4} is the original photo, the second has had it's contrast lowered, the third has had it's exposure increased, and the fourth has had a gaussian blur applied to it. From the results it's clear to see the model has no understanding of the decline in quality in the edited picture. In this example all of the edited pictures actually score higher than the original picture. + +\section{Filters} +\subsection{Filesize} +\subsection{Contrast} +\subsection{Brightness} +\subsection{Focus} diff --git a/docs/report/Chapters_Research/software-design-implementation-testing.tex b/docs/report/Chapters_Research/software-design-implementation-testing.tex new file mode 100755 index 0000000..992b537 --- /dev/null +++ b/docs/report/Chapters_Research/software-design-implementation-testing.tex @@ -0,0 +1,283 @@ +\chapter{Software Design, Implementation and Testing} + +\section{Development Process} +Originally, the plan was for the project to follow a scrum-like methodology, but due to the research-based nature of the project and working with new technologies -- it was difficult to estimate the time and effort required for certain tasks.Naturally, the weekly meetings with the project supervisor acted as a weekly review of the work done and what work was to be done the following week. When the project repositories were set up, a Kanban board was set up alongside it. This was used to keep track of the progress of tasks and features. Milestones were created to group small tasks together that lead to a bigger task being completed. +%blog +% kanban + +\section{Languages and Frameworks} +\subsection{Python} +Python\cite{python} was selected as the programming langauge for the project due to it's popularity in data science and it's dynamic and weakly typed nature. This enables an easier transisition from project ideas to working code. It was also chosen for it's use in machine learning as it seems to be the main language in most of the top machine learning libraries. + +\subsection{PyTorch} +The most common frameworks for deep learning are \textit{TensorFlow}\cite{tensorflow}, \textit{PyTorch}\cite{pytorch}, and \textit{Keras}\cite{keras}. + +\textit{TensorFlow}, arguably the most known of the three, is developed by Google. It's mostly used in Python but can also be used with C++, Java, and Javascript. It provides a powerful framework for ML (Machine Learning) and AI (Artificial Intelligence) tasks. Although, TensorFlows primarily focuses on creating deep neural network and training. + +\textit{Keras} is a high-level deep-learning API used to interface with TensorFlow. It's main aim is to simplify the process of developing deep neural networks for use in quick experimentation. + +The last of the three, \textit{PyTorch}, is primarily developed by Facebook and acts as the main competitor to TensorFlow. It's gained popularity within the research community due to it's ease of use and gradual learning curve compared to TensorFlow. %why? + +The decision was made to use PyTorch as machine learning isn't the primary aspect of this project. The reduced complexity should speed up development time. + +%This could be one chapter or a few chapters. It should define and discuss the software that is developed to support the research that is being conducted. For example, if your research involves running experiments, what software are you creating to support that work? What functionality is required? What design will be used? What implementation issues are there and what testing is used? +% +%Even though a research project is investigating specific research questions, it is still necessary for you to discuss the software that you develop. Research has a habit of generating bits of software that can exist for several years and need future modification. Therefore you need to be able to discuss the technical issues as well as the research approach. +% +\section{Software Tools and Technologies} +\subsection{VS Code} +The IDE/Editor used for this project is VS Code\footnote{More specifically: VS Codium. A libre-binary version of Microsoft's VS Code. It's built from VS Code's source albeit with tracking and telemetry disabled and then distributed at binaries. It's essential VS Code, so it'll continued to be referenced as such.}. This was chosen as it was a familiar and popular IDE/Editor with good plugin support and features. +\subsection{Docker} +Docker containers were used to host tools like Gitea and Woodpecker on a private server to aid with development. They were also used to create reproducible development and testing environments\footnote{a Dockerfile and Docker-compose file are supplied with the source code for this project.}. +\subsection{Gitea} +For version control this project uses git and Gitea as an open-source and self-hostable git host. Gitea also includes workflow features like bug tracking via ``issues'', kanban boards (see figure \ref{fig:kanban}), and plugins to work with other tools (see section \ref{woodpecker}). The source code for this project is hosted on a personal instance of Gitea hosted at \href{https://git.oscar.blue}{git.oscar.blue}. The project's repository is also mirrored\footnote{Sync interval is every 8 hours.} to \href{https://gitlab.com}{gitlab.com} for availability. +\begin{figure}[H] +\begin{subfigure}[b]{0.4\linewidth} +\centering +\includegraphics[width=\textwidth]{gitea} +\caption{Original Gitea version} +\label{fig:gitea} +\end{subfigure} +\hfill +\begin{subfigure}[b]{0.4\linewidth} +\centering +\includegraphics[width=\textwidth]{gitlab} +\caption{Mirror Gitlab version} +\label{fig:gitea} +\end{subfigure} +\end{figure} + +\begin{figure}[H] +\centering +\includegraphics[width=\textwidth]{kanban} +\caption{Gitea Kanban board} +\label{fig:kanban} +\end{figure} + +\begin{figure}[H] +\centering +\includegraphics[width=\textwidth]{milestones} +\caption{Project milestones} +\label{fig:milestones} +\end{figure} +\subsection{WoodpeckerCI}\label{woodpecker} +WoodpeckerCI, an open-source community fork of DroneCI, is a CI/CD (Continuous Integration/ Continous Deployment) platform used to create automated piplines for tesing and building. A personal instance was hosted at \href{https://woodpecker.oscar.blue}{woodpecker.oscar.blue} and linked to the project's git repository for CI/CD. +\subsubsection{Woodpecker pipelines} + +\begin{figure}[H] +\centering +\includegraphics[width=0.75\textwidth]{woodpecker-pipelines} +\caption{Woodpecker Pipelines} +\label{fig:pipelines} +\end{figure} +\begin{figure}[H] +\centering +\includegraphics[width=0.75\textwidth]{woodpecker-pipeline} +\caption{A Woodpecker Pipeline} +\label{fig:pipeline} +\end{figure} + +Two pipelines were created, one to establish automated testing and the other for source code linting. +\subsection{Terraform} +When training the CNN, Terraform was used to create GPU-enabled cloud compute resources on the fly so that it could easily be built up and torn down during training. Although this code was barely used in the end due to moving away from cloud solutions (See section \ref{Training model} for details). +\section{Design} +%You should concentrate on the more important aspects of the design. It is essential that an overview is presented before going into detail. As well as describing the design adopted it must also explain what other designs were considered and why they were rejected. +% +%The design should describe what you expected to do, and might also explain areas that you had to revise after some investigation. +% +%Typically, for an object-oriented design, the discussion will focus on the choice of objects and classes and the allocation of methods to classes. The use made of reusable components should be described and their source referenced. Particularly important decisions concerning data structures usually affect the architecture of a system and so should be described here. +% +%How much material you include on detailed design and implementation will depend very much on the nature of the project. It should not be padded out. Think about the significant aspects of your system. For example, describe the design of the user interface if it is a critical aspect of your system, or provide detail about methods and data structures that are not trivial. Do not spend time on long lists of trivial items and repetitive descriptions. If in doubt about what is appropriate, speak to your supervisor. +% +%You should also identify any support tools that you used. You should discuss your choice of implementation tools - programming language, compilers, database management system, program development environment, etc. +% +%Some example sub-sections may be as follows, but the specific sections are for you to define. + +\subsection{Overall Architecture} +\begin{figure}[H] +\centering +\includegraphics[width=\textwidth]{HL-Architecture-Diagram} +\caption{High Level Architecture} +\label{fig:high level architecture} +\end{figure} + +\subsection{Detailed design} +\subsubsection{CNN model architecture} +\begin{figure}[H] +\centering +\includegraphics[height=0.5\textwidth]{HL-Diagram-CNN-Simplified} +\caption{Simplified CNN Architecture} +\label{fig:simplified CNN architecture} +\end{figure} +\begin{figure}[H] +\centering +\includegraphics[height=0.9\textheight]{HL-Diagram-CNN} +\caption{CNN Architecture} +\label{fig:detailed CNN architecture} +\end{figure} +\subsubsection{Functions} +\begin{figure}[H] +\centering +\includegraphics[width=\textwidth]{diagrams/filter_paths} +\caption{filter\_paths() function} +\label{fig:2 detailed CNN architecture} +\end{figure} + +\begin{figure}[H] + \centering + \includegraphics[width=\textwidth]{diagrams/load_config} + \caption{load\_config() function} + \label{fig:2 detailed CNN architecture} +\end{figure} + +\begin{figure}[H] +\centering +\includegraphics[width=0.75\textwidth]{diagrams/filter_brightness} +\caption{filter\_brightness() function} +\label{fig:filterbrightness} +\end{figure} + + +\subsection{Datasets} +\paragraph{AVA} +The most common dataset used for analysing image aesthetics is the AVA (Aesthetics Quality Assessment)\cite{ava_paper}. This dataset is comprised of over 250,000 photographs taken from DPChallenge\cite{dpchallenge} including a varied selection of metadata including: a large number of aesthetic ratings from users for each photograph, over 10 photography style labels (macro, rule of thirds, shallow depth of field etc. ), and over 60 semantic lables (landscape, animal, wedding etc.). + +In the paper released alongside the dataset\cite{ava_paper}, it references that the dataset is available at \href{www.lucamarchesotti.com/ava}{www.lucamarchesotti.com/ava}. Although, this link has been down for the past 5 years. To work around this, there are many scripts online which will scrape DPChallenge to build the dataset for you. Others have decided to upload the entire dataset online for quicker access and from preventing users from being rate-limited by DPChallenge.com while scraping. For this project the dataset was downloaded from MEGA (\href{https://mega.nz/folder/9b520Lzb\#2gIa1fgAzr677dcHKxjmtQ}{mega.nz/folder/9b520Lzb\#2gIa1fgAzr677dcHKxjmtQ}) which was provided by a GitHub repository\cite{ava_dataset} which also included AVA download-helper scripts. + +\paragraph{AADB} +Another common dataset is AADB (Aesthetics and Attributes Database)\cite{aadb_paper}. Unlike AVA, AADB uses photos from Flickr\cite{flickr} an image sharing site which is less targeted towards professional photographers and therefore hosts a more varied range of aesthetic quality compared to DPChallenge. Although AADB uses only 10,000 images compared to AVA's 250,000. In AADB, rater identity is anonymously recorded a tracked across different photos which they use in their sampling strategy to contexualize the subjectivity of aesthetic tastes. + +As the project is aimed to help the general public to select high aesthetic quality frames from videos, it may make more sense to use the AADB dataset as it contains more amateur photography compared to AVA. Although, AVA has the advantage of being a larger dataset. Both datasets could be helpful in working with the project. +\section{Implementation} + +%This section should discuss issues you encountered as you tried to implement your experiments. What were the results of running the experiments? What conclusions can you draw from these results? +% +%During the work, you might have found that elements of your experiments were unnecessary or overly complex; perhaps third-party libraries were available that simplified some of the functions that you intended to implement. If things were easier in some areas, then how did you adapt your project to take account of your findings? +% +%It is more likely that things were more complex than you first thought. In particular, were there any problems or difficulties that you found during implementation that you had to address? Did such problems simply delay you or were they more significant? +% +%If you had multiple experiments to run, it may be sensible to discuss each experiment in separate sections. +\subsection{Configuration} +A YAML configuration file\footnote{See example configuration file in Apendix B section \ref{config file}.} was created to enabled quick changes to the filters and pipeline options. YAML was selected as it's a human readable and allows comments unlike JSON. The main options were: +\begin{itemize} +\item \textbf{filters} - declare which filters you want to use, and in which order (default) +\item \textbf{CNNrank} - declare whether you want to rank the remaining images using a CNN (default: False) +\item \textbf{ignore\_video} - declare wether you want to ingore video files when loading in paths (default: False) +\item \textbf{brightness\_options} - declare options for brightness filter +\item \textbf{filesize\_options} - declare options for filesize filter +\item \textbf{contrast\_options} - declare options for contrast filter +\item \textbf{focus\_options} - declare options for focus filter +\end{itemize} + +\subsection{Pipeline} +The overall pipeline takes in a set of paths and will applying image processing in layers to filter the lower aesthetic quality images and thus reducing the set of paths (see figure \ref{fig:high level architecture}). +% video is continuous(wrong word) so you get context + +\begin{itemize} +\item Loads in the video or image +\item Runs through each filter and ouputs a subset of the list of paths +\end{itemize} +\subsection{Filters} +In general, each filter takes in a list of paths and some options (for thresholds etc). The filter will attempt to reduce down the list of paths based on it's filtering technique and threshold. The reasoning behind each filter taking a list of paths as an input was to enable future functionality which would process the frame in context to the other frames. Based on the filter type, some filters will only have a lower bound (e.g discarding filesizes below a certain threshold) while others will include both a lower and higher bound (e.g. discarding images that are too dark or too bright in the brightness filter). +\subsubsection{Filesize} +When comparing file sizes it's safe to assume that larger file sizes contain more information, more information might allude to a more interesting and thus more likely to hold a higher aesthetic quality. When filtering by filesize, only the lower bound is considered. In other words: only filter out images below a certain filesize. To do this, set a threshold and compute the filesize of a given file. If the filesize is lower than the threshold then the image is discarded. +% only has lower bounds +\subsubsection{Brightness} +To quantify an image's brightness the L*a*b* colour space is used. This colour space is meant to reflect human perception of light and colour. In the case where brightness is only concerned, the L (Luminance) channel can be used as a comparable metric to human perception of brightness. To use this effectively, the image is first converted to L*a*b, then the pixel values for the L channel are normalised by dividing each pixels value by the maximum value, then the average of pixel brightness is calculated. This will give us our average luminance of the image. Here brightness should have a lower and upper bound. As some images can be over exposed or under exposed. Both extremes result in poor image quality. Therefore, we can set a percentile band removing the images that land in the extreme upper and lower bounds. + +\subsubsection{Contrast} +To detect contrast an existing function in the skimage\cite{skimage} library called "is\_low\_contrast" method. This method will take an image and a threshold and return true or false depending on if the contrast is above or below the threshold value. Again, like brightness, contrast has lower and upper bounds that need to be removed as an image can have too much contrast or too little. When researching how to calculate an image's contrast levels, the following post was found and followed as a guide\cite{pyis_contrast}. +% has upper and lower bounds +\subsubsection{Focus} +There are a couple of popular methods for detecting if an image is blurry or not. +For detecting blurry images there are two common methods. Laplacian method and fast farrier transform. The laplacian variance method. This method can actually be implemented fairly easily using cv2. You can compute the variance of the laplacian of an image then you can just take the standard deviation squared. A low variance indicates that there aren't many edges in the image, something we can see in blurry pictures. While a high variance means there are a lot of edges and therefore the image is less likely to be blurry. Although this method alone won't allow us to predict if an image with a low depth of field, with a subject is in focus or not as it will just return as "this image is somewhat blurred" which doesn't tell us much. This method works well when you can compute an good level of focus before hand and then you can remove the outliers "(like for a consistent video feed). The following guides were used as a resource for this methods\cite{pyis_laplace}\cite{pyis_fft}. +% only how lower bounds but a bit more complex + +\subsection{CNN} +\subsubsection{CNN architecture} +Originally, the plan was to build a CNN from scratch using PyTorch. This required a lot of research as the CS36220 Machine Learning\cite{ml-module} module didn't cover the details of CNNs nor their practical implementation. To gain a better theory understanding, Stanford University's online lecture material covering deep learning software\cite{stanford_dl} and CNN architecture\cite{stanford_cnn} was used. For practical knowledge several sources PyTorch's official tutorial for training\cite{pytorch-training} and pyimagesearch's guide on training a CNN\cite{pyis-cnn} were used a foundation for understanding the how to use PyTorch -- which is also where the idea of using a separate configuration file for storing variables for batch sizes and validaton splits was inspired from. While attempting to build a CNN, existing CNN approaches\cite{dcnn}\cite{aadb_paper} were researched in detail to build foundational knowledge of how to tackle the shared problem of judging image aesthetic quality. It soon became clear that most sucessful models were using transfer learning instead of building a CNN from scratch. Transfer learning is the process of using the knowledge learned by an existing model and transferring it to a new model which is attempting to solve a similar issue. + +After understanding its benefits, a transfer learning approach to creating a CNN was adopted. This approach was more suited for the project due to the time contraints and the approach's increased probability to create a good working model. + +ResNet50\cite{pytorch-resnet} was chosen as the base model as ResNet based networks have historically performed really well in transfer learning due to their large amounts of hidden layers. The large amount of hidden layers led to it winning all classification and detection competitions in both ILSVRC (ImageNet Large Scale Visual Recognition Challenge) and Microsoft's COCO (Common Objects in Context) in 2015. ResNet50 is a ResNet model with 50 hidden layers (See figure \ref{fig:detailed CNN architecture}) and 1000 different classes. It is trained on the ImageNet\cite{imagenet} dataset, a large dataset comprised of over 14 million annotated images. This dataset is used in ILSVRC as a benchmark for models in classification and object detection. + +Although this project's problem could be implemented as a classficiation problem in the sense of "Is this image of high aesthetic quality?" with two classes "Yes" and "No", we would achieve better insight through a regression-based model asking "How high is the aesthetic quality of this image?" which would return a rating between 0 and 10. To learn specifically how to implement a regression-based model, a couple of guides\cite{pyis_keras_cnn}\cite{pyis_keras} surrouding the building of regression-based models using the real estate dataset\cite{house_dataset}. Transfering the knowledge from the ResNet50 model and altering the model to fit our problem requires a few steps. The pyimagesearch's guide for transfer learning in PyTorch for classification problems\cite{pyis_pytorch_transferlearning} was also used as a guide and much of the structure of the model.py code is inspired by this post. + +\begin{enumerate} +\item Load ResNet50 model +\item Freeze all layers except the last +\item Remove final layer +\item Add a fully connected layer with one output and a relu function +\item Train using new problem data (AVA dataset) +\end{enumerate} +The original plan was to train the two models, once with the AVA dataset and once with the AADB dataset and compare their accuracy. Due to time contrainst and the other aspects of the project being neglected, this had to be dropped and only the AVA dataset was used in the end. + +\subsubsection{Working with the dataset} +The first step to working with the AVA dataset is to load in the data in the format we need it. As the images in AVA were rated from a scale of 1-10 we also want our model to ouput a rating between 1-10. The way AVA exposes these ratings is by showing the count of each rating (see figure \ref{fig: ava-entry}). In other words, for each image it shows you how many users rated the image (1/10, 2/10 etc.). For this project's use-case, these counts of ratings aren't very useful. They need to be processed into a single value. To do this, each rating is given a multipler (a rating of 1 is multiplied by 1, rating of 2 is multiplied by 2 etc.). The sum of all of these new multipied ratings is then dividing by the total number of casted votes. This should give us a single value rating between 1-10 (see figure \ref{fig: calculate_image_rating}). +\begin{figure}[H] +\includegraphics[width=\linewidth]{AVA-entry} +\caption{AVA Dataset entry} +\label{fig: ava-entry} +\end{figure} +\begin{figure}[H] +\includegraphics[width=0.75\linewidth]{calculate_image_rating} +\caption{calculate\_image\_rating() method} +\label{fig: calculate_image_rating} +\end{figure} + +\subsubsection{Training model}\label{Training model} +In order to train the model, PyTorch's in-built training functionality was used. Intially, the model was trained for 20 epochs on the CPU to validate that there weren't any runtime errors. In order to run the training for 20 epochs on a CPU it took just over 4 hours, meaning 2000 epochs would take over 400 hours or roughly 16 and a half days to train on a CPU. In order to speed up processing GPU-compute power was required. PyTorch has long supported using CUDA on Nvidia GPUs for accelerated workloads but has only recently implemented support for AMD's equivalent: ROCm\footnote{As of writing ROCm support for PyTorch is still in beta.}\cite{pytorch-rocm}\cite{rocm-ml}. ROCm also has a lack of installation targets - mostly packaging the stack for enterprise Linux distributions like RHEL (Red Hat Enterprise Linux), SLES (SUSE Linux Enterprise Server), and Ubuntu\footnote{Ubuntu requires the HWE (Hardware Enablement) kernel.}. Fortunately, ROCm is open source, unlike Nvidia's counterpart -- CUDA. This meant that theoretically ROCm could be compiled from source and installed manually. When this was attempted, the machine compiling the package ran out of memory and halted. ROCm was abandonned and the choice to move forward with CUDA was made. As the computer used for the project didn't have an Nvidia GPU, the option of using cloud computing to was explored. + +The next step involved researching a number of cloud providers which offered GPU compute and comparing prices. AWS (Amazon Web Services), the biggest global cloud provider to date, was unrealistically expensive so GCP (Google Cloud Platform), Azure, and Linode were considered instead. Although each of these platforms advertise GPU computer services, each platform has a GPU quota which is automatically locked to zero. This require contacting support to have the restriction lifted or in the case of Linode there's an additionally requirement to have \$100 or more in transactions before asking to remove the lock. After contacting GCP support, the quota for GPUs was increased to one which enabled the CNN model to be trained using Google's cloud GPU compute. + +As part of the project and the drive for creating an optimal development environment, IaC (Infrastructure as Code) was used to rapidly automate deployments of cloud resources, minimising cost and saving time when training. Terraform, a cloud agnostic IaC tool, was used to define the architecture for the cloud resources required to run a training workload. Unexpectedly, working with GCP was harder than expected due to it's novel methods. By default, GCP creates a user account for a newly created server and disables password authentication. Instead, GCP creates an SSH key pair and stores the private key within the GCP platform which isn't viewable by the user. To log in, users have to use the gcloud CLI application which connects to their GCP account which then in turn fetches the private SSH key and automatically logs the user in. Due to this convoluted process, it was difficult to automate the post-installation commands required to set up the training environment. Further issues arised when the decision was made to use Google's official machine learning images which were advertised as ``the easiest way to get started because these images already have the NVIDIA drivers and CUDA libraries pre-installed''\cite{gcp-gpu}. In reality, CUDA was not preinstalled. Instead, an installation script ran on boot which would install the aforementioned drivers and libraries. Unfortunately, Google's script clashed with the project's post-installation script as both of them used apt. This would result in the project's script locking apt when installing it's dependencies, preventing Google's script from using apt to install the drivers. Google's script would then terminate but wrongfully output that the drivers had been installed. + +Around the same time, the university offered access to use their GPU compute cluster on the condition that the project only used one GPU from their old server. The university's GPU compute cluster managed jobs using slurm\cite{slurm} which enqueues an new job to the cluster. The resources on the old server limited it to job very few concurrent jobs, creating a scenario where existing jobs would have to finish before new ones could start. This was ultimately the best option considering it was being provided at no extra cost and the setup wasmuch more straight-forward compared to GCP. + +The university's GPU cluster uses Anaconda\cite{anaconda} virtual environments to run experiements. Once a new environment was created and the depencies for the model training code were installed, a model was able to be trained. This code trained the model for 2000 epochs and saved a plot the train and validation loss. + +To speed up processing time, a batch of the dataset was pre-processed with translations and saved to tensors. This was originally done to speed up runtime troubleshooting in the training code by cutting out the time it took to process the images before each run. + +\section{Testing} +%Detailed descriptions of every test case are definitely not what is required in this section; the place for detailed lists of tests cases is in an appendix. In this section, it is more important to show that you adopted a sensible strategy that was, in principle, capable of testing the system adequately even if you did not have the time to test the system fully. +% +%Provide information in the body of your report and the appendix to explain the testing that has been performed. How does this testing address the requirements and design for the project? +% +%How comprehensive is the testing within the constraints of the project? Are you testing the normal working behaviour? Are you testing the exceptional behaviour, e.g. error conditions? Are you testing security issues if they are relevant for your project? +% +%Have you tested your system on ``real users''? For example, if your system is supposed to solve a problem for a business, then it would be appropriate to present your approach to involve the users in the testing process and to record the results that you obtained. Depending on the level of detail, it is likely that you would put any detailed results in an appendix. +% +%Whilst testing with ``real users'' can be useful, don't see it as a way to shortcut detailed testing of your own. Think about issues discussed in the lectures about until testing, integration testing, etc. User testing without sensible testing of your own is not a useful activity. +% +%The following sections indicate some areas you might include. Other sections may be more appropriate to your project. + +\subsection{Overall Approach to Testing} +Due to the explorative and experimental nature of this project, a lot of code was used temporarily or was CNN based which is difficult to write tests for. Therefore testing was left till the end when the project when there was more structure and finalised pieces. + +\subsection{Automated Testing} +CI/CD pipelines were set up to facilitate automated testing using pytest and pytest's conv plugin which shows a breakdown of test coverage on the codebase. + +\subsubsection{Unit Tests} +Only 4 unit tests were implemented. Three of the tests check the functionality to calculate a single value for the AVA ratings. As a lot of the functions in the this project rely on complex datastructures like panda DataFrames and images testing was quite difficult and the use of mocks was necessary. + +As the "calculate\_image\_rating()" function reads a CSV file and stores it as a dataframe, a mock dataframe had to be created for each test. +\paragraph{test\_calculate\_image\_rating\_with\_no\_ratings} +This test is checking that if all ratings for an image are 0 then the resulting single score would also be zero. This test intially failed and made aware the fact that by following the logic of the algorithm it would try to divide 0 by 0. This caused a runtime error and therefore a specific check had to be put into the function which checked if the summer score equated to 0. If it did, it would avoid diving by the total number of votes and instead just return 0. +\paragraph{test\_calculate\_image\_rating\_multiple\_ratings} +This test will check that the algorithm accurately calculates a single rating value. +\paragraph{test\_calculate\_image\_rating\_incorrect\_number\_of\_columns} +This test checks that the right exception is called when it attempts to calculate the image rating on an entry which has more than 15 columns which is the number of columns an entry had in the AVA dataset. +\paragraph{test\_load\_config\_nonexistent\_file} +This test checks if the right exception is thrown when an non-existent file is attempted to load using the "load\_config()" function in the autophotographer\_main.py script. This test implemented very well as it relies on the filesystem of the user. If the user has a file named "blahblahblah" on their system in the right location then the test will falsely fail. + +\subsection{CNN testing} +When testing the CNN performance, a random small batch of 4 images is selected and then their rating is predicted and plotted. Although as the images are fetched from the validation loader, they are pre-processed which has led to processed images being shown in the reduced size they are scaled down to for training. +\begin{figure}[H] +\centering +\includegraphics[width=0.5\textwidth]{cnn-testing} +\caption{CNN Testing} +\label{fig: cnn testing} +\end{figure} + +As observed in figure \ref{fig: cnn testing}, the CNN isn't very accurate as predicting the aesthetical quality of these images and the variance in prediction/ground truth is quite large between images. + diff --git a/docs/report/FrontMatter/abstract.tex b/docs/report/FrontMatter/abstract.tex new file mode 100755 index 0000000..24a19ec --- /dev/null +++ b/docs/report/FrontMatter/abstract.tex @@ -0,0 +1,15 @@ +\thispagestyle{empty} + +%TC:ignore +\section*{\centering Abstract} + +%Include an abstract for your project. This should be approximately 300 words. +% +%The abstract is an overview of the work you have done. Highlight the purpose of the work and the key outcomes of the work. + +% Why aesthetics is an active research area +% conferences about it etc... + +The goal of the Autophotographer project is to explore the idea of combination of machine learning and convential image processing techniques to select images with a high-level of aesthetic quality. + +%TC:endignore diff --git a/docs/report/FrontMatter/acknowledgements.tex b/docs/report/FrontMatter/acknowledgements.tex new file mode 100755 index 0000000..abe8d86 --- /dev/null +++ b/docs/report/FrontMatter/acknowledgements.tex @@ -0,0 +1,14 @@ +\thispagestyle{empty} + +%TC:ignore + +\section*{\centering Acknowledgements} + +I would like to thank the following people for their support and contributions towards the project: +\begin{itemize} +\item my major project supervisior, Dr Hannah Dee, for helping me keep calm and collected thoughout the project and for keeping me on track. +\item Aberystwyth University and Dave Price for providing me access to the unviersity's GPU compute cluster and providing assistance with using it. +\end{itemize} + + +%TC:endignore diff --git a/docs/report/FrontMatter/cover.tex b/docs/report/FrontMatter/cover.tex new file mode 100755 index 0000000..837959a --- /dev/null +++ b/docs/report/FrontMatter/cover.tex @@ -0,0 +1,32 @@ +%TC:ignore + +\title{Autophotographer} + +% Your name +\author{Oscar Pocock} + +% Your email +\authoremail{osp1@aber.ac.uk} + +\degreeschemecode{G401} %e.g. G400 +\degreeschemetitle{Computer Science (with integrated year in industry)} % e.g. Computer Science +\degreetype{BSc} + +\modulecode{CS39440} % i.e. CS39440, CC39440, CS39620 +\moduletitle{Major Project} % i.e. Major Project or Minor Project + +%\date{19th February 2019} % i.e. the date of the current version of your report +\date{\today} % i.e. the date of the current version of your report + +\status{Release} % Use draft until you create the release version. Then, change this to Release. +\version{1.0} + +% The title and name of your supervisor. +\supervisor{Dr. Hannah Dee} + +%The email for your supervisor. +\supervisoremail{osp1@aber.ac.uk} + +\maketitle + +%TC:endignore diff --git a/docs/report/FrontMatter/declaration.tex b/docs/report/FrontMatter/declaration.tex new file mode 100755 index 0000000..038e395 --- /dev/null +++ b/docs/report/FrontMatter/declaration.tex @@ -0,0 +1,54 @@ +\thispagestyle{empty} + +%TC:ignore + +%%% +%%% You must sign the declaration of originality. +%%% +%%% You are submitting this electronically. Therefore, to sign, you +%%% type your name and date to replace the .... characters. +%%% +\section*{\centering Declaration of originality} + +I confirm that: + +\begin{itemize} +\item{This submission is my own work, except where +clearly indicated.} + +\item{I understand that there are severe penalties for Unacceptable Academic Practice, which can lead to loss of marks or even the withholding of a degree.} + +\item{I have read the regulations on Unacceptable Academic Practice from the University's Academic Registry (AR) and the relevant sections of the current Student Handbook of the Department of Computer Science.} + +\item{In submitting this work I understand and agree to abide by the University's regulations governing these issues.} +\end{itemize} + +\vspace{2em} +Name: Oscar Pocock\\ + +\vspace{1em} +Date: \today \\ + +%%% +%%% We would like to make a selection of final reports available to students that take +%%% this module in future years. To enable us to do this, we require your consent. You +%%% are not required that you do this, but if you do give your consent, then we will have +%%% the option to select yours as one of a number of reports as examples for other +%%% students. If you would like to give your consent, then please include the following +%%% text and type your name and date to replace the .... characters. +%%% +%%% If you do not wish to give your consent, please remove this from your report. +%%% +\vspace{1em} +\section*{\centering Consent to share this work} + +By including my name below, I hereby agree to this project's report and technical work being made available to other students and academic staff of the Aberystwyth Computer Science Department. + +\vspace{2em} +Name: Oscar Pocock\\ + +\vspace{1em} +Date: \today \\ + +%TC:endignore + diff --git a/docs/report/README.md b/docs/report/README.md new file mode 100644 index 0000000..a98845f --- /dev/null +++ b/docs/report/README.md @@ -0,0 +1,40 @@ +# LaTeX Template for MMP Report + +This folder contains a LaTeX template for the project report. + +In a change to previous years, there is one combined template for the Engineering-oriented and Research-oriented projects. The organisation of the files has been simplified to make it easier to maintain this resource. + +## Engineering or Research + +Within `mmp-report.tex`, there is a defintion for `\reporttype`. This can have one of two values: `Engineering` or `Research`. This value is used to determine which of the two `Chapters_x` folders are read, where x is one of `Engineering` or `Research`. + +The intention is that you only use chapters from one of these two directories. They are handled in this way to make it easier to manage the production of the template. If you are doing an engineering-oriented project, then you do not need to keep the research-oriented files. + +## Colours + +The title, chapter and section headings are assigned a blue colour within the template. To control that colour and, if you prefer, remove the colour to simply use the default font colour, you can adjust the setting in `mmp-report.tex`. Look for the comments on `Title and Section Colours`. + +## Style File + +The LaTeX style file is defined in `StylesAndReferences/mmp-report.sty`. Editing this file is for those who are advanced users of LaTeX or the curious who are willing to learn something new. One area you may want to modify is the default choice of font. The document is setup to use `tgheros`, a sans serif font. You may prefer a different font or even a serif font. Look for the `% Fonts` comment in the style file to find the elements to change. + +## Text alignment + +The default text alignment in a LaTeX document is to justify the text. That can cause a problem for some people, such as those with dyslexia. The LaTeX command `\raggedright` has been added to the main report document. + +## References + +The set of example references is contained in the file `StylesAndReferences/references.bib`. This has been manually created but it could easily be something that is generated from a reference management tool such as Mendeley. + +Two example reference styles are provided for in the `mmp-report.tex` file. One is an author-date style (`StylesAndReferences/authordate2annot`) and one is an IEEE style (`StylesAndReferences/IEEEannotU`). + +The two styles are capable of producing annotated references. For projects submitted in 2022, it has been decided that we will not require annotated references. The two style files have been updated to stop the generation of the annotations. + +## Source of help for LaTeX + +The internet is not short of good resources to help you get the most out of LaTeX. One useful resource is hosted by [Overleaf](https://www.overleaf.com/learn/latex/Main_Page), which is also an online LaTeX editor. + +A LaTeX channel is also available on the Discord community server that has been setup for the module. If you have questions about this template, then please ask there and possibly share your experience. To find out how to access the Discord server, see the home page for the module in Bb. + +Neil Taylor +28th February 2022 diff --git a/docs/report/StylesAndReferences/IEEEannot.bst b/docs/report/StylesAndReferences/IEEEannot.bst new file mode 100644 index 0000000..9a9d760 --- /dev/null +++ b/docs/report/StylesAndReferences/IEEEannot.bst @@ -0,0 +1,2655 @@ +%% +%% IEEEannot.bst +%% BibTeX Bibliography Style file +%% Sorting version of IEEEtran.bst +%% *** Not for use with work to be submitted to the IEEE *** +%% Version 1.11 (2003/04/02) +%% +%% Copyright (c) 2003 Michael Shell +%% +%% Modified by Titus Barik (titus@barik.net) to support annotated +%% bibliographies in IEEE citation format. Renamed to IEEEannot.bst. +%% The latest version of IEEEannot can always be downloaded at: +%% +%% http://www.barik.net/sw/ieee/ +%% +%% This version of IEEEannot is: 2004-15-02 +%% +%% Original starting code base and algorithms obtained from the output of +%% Patrick W. Daly's makebst package as well as from prior versions of +%% IEEE BibTeX styles: +%% +%% 1. Howard Trickey and Oren Patashnik's ieeetr.bst (1985/1988) +%% 2. Silvano Balemi and Richard H. Roy's IEEEbib.bst (1993) +%% +%% Added sorting code is from plain.bst. +%% +%% Updated Legal Notice to provide updated URL for Perl Artistic License. +%% 1st March 2017. Neil Taylor (nst@aber.ac.uk) +%% +%% See: +%% http://www.ctan.org/tex-archive/macros/latex/contrib/supported/IEEEtran/ +%% for latest version and current contact information. +%% +%% For use with BibTeX version 0.99a or later +%% +%% This is a numerical citation style. +%% +%%********************************************************************** +%% Legal Notice: +%% This code is offered as-is without any warranty either expressed or +%% implied; without even the implied warranty of MERCHANTABILITY or +%% FITNESS FOR A PARTICULAR PURPOSE! +%% User assumes all risk. +%% In no event shall IEEE or any contributor to this code be liable for +%% any damages or losses, including, but not limited to, incidental, +%% consequential, or any other damages, resulting from the use or misuse +%% of any information contained here. +%% +%% This code is distributed under the Perl Artistic License +%% ( http://dev.perl.org/licenses/artistic.html ) +%% and may be freely used, distributed and modified - subject to the +%% constraints therein. +%% Retain all contribution notices, credits and disclaimers. +%% +%% All comments are the opinions of their respective authors and are not +%% necessarily endorsed by the IEEE. +%%********************************************************************** +% +% +% Changelog: +% +% 1.10 (2002/09/27) Initial release +% +% 1.11 (2003/04/02) +% 1. Fixed bug with URLs containing underscores when using url.sty. Thanks +% to Ming Kin Lai for reporting this. + + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%% DEFAULTS FOR THE CONTROLS OF THE BST STYLE %% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +% These are the defaults for the user adjustable controls. The values used +% here can be overridden by the user via IEEEtranBSTCTL entry type. + +% NOTE: The recommended LaTeX command to invoke a control entry type is: +% +%\makeatletter +%\def\bstctlcite#1{\@bsphack +% \@for\@citeb:=#1\do{% +% \edef\@citeb{\expandafter\@firstofone\@citeb}% +% \if@filesw\immediate\write\@auxout{\string\citation{\@citeb}}\fi}% +% \@esphack} +%\makeatother +% +% It is called at the start of the document, before the first \cite, like: +% \bstctlcite{IEEEexample:BSTcontrol} +% +% IEEEtran.cls V1.6 and later does provide this command. + + + +% #0 turns off the display of the number for articles. +% #1 enables +FUNCTION {default.is.use.number.for.article} { #1 } + + +% #0 turns off the display of the paper and type fields in @inproceedings. +% #1 enables +FUNCTION {default.is.use.paper} { #1 } + + +% #0 turns off the forced use of "et al." +% #1 enables +FUNCTION {default.is.forced.et.al} { #0 } + +% The maximum number of names that can be present beyond which an "et al." +% usage is forced. Be sure that num.names.shown.with.forced.et.al (below) +% is not greater than this value! +% Note: There are many instances of references in IEEE journals which have +% a very large number of authors as well as instances in which "et al." is +% used profusely. +FUNCTION {default.max.num.names.before.forced.et.al} { #10 } + +% The number of names that will be shown with a forced "et al.". +% Must be less than or equal to max.num.names.before.forced.et.al +FUNCTION {default.num.names.shown.with.forced.et.al} { #1 } + + +% #0 turns off the alternate interword spacing for entries with URLs. +% #1 enables +FUNCTION {default.is.use.alt.interword.spacing} { #1 } + +% If alternate interword spacing for entries with URLs is enabled, this is +% the interword spacing stretch factor that will be used. For example, the +% default "4" here means that the interword spacing in entries with URLs can +% stretch to four times normal. Does not have to be an integer. Note that +% the value specified here can be overridden by the user in their LaTeX +% code via a command such as: +% "\providecommand\BIBentryALTinterwordstretchfactor{1.5}" in addition to +% that via the IEEEtranBSTCTL entry type. +FUNCTION {default.ALTinterwordstretchfactor} { "4" } + + +% #0 turns off the "dashification" of repeated (i.e., identical to those +% of the previous entry) names. IEEE normally does this. +% #1 enables +FUNCTION {default.is.dash.repeated.names} { #1 } + + +% The default name format control string. +FUNCTION {default.name.format.string}{ "{f.~}{vv~}{ll}{, jj}" } + + +% The default LaTeX font command for the names. +FUNCTION {default.name.latex.cmd}{ "" } + + +% Other controls that cannot be accessed via IEEEtranBSTCTL entry type. + +% #0 turns off the terminal startup banner/completed message so as to +% operate more quietly. +% #1 enables +FUNCTION {is.print.banners.to.terminal} { #1 } + + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%% FILE VERSION AND BANNER %% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +FUNCTION{bst.file.version} { "1.11" } +FUNCTION{bst.file.date} { "2003/04/02" } +FUNCTION{bst.file.website} { "http://www.ctan.org/tex-archive/macros/latex/contrib/supported/IEEEtran/" } + +FUNCTION {banner.message} +{ is.print.banners.to.terminal + { "-- IEEEtranS.bst version" " " * bst.file.version * + " (" * bst.file.date * ") " * "by Michael Shell." * + top$ + "-- " bst.file.website * + top$ + "-- See the " quote$ * "IEEEtran_bst_HOWTO.pdf" * quote$ * " manual for usage information." * + top$ + "** Sorting version - not for use with work to be submitted to the IEEE." + top$ + } + { skip$ } + if$ +} + +FUNCTION {completed.message} +{ is.print.banners.to.terminal + { "" + top$ + "Done." + top$ + } + { skip$ } + if$ +} + + + + +%%%%%%%%%%%%%%%%%%%%%% +%% STRING CONSTANTS %% +%%%%%%%%%%%%%%%%%%%%%% + +FUNCTION {bbl.and}{ "and" } +FUNCTION {bbl.etal}{ "et~al." } +FUNCTION {bbl.editors}{ "eds." } +FUNCTION {bbl.editor}{ "ed." } +FUNCTION {bbl.edition}{ "ed." } +FUNCTION {bbl.volume}{ "vol." } +FUNCTION {bbl.of}{ "of" } +FUNCTION {bbl.number}{ "no." } +FUNCTION {bbl.in}{ "in" } +FUNCTION {bbl.pages}{ "pp." } +FUNCTION {bbl.page}{ "p." } +FUNCTION {bbl.chapter}{ "ch." } +FUNCTION {bbl.paper}{ "paper" } +FUNCTION {bbl.part}{ "pt." } +FUNCTION {bbl.patent}{ "Patent" } +FUNCTION {bbl.patentUS}{ "U.S." } +FUNCTION {bbl.revision}{ "Rev." } +FUNCTION {bbl.series}{ "ser." } +FUNCTION {bbl.standard}{ "Std." } +FUNCTION {bbl.techrep}{ "Tech. Rep." } +FUNCTION {bbl.mthesis}{ "Master's thesis" } +FUNCTION {bbl.phdthesis}{ "Ph.D. dissertation" } +FUNCTION {bbl.urlprefix}{ "[Online]. Available:" } +FUNCTION {bbl.st}{ "st" } +FUNCTION {bbl.nd}{ "nd" } +FUNCTION {bbl.rd}{ "rd" } +FUNCTION {bbl.th}{ "th" } + + +% This is the LaTeX spacer that is used when a larger than normal space +% is called for (such as just before the address:publisher). +FUNCTION {large.space} { "\hskip 1em plus 0.5em minus 0.4em\relax " } + +% The LaTeX code for dashes that are used to represent repeated names. +% Note: Some older IEEE journals used something like +% "\rule{0.275in}{0.5pt}\," which is fairly thick and runs right along +% the baseline. However, IEEE now uses a thinner, above baseline, +% six dash long sequence. +FUNCTION {repeated.name.dashes} { "------" } + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%% PREDEFINED STRING MACROS %% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +MACRO {jan} {"Jan."} +MACRO {feb} {"Feb."} +MACRO {mar} {"Mar."} +MACRO {apr} {"Apr."} +MACRO {may} {"May"} +MACRO {jun} {"June"} +MACRO {jul} {"July"} +MACRO {aug} {"Aug."} +MACRO {sep} {"Sept."} +MACRO {oct} {"Oct."} +MACRO {nov} {"Nov."} +MACRO {dec} {"Dec."} + + + +%%%%%%%%%%%%%%%%%% +%% ENTRY FIELDS %% +%%%%%%%%%%%%%%%%%% + +ENTRY + { + address + annote + assignee + author + booktitle + chapter + day + dayfiled + edition + editor + howpublished + institution + intype + isbn + journal + key + language + month + monthfiled + nationality + note + number + organization + pages + paper + publisher + school + series + revision + title + type + url + volume + year + yearfiled + CTLuse_article_number + CTLuse_paper + CTLuse_forced_etal + CTLmax_names_forced_etal + CTLnames_show_etal + CTLuse_alt_spacing + CTLalt_stretch_factor + CTLdash_repeated_names + CTLname_format_string + CTLname_latex_cmd + } + {} + { label } + + + + +%%%%%%%%%%%%%%%%%%%%%%% +%% INTEGER VARIABLES %% +%%%%%%%%%%%%%%%%%%%%%%% + +INTEGERS { prev.status.punct this.status.punct punct.std + punct.no punct.comma punct.period + prev.status.space this.status.space space.std + space.no space.normal space.large + prev.status.quote this.status.quote quote.std + quote.no quote.close + prev.status.nline this.status.nline nline.std + nline.no nline.newblock + status.cap cap.std + cap.no cap.yes} + +INTEGERS { longest.label.width multiresult nameptr namesleft number.label numnames } + +INTEGERS { is.use.number.for.article + is.use.paper + is.forced.et.al + max.num.names.before.forced.et.al + num.names.shown.with.forced.et.al + is.use.alt.interword.spacing + is.dash.repeated.names} + + +%%%%%%%%%%%%%%%%%%%%%% +%% STRING VARIABLES %% +%%%%%%%%%%%%%%%%%%%%%% + +STRINGS { bibinfo + longest.label + oldname + s + t + ALTinterwordstretchfactor + name.format.string + name.latex.cmd} + + + + +%%%%%%%%%%%%%%%%%%%%%%%%% +%% LOW LEVEL FUNCTIONS %% +%%%%%%%%%%%%%%%%%%%%%%%%% + +FUNCTION {initialize.controls} +{ default.is.use.number.for.article 'is.use.number.for.article := + default.is.use.paper 'is.use.paper := + default.is.forced.et.al 'is.forced.et.al := + default.max.num.names.before.forced.et.al 'max.num.names.before.forced.et.al := + default.num.names.shown.with.forced.et.al 'num.names.shown.with.forced.et.al := + default.is.use.alt.interword.spacing 'is.use.alt.interword.spacing := + default.is.dash.repeated.names 'is.dash.repeated.names := + default.ALTinterwordstretchfactor 'ALTinterwordstretchfactor := + default.name.format.string 'name.format.string := + default.name.latex.cmd 'name.latex.cmd := +} + + +% This IEEEtran.bst features a very powerful and flexible mechanism for +% controlling the capitalization, punctuation, spacing, quotation, and +% newlines of the formatted entry fields. (Note: IEEEtran.bst does not need +% or use the newline/newblock feature, but it has been implemented for +% possible future use.) The output states of IEEEtran.bst consist of +% multiple independent attributes and, as such, can be thought of as being +% vectors, rather than the simple scalar values ("before.all", +% "mid.sentence", etc.) used in most other .bst files. +% +% The more flexible and complex design used here was motivated in part by +% IEEE's rather unusual bibliography style. For example, IEEE ends the +% previous field item with a period and large space prior to the publisher +% address; the @electronic entry types use periods as inter-item punctuation +% rather than the commas used by the other entry types; and URLs are never +% followed by periods even though they are the last item in the entry. +% Although it is possible to accommodate these features with the conventional +% output state system, the seemingly endless exceptions make for convoluted, +% unreliable and difficult to maintain code. +% +% IEEEtran.bst's output state system can be easily understood via a simple +% illustration of two most recently formatted entry fields (on the stack): +% +% CURRENT_ITEM +% "PREVIOUS_ITEM +% +% which, in this example, is to eventually appear in the bibliography as: +% +% "PREVIOUS_ITEM," CURRENT_ITEM +% +% It is the job of the output routine to take the previous item off of the +% stack (while leaving the current item at the top of the stack), apply its +% trailing punctuation (including closing quote marks) and spacing, and then +% to write the result to BibTeX's output buffer: +% +% "PREVIOUS_ITEM," +% +% Punctuation (and spacing) between items is often determined by both of the +% items rather than just the first one. The presence of quotation marks +% further complicates the situation because, in standard English, trailing +% punctuation marks are supposed to be contained within the quotes. +% +% IEEEtran.bst maintains two output state (aka "status") vectors which +% correspond to the previous and current (aka "this") items. Each vector +% consists of several independent attributes which track punctuation, +% spacing, quotation, and newlines. Capitalization status is handled by a +% separate scalar because the format routines, not the output routine, +% handle capitalization and, therefore, there is no need to maintain the +% capitalization attribute for both the "previous" and "this" items. +% +% When a format routine adds a new item, it copies the current output status +% vector to the previous output status vector and (usually) resets the +% current (this) output status vector to a "standard status" vector. Using a +% "standard status" vector in this way allows us to redefine what we mean by +% "standard status" at the start of each entry handler and reuse the same +% format routines under the various inter-item separation schemes. For +% example, the standard status vector for the @book entry type may use +% commas for item separators, while the @electronic type may use periods, +% yet both entry handlers exploit many of the exact same format routines. +% +% Because format routines have write access to the output status vector of +% the previous item, they can override the punctuation choices of the +% previous format routine! Therefore, it becomes trivial to implement rules +% such as "Always use a period and a large space before the publisher." By +% pushing the generation of the closing quote mark to the output routine, we +% avoid all the problems caused by having to close a quote before having all +% the information required to determine what the punctuation should be. +% +% The IEEEtran.bst output state system can easily be expanded if needed. +% For instance, it is easy to add a "space.tie" attribute value if the +% bibliography rules mandate that two items have to be joined with an +% unbreakable space. + +% Titus Barik Annotation Addition + +% annotation addition +FUNCTION {format.annotate} +{ annote empty$ + { "" } + { " \begin{quotation}\noindent " + annote + * " \end{quotation} " * + } + if$ +} + + +FUNCTION {initialize.status.constants} +{ #0 'punct.no := + #1 'punct.comma := + #2 'punct.period := + #0 'space.no := + #1 'space.normal := + #2 'space.large := + #0 'quote.no := + #1 'quote.close := + #0 'cap.no := + #1 'cap.yes := + #0 'nline.no := + #1 'nline.newblock := +} + +FUNCTION {std.status.using.comma} +{ punct.comma 'punct.std := + space.normal 'space.std := + quote.no 'quote.std := + nline.no 'nline.std := + cap.no 'cap.std := +} + +FUNCTION {std.status.using.period} +{ punct.period 'punct.std := + space.normal 'space.std := + quote.no 'quote.std := + nline.no 'nline.std := + cap.yes 'cap.std := +} + +FUNCTION {initialize.prev.this.status} +{ punct.no 'prev.status.punct := + space.no 'prev.status.space := + quote.no 'prev.status.quote := + nline.no 'prev.status.nline := + punct.no 'this.status.punct := + space.no 'this.status.space := + quote.no 'this.status.quote := + nline.no 'this.status.nline := + cap.yes 'status.cap := +} + +FUNCTION {this.status.std} +{ punct.std 'this.status.punct := + space.std 'this.status.space := + quote.std 'this.status.quote := + nline.std 'this.status.nline := +} + +FUNCTION {cap.status.std}{ cap.std 'status.cap := } + +FUNCTION {this.to.prev.status} +{ this.status.punct 'prev.status.punct := + this.status.space 'prev.status.space := + this.status.quote 'prev.status.quote := + this.status.nline 'prev.status.nline := +} + + +FUNCTION {not} +{ { #0 } + { #1 } + if$ +} + +FUNCTION {and} +{ { skip$ } + { pop$ #0 } + if$ +} + +FUNCTION {or} +{ { pop$ #1 } + { skip$ } + if$ +} + + +% convert the strings "yes" or "no" to #1 or #0 respectively +FUNCTION {yes.no.to.int} +{ "l" change.case$ duplicate$ + "yes" = + { pop$ #1 } + { duplicate$ "no" = + { pop$ #0 } + { "unknown boolean " quote$ * swap$ * quote$ * + " in " * cite$ * warning$ + #0 + } + if$ + } + if$ +} + + +% pushes true if the single char string on the stack is in the +% range of "0" to "9" +FUNCTION {is.num} +{ chr.to.int$ + duplicate$ "0" chr.to.int$ < not + swap$ "9" chr.to.int$ > not and +} + +% multiplies the integer on the stack by a factor of 10 +FUNCTION {bump.int.mag} +{ #0 'multiresult := + { duplicate$ #0 > } + { #1 - + multiresult #10 + + 'multiresult := + } + while$ +pop$ +multiresult +} + +% converts a single character string on the stack to an integer +FUNCTION {char.to.integer} +{ duplicate$ + is.num + { chr.to.int$ "0" chr.to.int$ - } + {"noninteger character " quote$ * swap$ * quote$ * + " in integer field of " * cite$ * warning$ + #0 + } + if$ +} + +% converts a string on the stack to an integer +FUNCTION {string.to.integer} +{ duplicate$ text.length$ 'namesleft := + #1 'nameptr := + #0 'numnames := + { nameptr namesleft > not } + { duplicate$ nameptr #1 substring$ + char.to.integer numnames bump.int.mag + + 'numnames := + nameptr #1 + + 'nameptr := + } + while$ +pop$ +numnames +} + + + + +% The output routines write out the *next* to the top (previous) item on the +% stack, adding punctuation and such as needed. Since IEEEtran.bst maintains +% the output status for the top two items on the stack, these output +% routines have to consider the previous output status (which corresponds to +% the item that is being output). Full independent control of punctuation, +% closing quote marks, spacing, and newblock is provided. +% +% "output.nonnull" does not check for the presence of a previous empty +% item. +% +% "output" does check for the presence of a previous empty item and will +% remove an empty item rather than outputing it. +% +% "output.warn" is like "output", but will issue a warning if it detects +% an empty item. + +FUNCTION {output.nonnull} +{ swap$ + prev.status.punct punct.comma = + { "," * } + { skip$ } + if$ + prev.status.punct punct.period = + { add.period$ } + { skip$ } + if$ + prev.status.quote quote.close = + { "''" * } + { skip$ } + if$ + prev.status.space space.normal = + { " " * } + { skip$ } + if$ + prev.status.space space.large = + { large.space * } + { skip$ } + if$ + write$ + prev.status.nline nline.newblock = + { newline$ "\newblock " write$ } + { skip$ } + if$ +} + +FUNCTION {output} +{ duplicate$ empty$ + 'pop$ + 'output.nonnull + if$ +} + +FUNCTION {output.warn} +{ 't := + duplicate$ empty$ + { pop$ "empty " t * " in " * cite$ * warning$ } + 'output.nonnull + if$ +} + +% "fin.entry" is the output routine that handles the last item of the entry +% (which will be on the top of the stack when "fin.entry" is called). + +FUNCTION {fin.entry} +{ this.status.punct punct.no = + { skip$ } + { add.period$ } + if$ + this.status.quote quote.close = + { "''" * } + { skip$ } + if$ +write$ +newline$ +} + + +FUNCTION {is.last.char.not.punct} +{ duplicate$ + "}" * add.period$ + #-1 #1 substring$ "." = +} + +FUNCTION {is.multiple.pages} +{ 't := + #0 'multiresult := + { multiresult not + t empty$ not + and + } + { t #1 #1 substring$ + duplicate$ "-" = + swap$ duplicate$ "," = + swap$ "+" = + or or + { #1 'multiresult := } + { t #2 global.max$ substring$ 't := } + if$ + } + while$ + + multiresult +} + +FUNCTION {capitalize}{ "u" change.case$ "t" change.case$ } + +FUNCTION {emphasize} +{ duplicate$ empty$ + { pop$ "" } + { "\emph{" swap$ * "}" * } + if$ +} + +FUNCTION {do.name.latex.cmd} +{ name.latex.cmd + empty$ + { skip$ } + { name.latex.cmd "{" * swap$ * "}" * } + if$ +} + +% IEEEtran.bst uses its own \BIBforeignlanguage command which directly +% invokes the TeX hyphenation patterns without the need of the Babel +% package. Babel does a lot more than switch hyphenation patterns and +% its loading can cause unintended effects in many class files (such as +% IEEEtran.cls). +FUNCTION {select.language} +{ duplicate$ empty$ 'pop$ + { language empty$ 'skip$ + { "\BIBforeignlanguage{" language * "}{" * swap$ * "}" * } + if$ + } + if$ +} + +FUNCTION {tie.or.space.prefix} +{ duplicate$ text.length$ #3 < + { "~" } + { " " } + if$ + swap$ +} + +FUNCTION {get.bbl.editor} +{ editor num.names$ #1 > 'bbl.editors 'bbl.editor if$ } + +FUNCTION {space.word}{ " " swap$ * " " * } + + +% Field Conditioners, Converters, Checkers and External Interfaces + +FUNCTION {empty.field.to.null.string} +{ duplicate$ empty$ + { pop$ "" } + { skip$ } + if$ +} + +FUNCTION {either.or.check} +{ empty$ + { pop$ } + { "can't use both " swap$ * " fields in " * cite$ * warning$ } + if$ +} + +FUNCTION {empty.entry.warn} +{ author empty$ title empty$ howpublished empty$ + month empty$ year empty$ note empty$ url empty$ + and and and and and and + { "all relevant fields are empty in " cite$ * warning$ } + 'skip$ + if$ +} + + +% The bibinfo system provides a way for the electronic parsing/acquisition +% of a bibliography's contents as is done by ReVTeX. For example, a field +% could be entered into the bibliography as: +% \bibinfo{volume}{2} +% Only the "2" would show up in the document, but the LaTeX \bibinfo command +% could do additional things with the information. IEEEtran.bst does provide +% a \bibinfo command via "\providecommand{\bibinfo}[2]{#2}". However, it is +% currently not used as the bogus bibinfo functions defined here output the +% entry values directly without the \bibinfo wrapper. The bibinfo functions +% themselves (and the calls to them) are retained for possible future use. +% +% bibinfo.check avoids acting on missing fields while bibinfo.warn will +% issue a warning message if a missing field is detected. Prior to calling +% the bibinfo functions, the user should push the field value and then its +% name string, in that order. + +FUNCTION {bibinfo.check} +{ swap$ duplicate$ missing$ + { pop$ pop$ "" } + { duplicate$ empty$ + { swap$ pop$ } + { swap$ pop$ } + if$ + } + if$ +} + +FUNCTION {bibinfo.warn} +{ swap$ duplicate$ missing$ + { swap$ "missing " swap$ * " in " * cite$ * warning$ pop$ "" } + { duplicate$ empty$ + { swap$ "empty " swap$ * " in " * cite$ * warning$ } + { swap$ pop$ } + if$ + } + if$ +} + + +% IEEE separates large numbers with more than 4 digits into groups of +% three. IEEE uses a small space to separate these number groups. +% Typical applications include patent and page numbers. + +% number of consecutive digits required to trigger the group separation. +FUNCTION {large.number.trigger}{ #5 } + +% For numbers longer than the trigger, this is the blocksize of the groups. +% The blocksize must be less than the trigger threshold, and 2 * blocksize +% must be greater than the trigger threshold (can't do more than one +% separation on the initial trigger). +FUNCTION {large.number.blocksize}{ #3 } + +% What is actually inserted between the number groups. +FUNCTION {large.number.separator}{ "\," } + +% So as to save on integer variables by reusing existing ones, numnames +% holds the current number of consecutive digits read and nameptr holds +% the number that will trigger an inserted space. +FUNCTION {large.number.separate} +{ 't := + "" + #0 'numnames := + large.number.trigger 'nameptr := + { t empty$ not } + { t #-1 #1 substring$ is.num + { numnames #1 + 'numnames := } + { #0 'numnames := + large.number.trigger 'nameptr := + } + if$ + t #-1 #1 substring$ swap$ * + t #-2 global.max$ substring$ 't := + numnames nameptr = + { duplicate$ #1 nameptr large.number.blocksize - substring$ swap$ + nameptr large.number.blocksize - #1 + global.max$ substring$ + large.number.separator swap$ * * + nameptr large.number.blocksize - 'numnames := + large.number.blocksize #1 + 'nameptr := + } + { skip$ } + if$ + } + while$ +} + +% Converts all single dashes "-" to double dashes "--". +FUNCTION {n.dashify} +{ large.number.separate + 't := + "" + { t empty$ not } + { t #1 #1 substring$ "-" = + { t #1 #2 substring$ "--" = not + { "--" * + t #2 global.max$ substring$ 't := + } + { { t #1 #1 substring$ "-" = } + { "-" * + t #2 global.max$ substring$ 't := + } + while$ + } + if$ + } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + if$ + } + while$ +} + + +% This function detects entries with names that are identical to that of +% the previous entry and replaces the repeated names with dashes (if the +% "is.dash.repeated.names" user control is nonzero). +FUNCTION {name.or.dash} +{ 's := + oldname empty$ + { s 'oldname := s } + { s oldname = + { is.dash.repeated.names + { repeated.name.dashes } + { s 'oldname := s } + if$ + } + { s 'oldname := s } + if$ + } + if$ +} + +% Converts the number string on the top of the stack to +% "numerical ordinal form" (e.g., "7" to "7th"). There is +% no artificial limit to the upper bound of the numbers as the +% least significant digit always determines the ordinal form. +FUNCTION {num.to.ordinal} +{ duplicate$ #-1 #1 substring$ "1" = + { bbl.st * } + { duplicate$ #-1 #1 substring$ "2" = + { bbl.nd * } + { duplicate$ #-1 #1 substring$ "3" = + { bbl.rd * } + { bbl.th * } + if$ + } + if$ + } + if$ +} + +% If the string on the top of the stack begins with a number, +% (e.g., 11th) then replace the string with the leading number +% it contains. Otherwise retain the string as-is. s holds the +% extracted number, t holds the part of the string that remains +% to be scanned. +FUNCTION {extract.num} +{ duplicate$ 't := + "" 's := + { t empty$ not } + { t #1 #1 substring$ + t #2 global.max$ substring$ 't := + duplicate$ is.num + { s swap$ * 's := } + { pop$ "" 't := } + if$ + } + while$ + s empty$ + 'skip$ + { pop$ s } + if$ +} + +% Converts the word number string on the top of the stack to +% Arabic string form. Will be successful up to "tenth". +FUNCTION {word.to.num} +{ duplicate$ "l" change.case$ 's := + s "first" = + { pop$ "1" } + { skip$ } + if$ + s "second" = + { pop$ "2" } + { skip$ } + if$ + s "third" = + { pop$ "3" } + { skip$ } + if$ + s "fourth" = + { pop$ "4" } + { skip$ } + if$ + s "fifth" = + { pop$ "5" } + { skip$ } + if$ + s "sixth" = + { pop$ "6" } + { skip$ } + if$ + s "seventh" = + { pop$ "7" } + { skip$ } + if$ + s "eighth" = + { pop$ "8" } + { skip$ } + if$ + s "ninth" = + { pop$ "9" } + { skip$ } + if$ + s "tenth" = + { pop$ "10" } + { skip$ } + if$ +} + + +% Converts the string on the top of the stack to numerical +% ordinal (e.g., "11th") form. +FUNCTION {convert.edition} +{ duplicate$ empty$ 'skip$ + { duplicate$ #1 #1 substring$ is.num + { extract.num + num.to.ordinal + } + { word.to.num + duplicate$ #1 #1 substring$ is.num + { num.to.ordinal } + { "edition ordinal word " quote$ * edition * quote$ * + " may be too high (or improper) for conversion" * " in " * cite$ * warning$ + } + if$ + } + if$ + } + if$ +} + + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%% LATEX BIBLIOGRAPHY CODE %% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +FUNCTION {start.entry} +{ newline$ + "\bibitem{" write$ + cite$ write$ + "}" write$ + newline$ + "" + initialize.prev.this.status +} + +% Here we write out all the LaTeX code that we will need. The most involved +% code sequences are those that control the alternate interword spacing and +% foreign language hyphenation patterns. The heavy use of \providecommand +% gives users a way to override the defaults. Special thanks to Javier Bezos, +% Johannes Braams, Robin Fairburns, Heiko Oberdiek, Donald Arseneau and all +% the other gurus on comp.text.tex for their help and advice on the topic of +% \selectlanguage, Babel and BibTeX. +FUNCTION {begin.bib} +{ preamble$ empty$ 'skip$ + { preamble$ write$ newline$ } + if$ + "\begin{thebibliography}{" longest.label * "}" * + write$ newline$ + "\providecommand{\url}[1]{#1}" + write$ newline$ + "\csname url@rmstyle\endcsname" + write$ newline$ + "\providecommand{\newblock}{\relax}" + write$ newline$ + "\providecommand{\bibinfo}[2]{#2}" + write$ newline$ + "\providecommand\BIBentrySTDinterwordspacing{\spaceskip=0pt\relax}" + write$ newline$ + "\providecommand\BIBentryALTinterwordstretchfactor{" + ALTinterwordstretchfactor * "}" * + write$ newline$ + "\providecommand\BIBentryALTinterwordspacing{\spaceskip=\fontdimen2\font plus " + write$ newline$ + "\BIBentryALTinterwordstretchfactor\fontdimen3\font minus \fontdimen4\font\relax}" + write$ newline$ + "\providecommand\BIBforeignlanguage[2]{{%" + write$ newline$ + "\expandafter\ifx\csname l@#1\endcsname\relax" + write$ newline$ + "\typeout{** WARNING: IEEEtran.bst: No hyphenation pattern has been}%" + write$ newline$ + "\typeout{** loaded for the language `#1'. Using the pattern for}%" + write$ newline$ + "\typeout{** the default language instead.}%" + write$ newline$ + "\else" + write$ newline$ + "\language=\csname l@#1\endcsname" + write$ newline$ + "\fi" + write$ newline$ + "#2}}" + write$ newline$ +} + +FUNCTION {end.bib} +{ newline$ "\end{thebibliography}" write$ newline$ } + +FUNCTION {if.url.alt.interword.spacing} +{ is.use.alt.interword.spacing + {url empty$ 'skip$ {"\BIBentryALTinterwordspacing" write$ newline$} if$} + { skip$ } + if$ +} + +FUNCTION {if.url.std.interword.spacing} +{ is.use.alt.interword.spacing + {url empty$ 'skip$ {"\BIBentrySTDinterwordspacing" write$ newline$} if$} + { skip$ } + if$ +} + + + + +%%%%%%%%%%%%%%%%%%%%%%%% +%% LONGEST LABEL PASS %% +%%%%%%%%%%%%%%%%%%%%%%%% + +FUNCTION {initialize.longest.label} +{ "" 'longest.label := + #1 'number.label := + #0 'longest.label.width := +} + +FUNCTION {longest.label.pass} +{ number.label int.to.str$ 'label := + number.label #1 + 'number.label := + label width$ longest.label.width > + { label 'longest.label := + label width$ 'longest.label.width := + } + 'skip$ + if$ +} + + + + +%%%%%%%%%%%%%%%%%%%%% +%% FORMAT HANDLERS %% +%%%%%%%%%%%%%%%%%%%%% + +%% Lower Level Formats (used by higher level formats) + +FUNCTION {format.address.org.or.pub.date} +{ 't := + "" + year empty$ + { "empty year in " cite$ * warning$ } + { skip$ } + if$ + address empty$ t empty$ and + year empty$ and month empty$ and + { skip$ } + { this.to.prev.status + this.status.std + cap.status.std + address "address" bibinfo.check * + t empty$ + { skip$ } + { punct.period 'prev.status.punct := + space.large 'prev.status.space := + address empty$ + { skip$ } + { ": " * } + if$ + t * + } + if$ + year empty$ month empty$ and + { skip$ } + { t empty$ address empty$ and + { skip$ } + { ", " * } + if$ + month empty$ + { year empty$ + { skip$ } + { year "year" bibinfo.check * } + if$ + } + { month "month" bibinfo.check * + year empty$ + { skip$ } + { " " * year "year" bibinfo.check * } + if$ + } + if$ + } + if$ + } + if$ +} + + +FUNCTION {format.names} +{ 'bibinfo := + duplicate$ empty$ 'skip$ { + this.to.prev.status + this.status.std + 's := + "" 't := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + name.format.string + format.name$ + bibinfo bibinfo.check + 't := + nameptr #1 > + { nameptr num.names.shown.with.forced.et.al #1 + = + numnames max.num.names.before.forced.et.al > + is.forced.et.al and and + { "others" 't := + #1 'namesleft := + } + { skip$ } + if$ + namesleft #1 > + { ", " * t do.name.latex.cmd * } + { + numnames #2 > + { "," * } + 'skip$ + if$ + s nameptr "{ll}" format.name$ duplicate$ "others" = + { 't := } + { pop$ } + if$ + t "others" = + { + " " * bbl.etal emphasize * + } + { + bbl.and + space.word * t do.name.latex.cmd * + } + if$ + } + if$ + } + { t do.name.latex.cmd } + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ + cap.status.std + } if$ +} + + + + +%% Higher Level Formats + +%% addresses/locations + +FUNCTION {format.address} +{ address duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + cap.status.std + } + if$ +} + + + +%% author/editor names + +FUNCTION {format.authors}{ author "author" format.names } + +FUNCTION {format.editors} +{ editor "editor" format.names duplicate$ empty$ 'skip$ + { ", " * + get.bbl.editor + capitalize + * + } + if$ +} + + + +%% date + +FUNCTION {format.date} +{ + month "month" bibinfo.check duplicate$ empty$ + year "year" bibinfo.check duplicate$ empty$ + { swap$ 'skip$ + { this.to.prev.status + this.status.std + cap.status.std + "there's a month but no year in " cite$ * warning$ } + if$ + * + } + { this.to.prev.status + this.status.std + cap.status.std + swap$ 'skip$ + { + swap$ + " " * swap$ + } + if$ + * + } + if$ +} + +FUNCTION {format.date.electronic} +{ month "month" bibinfo.check duplicate$ empty$ + year "year" bibinfo.check duplicate$ empty$ + { swap$ + { pop$ } + { "there's a month but no year in " cite$ * warning$ + pop$ ")" * "(" swap$ * + this.to.prev.status + punct.no 'this.status.punct := + space.normal 'this.status.space := + quote.no 'this.status.quote := + cap.yes 'status.cap := + } + if$ + } + { swap$ + { swap$ pop$ ")" * "(" swap$ * } + { "(" swap$ * ", " * swap$ * ")" * } + if$ + this.to.prev.status + punct.no 'this.status.punct := + space.normal 'this.status.space := + quote.no 'this.status.quote := + cap.yes 'status.cap := + } + if$ +} + + + +%% edition/title + +% Note: IEEE considers the edition to be closely associated with +% the title of a book. So, in IEEEtran.bst the edition is normally handled +% within the formatting of the title. The format.edition function is +% retained here for possible future use. +FUNCTION {format.edition} +{ edition duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + convert.edition + status.cap + { "t" } + { "l" } + if$ change.case$ + "edition" bibinfo.check + "~" * bbl.edition * + cap.status.std + } + if$ +} + +% This is used to format the booktitle of a conference proceedings. +% Here we use the "intype" field to provide the user a way to +% override the word "in" (e.g., with things like "presented at") +% Use of intype stops the emphasis of the booktitle to indicate that +% we no longer mean the written conference proceedings, but the +% conference itself. +FUNCTION {format.in.booktitle} +{ booktitle "booktitle" bibinfo.check duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + select.language + intype missing$ + { emphasize + bbl.in " " * + } + { intype " " * } + if$ + swap$ * + cap.status.std + } + if$ +} + +% This is used to format the booktitle of collection. +% Here the "intype" field is not supported, but "edition" is. +FUNCTION {format.in.booktitle.edition} +{ booktitle "booktitle" bibinfo.check duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + select.language + emphasize + edition empty$ 'skip$ + { ", " * + edition + convert.edition + "l" change.case$ + * "~" * bbl.edition * + } + if$ + bbl.in " " * swap$ * + cap.status.std + } + if$ +} + +FUNCTION {format.article.title} +{ title duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + "t" change.case$ + } + if$ + "title" bibinfo.check + duplicate$ empty$ 'skip$ + { quote.close 'this.status.quote := + is.last.char.not.punct + { punct.std 'this.status.punct := } + { punct.no 'this.status.punct := } + if$ + select.language + "``" swap$ * + cap.status.std + } + if$ +} + +FUNCTION {format.article.title.electronic} +{ title duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + cap.status.std + "t" change.case$ + } + if$ + "title" bibinfo.check + duplicate$ empty$ + { skip$ } + { select.language } + if$ +} + +FUNCTION {format.book.title.edition} +{ title "title" bibinfo.check + duplicate$ empty$ + { "empty title in " cite$ * warning$ } + { this.to.prev.status + this.status.std + select.language + emphasize + edition empty$ 'skip$ + { ", " * + edition + convert.edition + status.cap + { "t" } + { "l" } + if$ + change.case$ + * "~" * bbl.edition * + } + if$ + cap.status.std + } + if$ +} + +FUNCTION {format.book.title} +{ title "title" bibinfo.check + duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + cap.status.std + select.language + emphasize + } + if$ +} + + + +%% journal + +FUNCTION {format.journal} +{ journal duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + cap.status.std + select.language + emphasize + } + if$ +} + + + +%% how published + +FUNCTION {format.howpublished} +{ howpublished duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + cap.status.std + } + if$ +} + + + +%% institutions/organization/publishers/school + +FUNCTION {format.institution} +{ institution duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + cap.status.std + } + if$ +} + +FUNCTION {format.organization} +{ organization duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + cap.status.std + } + if$ +} + +FUNCTION {format.address.publisher.date} +{ publisher "publisher" bibinfo.warn format.address.org.or.pub.date } + +FUNCTION {format.address.publisher.date.nowarn} +{ publisher "publisher" bibinfo.check format.address.org.or.pub.date } + +FUNCTION {format.address.organization.date} +{ organization "organization" bibinfo.check format.address.org.or.pub.date } + +FUNCTION {format.school} +{ school duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + cap.status.std + } + if$ +} + + + +%% volume/number/series/chapter/pages + +FUNCTION {format.volume} +{ volume empty.field.to.null.string + duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + bbl.volume + status.cap + { capitalize } + { skip$ } + if$ + swap$ tie.or.space.prefix + "volume" bibinfo.check + * * + cap.status.std + } + if$ +} + +FUNCTION {format.number} +{ number empty.field.to.null.string + duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + status.cap + { bbl.number capitalize } + { bbl.number } + if$ + swap$ tie.or.space.prefix + "number" bibinfo.check + * * + cap.status.std + } + if$ +} + +FUNCTION {format.number.if.use.for.article} +{ is.use.number.for.article + { format.number } + { "" } + if$ +} + +% IEEE does not seem to tie the series so closely with the volume +% and number as is done in other bibliography styles. Instead the +% series is treated somewhat like an extension of the title. +FUNCTION {format.series} +{ series empty$ + { "" } + { this.to.prev.status + this.status.std + bbl.series " " * + series "series" bibinfo.check * + cap.status.std + } + if$ +} + + +FUNCTION {format.chapter} +{ chapter empty$ + { "" } + { this.to.prev.status + this.status.std + type empty$ + { bbl.chapter } + { type "l" change.case$ + "type" bibinfo.check + } + if$ + chapter tie.or.space.prefix + "chapter" bibinfo.check + * * + cap.status.std + } + if$ +} + + +% The intended use of format.paper is for paper numbers of inproceedings. +% The paper type can be overridden via the type field. +% We allow the type to be displayed even if the paper number is absent +% for things like "postdeadline paper" +FUNCTION {format.paper} +{ is.use.paper + { paper empty$ + { type empty$ + { "" } + { this.to.prev.status + this.status.std + type "type" bibinfo.check + cap.status.std + } + if$ + } + { this.to.prev.status + this.status.std + type empty$ + { bbl.paper } + { type "type" bibinfo.check } + if$ + " " * paper + "paper" bibinfo.check + * + cap.status.std + } + if$ + } + { "" } + if$ +} + + +FUNCTION {format.pages} +{ pages duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + duplicate$ is.multiple.pages + { + bbl.pages swap$ + n.dashify + } + { + bbl.page swap$ + } + if$ + tie.or.space.prefix + "pages" bibinfo.check + * * + cap.status.std + } + if$ +} + + + +%% technical report number + +FUNCTION {format.tech.report.number} +{ number "number" bibinfo.check + type duplicate$ empty$ + { pop$ + this.to.prev.status + this.status.std + cap.status.std + bbl.techrep + } + { skip$ } + if$ + "type" bibinfo.check + swap$ duplicate$ empty$ + { pop$ } + { this.to.prev.status + this.status.std + cap.status.std + tie.or.space.prefix * * } + if$ +} + +%% isbn + +FUNCTION {format.isbn} +{ isbn empty$ + { "" } + { this.to.prev.status + this.status.std + punct.period 'this.status.punct := + isbn #1 #1 substring$ + duplicate$ "{" = + { skip$ } + { status.cap + { "u" } + { "l" } + if$ + change.case$ + } + if$ + isbn #2 global.max$ substring$ * "isbn" bibinfo.check + cap.yes 'status.cap := + } + if$ +} + + +%% note + +FUNCTION {format.note} +{ note empty$ + { "" } + { this.to.prev.status + this.status.std + punct.period 'this.status.punct := + note #1 #1 substring$ + duplicate$ "{" = + { skip$ } + { status.cap + { "u" } + { "l" } + if$ + change.case$ + } + if$ + note #2 global.max$ substring$ * "note" bibinfo.check + cap.yes 'status.cap := + } + if$ +} + + + +%% patent + +FUNCTION {format.patent.date} +{ this.to.prev.status + this.status.std + year empty$ + { monthfiled duplicate$ empty$ + { "monthfiled" bibinfo.check pop$ "" } + { "monthfiled" bibinfo.check } + if$ + dayfiled duplicate$ empty$ + { "dayfiled" bibinfo.check pop$ "" * } + { "dayfiled" bibinfo.check + monthfiled empty$ + { "dayfiled without a monthfiled in " cite$ * warning$ + * + } + { " " swap$ * * } + if$ + } + if$ + yearfiled empty$ + { "no year or yearfiled in " cite$ * warning$ } + { yearfiled "yearfiled" bibinfo.check + swap$ + duplicate$ empty$ + { pop$ } + { ", " * swap$ * } + if$ + } + if$ + } + { month duplicate$ empty$ + { "month" bibinfo.check pop$ "" } + { "month" bibinfo.check } + if$ + day duplicate$ empty$ + { "day" bibinfo.check pop$ "" * } + { "day" bibinfo.check + month empty$ + { "day without a month in " cite$ * warning$ + * + } + { " " swap$ * * } + if$ + } + if$ + year "year" bibinfo.check + swap$ + duplicate$ empty$ + { pop$ } + { ", " * swap$ * } + if$ + } + if$ + cap.status.std +} + +FUNCTION {format.patent.nationality.type.number} +{ this.to.prev.status + this.status.std + nationality duplicate$ empty$ + { "nationality" bibinfo.warn pop$ "" } + { "nationality" bibinfo.check + duplicate$ "l" change.case$ "united states" = + { pop$ bbl.patentUS } + { skip$ } + if$ + " " * + } + if$ + type empty$ + { bbl.patent "type" bibinfo.check } + { type "type" bibinfo.check } + if$ + * + number duplicate$ empty$ + { "number" bibinfo.warn pop$ } + { "number" bibinfo.check + large.number.separate + swap$ " " * swap$ * + } + if$ + cap.status.std +} + + + +%% standard + +FUNCTION {format.organization.institution.standard.type.number} +{ this.to.prev.status + this.status.std + organization duplicate$ empty$ + { pop$ + institution duplicate$ empty$ + { "institution" bibinfo.warn } + { "institution" bibinfo.warn " " * } + if$ + } + { "organization" bibinfo.warn " " * } + if$ + type empty$ + { bbl.standard "type" bibinfo.check } + { type "type" bibinfo.check } + if$ + * + number duplicate$ empty$ + { "number" bibinfo.check pop$ } + { "number" bibinfo.check + large.number.separate + swap$ " " * swap$ * + } + if$ + cap.status.std +} + +FUNCTION {format.revision} +{ revision empty$ + { "" } + { this.to.prev.status + this.status.std + bbl.revision + revision tie.or.space.prefix + "revision" bibinfo.check + * * + cap.status.std + } + if$ +} + + +%% thesis + +FUNCTION {format.master.thesis.type} +{ this.to.prev.status + this.status.std + type empty$ + { + bbl.mthesis + } + { + type "type" bibinfo.check + } + if$ +cap.status.std +} + +FUNCTION {format.phd.thesis.type} +{ this.to.prev.status + this.status.std + type empty$ + { + bbl.phdthesis + } + { + type "type" bibinfo.check + } + if$ +cap.status.std +} + + + +%% URL + +FUNCTION {format.url} +{ url empty$ + { "" } + { this.to.prev.status + this.status.std + cap.yes 'status.cap := + bbl.urlprefix " " * + "\url{" * url * "}" * + punct.no 'this.status.punct := + punct.period 'prev.status.punct := + space.normal 'this.status.space := + space.normal 'prev.status.space := + quote.no 'this.status.quote := + } + if$ +} + + + + +%%%%%%%%%%%%%%%%%%%% +%% ENTRY HANDLERS %% +%%%%%%%%%%%%%%%%%%%% + + +% Note: In many journals, IEEE (or the authors) tend not to show the number +% for articles, so the display of the number is controlled here by the +% switch "is.use.number.for.article" +FUNCTION {article} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors "author" output.warn + name.or.dash + format.article.title "title" output.warn + format.journal "journal" bibinfo.check "journal" output.warn + format.volume output + format.number.if.use.for.article output + format.pages output + format.date "year" output.warn + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation + format.annotate write$ + newline$ +} + +FUNCTION {book} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + author empty$ + { format.editors "author and editor" output.warn } + { format.authors output.nonnull } + if$ + name.or.dash + format.book.title.edition output + format.series output + author empty$ + { skip$ } + { format.editors output } + if$ + format.address.publisher.date output + format.volume output + format.number output + format.pages output + format.note output + format.url output + format.isbn output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation + format.annotate write$ + newline$ +} + +FUNCTION {booklet} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors output + name.or.dash + format.article.title "title" output.warn + format.howpublished "howpublished" bibinfo.check output + format.organization "organization" bibinfo.check output + format.address "address" bibinfo.check output + format.date output + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation + format.annotate write$ + newline$ +} + +FUNCTION {electronic} +{ std.status.using.period + start.entry + if.url.alt.interword.spacing + format.authors output + name.or.dash + format.date.electronic output + format.article.title.electronic output + format.howpublished "howpublished" bibinfo.check output + format.organization "organization" bibinfo.check output + format.address "address" bibinfo.check output + format.note output + format.url output + fin.entry + empty.entry.warn + if.url.std.interword.spacing +% TB: added for annotation + format.annotate write$ + newline$ +} + +FUNCTION {inbook} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + author empty$ + { format.editors "author and editor" output.warn } + { format.authors output.nonnull } + if$ + name.or.dash + format.book.title.edition output + format.series output + format.address.publisher.date output + format.volume output + format.number output + format.chapter output + format.pages output + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation + format.annotate write$ + newline$ +} + +FUNCTION {incollection} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors "author" output.warn + name.or.dash + format.article.title "title" output.warn + format.in.booktitle.edition "booktitle" output.warn + format.series output + format.editors output + format.address.publisher.date.nowarn output + format.volume output + format.number output + format.chapter output + format.pages output + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation + format.annotate write$ + newline$ +} + +FUNCTION {inproceedings} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors "author" output.warn + name.or.dash + format.article.title "title" output.warn + format.in.booktitle "booktitle" output.warn + format.series output + format.editors output + format.volume output + format.number output + publisher empty$ + { format.address.organization.date output } + { format.organization "organization" bibinfo.check output + format.address.publisher.date output + } + if$ + format.paper output + format.pages output + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation + format.annotate write$ + newline$ +} + +FUNCTION {manual} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors output + name.or.dash + format.book.title.edition "title" output.warn + format.howpublished "howpublished" bibinfo.check output + format.organization "organization" bibinfo.check output + format.address "address" bibinfo.check output + format.date output + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation + format.annotate write$ + newline$ +} + +FUNCTION {mastersthesis} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors "author" output.warn + name.or.dash + format.article.title "title" output.warn + format.master.thesis.type output.nonnull + format.school "school" bibinfo.warn output + format.address "address" bibinfo.check output + format.date "year" output.warn + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation + format.annotate write$ + newline$ +} + +FUNCTION {misc} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors output + name.or.dash + format.article.title output + format.howpublished "howpublished" bibinfo.check output + format.organization "organization" bibinfo.check output + format.address "address" bibinfo.check output + format.pages output + format.date output + format.note output + format.url output + fin.entry + empty.entry.warn + if.url.std.interword.spacing +% TB: added for annotation + format.annotate write$ + newline$ +} + +FUNCTION {patent} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors output + name.or.dash + format.article.title output + format.patent.nationality.type.number output + format.patent.date output + format.note output + format.url output + fin.entry + empty.entry.warn + if.url.std.interword.spacing +% TB: added for annotation + format.annotate write$ + newline$ +} + +FUNCTION {periodical} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.editors output + name.or.dash + format.book.title "title" output.warn + format.series output + format.volume output + format.number output + format.organization "organization" bibinfo.check output + format.date "year" output.warn + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation + format.annotate write$ + newline$ +} + +FUNCTION {phdthesis} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors "author" output.warn + name.or.dash + format.article.title "title" output.warn + format.phd.thesis.type output.nonnull + format.school "school" bibinfo.warn output + format.address "address" bibinfo.check output + format.date "year" output.warn + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation + format.annotate write$ + newline$ +} + +FUNCTION {proceedings} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.editors output + name.or.dash + format.book.title "title" output.warn + format.series output + format.volume output + format.number output + publisher empty$ + { format.address.organization.date output } + { format.organization "organization" bibinfo.check output + format.address.publisher.date output + } + if$ + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation + format.annotate write$ + newline$ +} + +FUNCTION {standard} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors output + name.or.dash + format.book.title "title" output.warn + format.howpublished "howpublished" bibinfo.check output + format.organization.institution.standard.type.number output + format.revision output + format.date output + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation + format.annotate write$ + newline$ +} + +FUNCTION {techreport} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors "author" output.warn + name.or.dash + format.article.title "title" output.warn + format.howpublished "howpublished" bibinfo.check output + format.institution "institution" bibinfo.warn output + format.address "address" bibinfo.check output + format.tech.report.number output.nonnull + format.date "year" output.warn + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation + format.annotate write$ + newline$ +} + +FUNCTION {unpublished} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors "author" output.warn + name.or.dash + format.article.title "title" output.warn + format.date output + format.note "note" output.warn + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation + format.annotate write$ + newline$ +} + + +% The special entry type which provides the user interface to the +% BST controls +FUNCTION {IEEEtranBSTCTL} +{ is.print.banners.to.terminal + { "** IEEEtran BST control entry " quote$ * cite$ * quote$ * " detected." * + top$ + } + { skip$ } + if$ + CTLuse_article_number + empty$ + { skip$ } + { CTLuse_article_number + yes.no.to.int + 'is.use.number.for.article := + } + if$ + CTLuse_paper + empty$ + { skip$ } + { CTLuse_paper + yes.no.to.int + 'is.use.paper := + } + if$ + CTLuse_forced_etal + empty$ + { skip$ } + { CTLuse_forced_etal + yes.no.to.int + 'is.forced.et.al := + } + if$ + CTLmax_names_forced_etal + empty$ + { skip$ } + { CTLmax_names_forced_etal + string.to.integer + 'max.num.names.before.forced.et.al := + } + if$ + CTLnames_show_etal + empty$ + { skip$ } + { CTLnames_show_etal + string.to.integer + 'num.names.shown.with.forced.et.al := + } + if$ + CTLuse_alt_spacing + empty$ + { skip$ } + { CTLuse_alt_spacing + yes.no.to.int + 'is.use.alt.interword.spacing := + } + if$ + CTLalt_stretch_factor + empty$ + { skip$ } + { CTLalt_stretch_factor + 'ALTinterwordstretchfactor := + "\renewcommand\BIBentryALTinterwordstretchfactor{" + ALTinterwordstretchfactor * "}" * + write$ newline$ + } + if$ + CTLdash_repeated_names + empty$ + { skip$ } + { CTLdash_repeated_names + yes.no.to.int + 'is.dash.repeated.names := + } + if$ + CTLname_format_string + empty$ + { skip$ } + { CTLname_format_string + 'name.format.string := + } + if$ + CTLname_latex_cmd + empty$ + { skip$ } + { CTLname_latex_cmd + 'name.latex.cmd := + } + if$ + + + num.names.shown.with.forced.et.al max.num.names.before.forced.et.al > + { "CTLnames_show_etal cannot be greater than CTLmax_names_forced_etal in " cite$ * warning$ + max.num.names.before.forced.et.al 'num.names.shown.with.forced.et.al := + } + { skip$ } + if$ +} + + +%%%%%%%%%%%%%%%%%%% +%% ENTRY ALIASES %% +%%%%%%%%%%%%%%%%%%% +FUNCTION {conference}{inproceedings} +FUNCTION {online}{electronic} +FUNCTION {internet}{electronic} +FUNCTION {webpage}{electronic} +FUNCTION {default.type}{misc} + + + +%%%%%%%%%%%%%%%%%% +%% MAIN PROGRAM %% +%%%%%%%%%%%%%%%%%% + +READ + +EXECUTE {initialize.controls} +EXECUTE {initialize.status.constants} +EXECUTE {banner.message} + + + +% BEGIN sort code based on that of plain.bst + +FUNCTION {sortify} +{ purify$ + "l" change.case$ +} + +INTEGERS { len } + +FUNCTION {chop.word} +{ 's := + 'len := + s #1 len substring$ = + { s len #1 + global.max$ substring$ } + { s } + if$ +} + +FUNCTION {sort.format.names} +{ 's := + #1 'nameptr := + "" + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { nameptr #1 > + { " " * } + { skip$ } + if$ + s nameptr "{vv{ } }{ll{ }}{ ff{ }}{ jj{ }}" format.name$ 't := + nameptr numnames = t "others" = and + { "et al" * } + { t sortify * } + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {sort.format.title} +{ 't := + "A " #2 + "An " #3 + "The " #4 t chop.word + chop.word + chop.word + sortify + #1 global.max$ substring$ +} + +FUNCTION {author.sort} +{ author empty$ + { key empty$ + { "to sort, need author or key in " cite$ * warning$ "" } + { key sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.editor.sort} +{ author empty$ + { editor empty$ + { key empty$ + { "to sort, need author, editor, or key in " cite$ * warning$ "" } + { key sortify } + if$ + } + { editor sort.format.names } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.organization.sort} +{ author empty$ + { organization empty$ + { key empty$ + { "to sort, need author, organization, or key in " cite$ * warning$ "" } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {editor.organization.sort} +{ editor empty$ + { organization empty$ + { key empty$ + { "to sort, need editor, organization, or key in " cite$ * warning$ "" } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { editor sort.format.names } + if$ +} + +FUNCTION {author.organization.institution.sort} +{ author empty$ + { organization empty$ + { institution empty$ + { key empty$ + { "to sort, need author, organization, institution or key in " cite$ * warning$ "" } + { key sortify } + if$ + } + { "The " #4 institution chop.word sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { author sort.format.names } + if$ +} + + +FUNCTION {presort} +{ type$ "ieeetranbstctl" = + { key empty$ + { "_" } + { key sortify } + if$ + } + { type$ "book" = + type$ "inbook" = + or + { author.editor.sort } + { type$ "proceedings" = + type$ "periodical" = + or + { editor.organization.sort } + { type$ "manual" = + type$ "electronic" = + type$ "misc" = + or or + { author.organization.sort } + { type$ "standard" = + { author.organization.institution.sort } + { author.sort } + if$ + } + if$ + } + if$ + } + if$ + " " + * + year empty.field.to.null.string sortify + * + " " + * + title empty.field.to.null.string + sort.format.title + * + } + if$ + #1 entry.max$ substring$ + 'sort.key$ := +} + +ITERATE {presort} + +SORT + +% END sort code based on that of plain.bst + + + +EXECUTE {initialize.longest.label} +ITERATE {longest.label.pass} + +EXECUTE {begin.bib} +ITERATE {call.type$} +EXECUTE {end.bib} + +EXECUTE{completed.message} + + +%% That's all folks, mds. diff --git a/docs/report/StylesAndReferences/IEEEannotU.bst b/docs/report/StylesAndReferences/IEEEannotU.bst new file mode 100644 index 0000000..c0562e6 --- /dev/null +++ b/docs/report/StylesAndReferences/IEEEannotU.bst @@ -0,0 +1,2474 @@ +%% +%% IEEEannot.bst +%% BibTeX Bibliography Style file +%% Sorting version of IEEEtran.bst +%% *** Not for use with work to be submitted to the IEEE *** +%% Version 1.2 (2017-02-05) +%% +%% Copyright (c) 2003 Michael Shell +%% +%% Modified by Titus Barik (titus@barik.net) to support annotated +%% bibliographies in IEEE citation format. Renamed to IEEEannot.bst. +%% The latest version of IEEEannot can always be downloaded at: +%% +%% http://www.barik.net/sw/ieee/ +%% +%% Modified by Neil Taylor (nst@aber.ac.uk) to remove the +%% sorting based on plain.bst. Renamed to IEEEannotU (unsorted) +%% This modified version is available at https://github.com/digidol/MMP/ +%% +%% Updated Legal Notice to provide updated URL for Perl Artistic License. +%% 1st March 2017. Neil Taylor (nst@aber.ac.uk) +%% +%% This version of IEEEannot is: 2017-02-05 +%% +%% Original starting code base and algorithms obtained from the output of +%% Patrick W. Daly's makebst package as well as from prior versions of +%% IEEE BibTeX styles: +%% +%% 1. Howard Trickey and Oren Patashnik's ieeetr.bst (1985/1988) +%% 2. Silvano Balemi and Richard H. Roy's IEEEbib.bst (1993) +%% +%% See: +%% http://www.ctan.org/tex-archive/macros/latex/contrib/supported/IEEEtran/ +%% for latest version and current contact information. +%% +%% For use with BibTeX version 0.99a or later +%% +%% This is a numerical citation style. +%% +%%********************************************************************** +%% Legal Notice: +%% This code is offered as-is without any warranty either expressed or +%% implied; without even the implied warranty of MERCHANTABILITY or +%% FITNESS FOR A PARTICULAR PURPOSE! +%% User assumes all risk. +%% In no event shall IEEE or any contributor to this code be liable for +%% any damages or losses, including, but not limited to, incidental, +%% consequential, or any other damages, resulting from the use or misuse +%% of any information contained here. +%% +%% This code is distributed under the Perl Artistic License +%% ( http://dev.perl.org/licenses/artistic.html ) +%% and may be freely used, distributed and modified - subject to the +%% constraints therein. +%% +%% Retain all contribution notices, credits and disclaimers. +%% +%% All comments are the opinions of their respective authors and are not +%% necessarily endorsed by the IEEE. +%%********************************************************************** +% +% Changelog: +% +% 1.10 (2002/09/27) Initial release +% +% 1.11 (2003/04/02) +% 1. Fixed bug with URLs containing underscores when using url.sty. Thanks +% to Ming Kin Lai for reporting this. +% 1.2 (2017-02-05) +% 1. Removed sorting from the template. The items should now appear in +% the normal IEEE order, which is in the order they are first cited. + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%% DEFAULTS FOR THE CONTROLS OF THE BST STYLE %% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +% These are the defaults for the user adjustable controls. The values used +% here can be overridden by the user via IEEEtranBSTCTL entry type. + +% NOTE: The recommended LaTeX command to invoke a control entry type is: +% +%\makeatletter +%\def\bstctlcite#1{\@bsphack +% \@for\@citeb:=#1\do{% +% \edef\@citeb{\expandafter\@firstofone\@citeb}% +% \if@filesw\immediate\write\@auxout{\string\citation{\@citeb}}\fi}% +% \@esphack} +%\makeatother +% +% It is called at the start of the document, before the first \cite, like: +% \bstctlcite{IEEEexample:BSTcontrol} +% +% IEEEtran.cls V1.6 and later does provide this command. + + + +% #0 turns off the display of the number for articles. +% #1 enables +FUNCTION {default.is.use.number.for.article} { #1 } + + +% #0 turns off the display of the paper and type fields in @inproceedings. +% #1 enables +FUNCTION {default.is.use.paper} { #1 } + + +% #0 turns off the forced use of "et al." +% #1 enables +FUNCTION {default.is.forced.et.al} { #0 } + +% The maximum number of names that can be present beyond which an "et al." +% usage is forced. Be sure that num.names.shown.with.forced.et.al (below) +% is not greater than this value! +% Note: There are many instances of references in IEEE journals which have +% a very large number of authors as well as instances in which "et al." is +% used profusely. +FUNCTION {default.max.num.names.before.forced.et.al} { #10 } + +% The number of names that will be shown with a forced "et al.". +% Must be less than or equal to max.num.names.before.forced.et.al +FUNCTION {default.num.names.shown.with.forced.et.al} { #1 } + + +% #0 turns off the alternate interword spacing for entries with URLs. +% #1 enables +FUNCTION {default.is.use.alt.interword.spacing} { #1 } + +% If alternate interword spacing for entries with URLs is enabled, this is +% the interword spacing stretch factor that will be used. For example, the +% default "4" here means that the interword spacing in entries with URLs can +% stretch to four times normal. Does not have to be an integer. Note that +% the value specified here can be overridden by the user in their LaTeX +% code via a command such as: +% "\providecommand\BIBentryALTinterwordstretchfactor{1.5}" in addition to +% that via the IEEEtranBSTCTL entry type. +FUNCTION {default.ALTinterwordstretchfactor} { "4" } + + +% #0 turns off the "dashification" of repeated (i.e., identical to those +% of the previous entry) names. IEEE normally does this. +% #1 enables +FUNCTION {default.is.dash.repeated.names} { #1 } + + +% The default name format control string. +FUNCTION {default.name.format.string}{ "{f.~}{vv~}{ll}{, jj}" } + + +% The default LaTeX font command for the names. +FUNCTION {default.name.latex.cmd}{ "" } + + +% Other controls that cannot be accessed via IEEEtranBSTCTL entry type. + +% #0 turns off the terminal startup banner/completed message so as to +% operate more quietly. +% #1 enables +FUNCTION {is.print.banners.to.terminal} { #1 } + + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%% FILE VERSION AND BANNER %% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +FUNCTION{bst.file.version} { "1.2" } +FUNCTION{bst.file.date} { "2017-02-05" } +FUNCTION{bst.file.website} { "http://www.ctan.org/tex-archive/macros/latex/contrib/supported/IEEEtran/" } + +FUNCTION {banner.message} +{ is.print.banners.to.terminal + { "-- IEEEannotU.bst version" " " * bst.file.version * + " (" * bst.file.date * ") " * "by Neil Taylor, based on work by Michael Shell (IEEEtransS.bst) and Titus Barik (IEEEannot)." * + top$ + "-- " bst.file.website * + top$ + "-- See the " quote$ * "IEEEtran_bst_HOWTO.pdf" * quote$ * " manual for usage information." * + top$ + "** Sorting version - not for use with work to be submitted to the IEEE." + top$ + } + { skip$ } + if$ +} + +FUNCTION {completed.message} +{ is.print.banners.to.terminal + { "" + top$ + "Done." + top$ + } + { skip$ } + if$ +} + + + + +%%%%%%%%%%%%%%%%%%%%%% +%% STRING CONSTANTS %% +%%%%%%%%%%%%%%%%%%%%%% + +FUNCTION {bbl.and}{ "and" } +FUNCTION {bbl.etal}{ "et~al." } +FUNCTION {bbl.editors}{ "eds." } +FUNCTION {bbl.editor}{ "ed." } +FUNCTION {bbl.edition}{ "ed." } +FUNCTION {bbl.volume}{ "vol." } +FUNCTION {bbl.of}{ "of" } +FUNCTION {bbl.number}{ "no." } +FUNCTION {bbl.in}{ "in" } +FUNCTION {bbl.pages}{ "pp." } +FUNCTION {bbl.page}{ "p." } +FUNCTION {bbl.chapter}{ "ch." } +FUNCTION {bbl.paper}{ "paper" } +FUNCTION {bbl.part}{ "pt." } +FUNCTION {bbl.patent}{ "Patent" } +FUNCTION {bbl.patentUS}{ "U.S." } +FUNCTION {bbl.revision}{ "Rev." } +FUNCTION {bbl.series}{ "ser." } +FUNCTION {bbl.standard}{ "Std." } +FUNCTION {bbl.techrep}{ "Tech. Rep." } +FUNCTION {bbl.mthesis}{ "Master's thesis" } +FUNCTION {bbl.phdthesis}{ "Ph.D. dissertation" } +FUNCTION {bbl.urlprefix}{ "[Online]. Available:" } +FUNCTION {bbl.st}{ "st" } +FUNCTION {bbl.nd}{ "nd" } +FUNCTION {bbl.rd}{ "rd" } +FUNCTION {bbl.th}{ "th" } + + +% This is the LaTeX spacer that is used when a larger than normal space +% is called for (such as just before the address:publisher). +FUNCTION {large.space} { "\hskip 1em plus 0.5em minus 0.4em\relax " } + +% The LaTeX code for dashes that are used to represent repeated names. +% Note: Some older IEEE journals used something like +% "\rule{0.275in}{0.5pt}\," which is fairly thick and runs right along +% the baseline. However, IEEE now uses a thinner, above baseline, +% six dash long sequence. +FUNCTION {repeated.name.dashes} { "------" } + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%% PREDEFINED STRING MACROS %% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +MACRO {jan} {"Jan."} +MACRO {feb} {"Feb."} +MACRO {mar} {"Mar."} +MACRO {apr} {"Apr."} +MACRO {may} {"May"} +MACRO {jun} {"June"} +MACRO {jul} {"July"} +MACRO {aug} {"Aug."} +MACRO {sep} {"Sept."} +MACRO {oct} {"Oct."} +MACRO {nov} {"Nov."} +MACRO {dec} {"Dec."} + + + +%%%%%%%%%%%%%%%%%% +%% ENTRY FIELDS %% +%%%%%%%%%%%%%%%%%% + +ENTRY + { + address + annote + assignee + author + booktitle + chapter + day + dayfiled + edition + editor + howpublished + institution + intype + isbn + journal + key + language + month + monthfiled + nationality + note + number + organization + pages + paper + publisher + school + series + revision + title + type + url + volume + year + yearfiled + CTLuse_article_number + CTLuse_paper + CTLuse_forced_etal + CTLmax_names_forced_etal + CTLnames_show_etal + CTLuse_alt_spacing + CTLalt_stretch_factor + CTLdash_repeated_names + CTLname_format_string + CTLname_latex_cmd + } + {} + { label } + + + + +%%%%%%%%%%%%%%%%%%%%%%% +%% INTEGER VARIABLES %% +%%%%%%%%%%%%%%%%%%%%%%% + +INTEGERS { prev.status.punct this.status.punct punct.std + punct.no punct.comma punct.period + prev.status.space this.status.space space.std + space.no space.normal space.large + prev.status.quote this.status.quote quote.std + quote.no quote.close + prev.status.nline this.status.nline nline.std + nline.no nline.newblock + status.cap cap.std + cap.no cap.yes} + +INTEGERS { longest.label.width multiresult nameptr namesleft number.label numnames } + +INTEGERS { is.use.number.for.article + is.use.paper + is.forced.et.al + max.num.names.before.forced.et.al + num.names.shown.with.forced.et.al + is.use.alt.interword.spacing + is.dash.repeated.names} + + +%%%%%%%%%%%%%%%%%%%%%% +%% STRING VARIABLES %% +%%%%%%%%%%%%%%%%%%%%%% + +STRINGS { bibinfo + longest.label + oldname + s + t + ALTinterwordstretchfactor + name.format.string + name.latex.cmd} + + + + +%%%%%%%%%%%%%%%%%%%%%%%%% +%% LOW LEVEL FUNCTIONS %% +%%%%%%%%%%%%%%%%%%%%%%%%% + +FUNCTION {initialize.controls} +{ default.is.use.number.for.article 'is.use.number.for.article := + default.is.use.paper 'is.use.paper := + default.is.forced.et.al 'is.forced.et.al := + default.max.num.names.before.forced.et.al 'max.num.names.before.forced.et.al := + default.num.names.shown.with.forced.et.al 'num.names.shown.with.forced.et.al := + default.is.use.alt.interword.spacing 'is.use.alt.interword.spacing := + default.is.dash.repeated.names 'is.dash.repeated.names := + default.ALTinterwordstretchfactor 'ALTinterwordstretchfactor := + default.name.format.string 'name.format.string := + default.name.latex.cmd 'name.latex.cmd := +} + + +% This IEEEtran.bst features a very powerful and flexible mechanism for +% controlling the capitalization, punctuation, spacing, quotation, and +% newlines of the formatted entry fields. (Note: IEEEtran.bst does not need +% or use the newline/newblock feature, but it has been implemented for +% possible future use.) The output states of IEEEtran.bst consist of +% multiple independent attributes and, as such, can be thought of as being +% vectors, rather than the simple scalar values ("before.all", +% "mid.sentence", etc.) used in most other .bst files. +% +% The more flexible and complex design used here was motivated in part by +% IEEE's rather unusual bibliography style. For example, IEEE ends the +% previous field item with a period and large space prior to the publisher +% address; the @electronic entry types use periods as inter-item punctuation +% rather than the commas used by the other entry types; and URLs are never +% followed by periods even though they are the last item in the entry. +% Although it is possible to accommodate these features with the conventional +% output state system, the seemingly endless exceptions make for convoluted, +% unreliable and difficult to maintain code. +% +% IEEEtran.bst's output state system can be easily understood via a simple +% illustration of two most recently formatted entry fields (on the stack): +% +% CURRENT_ITEM +% "PREVIOUS_ITEM +% +% which, in this example, is to eventually appear in the bibliography as: +% +% "PREVIOUS_ITEM," CURRENT_ITEM +% +% It is the job of the output routine to take the previous item off of the +% stack (while leaving the current item at the top of the stack), apply its +% trailing punctuation (including closing quote marks) and spacing, and then +% to write the result to BibTeX's output buffer: +% +% "PREVIOUS_ITEM," +% +% Punctuation (and spacing) between items is often determined by both of the +% items rather than just the first one. The presence of quotation marks +% further complicates the situation because, in standard English, trailing +% punctuation marks are supposed to be contained within the quotes. +% +% IEEEtran.bst maintains two output state (aka "status") vectors which +% correspond to the previous and current (aka "this") items. Each vector +% consists of several independent attributes which track punctuation, +% spacing, quotation, and newlines. Capitalization status is handled by a +% separate scalar because the format routines, not the output routine, +% handle capitalization and, therefore, there is no need to maintain the +% capitalization attribute for both the "previous" and "this" items. +% +% When a format routine adds a new item, it copies the current output status +% vector to the previous output status vector and (usually) resets the +% current (this) output status vector to a "standard status" vector. Using a +% "standard status" vector in this way allows us to redefine what we mean by +% "standard status" at the start of each entry handler and reuse the same +% format routines under the various inter-item separation schemes. For +% example, the standard status vector for the @book entry type may use +% commas for item separators, while the @electronic type may use periods, +% yet both entry handlers exploit many of the exact same format routines. +% +% Because format routines have write access to the output status vector of +% the previous item, they can override the punctuation choices of the +% previous format routine! Therefore, it becomes trivial to implement rules +% such as "Always use a period and a large space before the publisher." By +% pushing the generation of the closing quote mark to the output routine, we +% avoid all the problems caused by having to close a quote before having all +% the information required to determine what the punctuation should be. +% +% The IEEEtran.bst output state system can easily be expanded if needed. +% For instance, it is easy to add a "space.tie" attribute value if the +% bibliography rules mandate that two items have to be joined with an +% unbreakable space. + +% Titus Barik Annotation Addition + +% annotation addition +FUNCTION {format.annotate} +{ annote empty$ + { "" } + { " \begin{quotation}\noindent " + annote + * " \end{quotation} " * + } + if$ +} + + +FUNCTION {initialize.status.constants} +{ #0 'punct.no := + #1 'punct.comma := + #2 'punct.period := + #0 'space.no := + #1 'space.normal := + #2 'space.large := + #0 'quote.no := + #1 'quote.close := + #0 'cap.no := + #1 'cap.yes := + #0 'nline.no := + #1 'nline.newblock := +} + +FUNCTION {std.status.using.comma} +{ punct.comma 'punct.std := + space.normal 'space.std := + quote.no 'quote.std := + nline.no 'nline.std := + cap.no 'cap.std := +} + +FUNCTION {std.status.using.period} +{ punct.period 'punct.std := + space.normal 'space.std := + quote.no 'quote.std := + nline.no 'nline.std := + cap.yes 'cap.std := +} + +FUNCTION {initialize.prev.this.status} +{ punct.no 'prev.status.punct := + space.no 'prev.status.space := + quote.no 'prev.status.quote := + nline.no 'prev.status.nline := + punct.no 'this.status.punct := + space.no 'this.status.space := + quote.no 'this.status.quote := + nline.no 'this.status.nline := + cap.yes 'status.cap := +} + +FUNCTION {this.status.std} +{ punct.std 'this.status.punct := + space.std 'this.status.space := + quote.std 'this.status.quote := + nline.std 'this.status.nline := +} + +FUNCTION {cap.status.std}{ cap.std 'status.cap := } + +FUNCTION {this.to.prev.status} +{ this.status.punct 'prev.status.punct := + this.status.space 'prev.status.space := + this.status.quote 'prev.status.quote := + this.status.nline 'prev.status.nline := +} + + +FUNCTION {not} +{ { #0 } + { #1 } + if$ +} + +FUNCTION {and} +{ { skip$ } + { pop$ #0 } + if$ +} + +FUNCTION {or} +{ { pop$ #1 } + { skip$ } + if$ +} + + +% convert the strings "yes" or "no" to #1 or #0 respectively +FUNCTION {yes.no.to.int} +{ "l" change.case$ duplicate$ + "yes" = + { pop$ #1 } + { duplicate$ "no" = + { pop$ #0 } + { "unknown boolean " quote$ * swap$ * quote$ * + " in " * cite$ * warning$ + #0 + } + if$ + } + if$ +} + + +% pushes true if the single char string on the stack is in the +% range of "0" to "9" +FUNCTION {is.num} +{ chr.to.int$ + duplicate$ "0" chr.to.int$ < not + swap$ "9" chr.to.int$ > not and +} + +% multiplies the integer on the stack by a factor of 10 +FUNCTION {bump.int.mag} +{ #0 'multiresult := + { duplicate$ #0 > } + { #1 - + multiresult #10 + + 'multiresult := + } + while$ +pop$ +multiresult +} + +% converts a single character string on the stack to an integer +FUNCTION {char.to.integer} +{ duplicate$ + is.num + { chr.to.int$ "0" chr.to.int$ - } + {"noninteger character " quote$ * swap$ * quote$ * + " in integer field of " * cite$ * warning$ + #0 + } + if$ +} + +% converts a string on the stack to an integer +FUNCTION {string.to.integer} +{ duplicate$ text.length$ 'namesleft := + #1 'nameptr := + #0 'numnames := + { nameptr namesleft > not } + { duplicate$ nameptr #1 substring$ + char.to.integer numnames bump.int.mag + + 'numnames := + nameptr #1 + + 'nameptr := + } + while$ +pop$ +numnames +} + + + + +% The output routines write out the *next* to the top (previous) item on the +% stack, adding punctuation and such as needed. Since IEEEtran.bst maintains +% the output status for the top two items on the stack, these output +% routines have to consider the previous output status (which corresponds to +% the item that is being output). Full independent control of punctuation, +% closing quote marks, spacing, and newblock is provided. +% +% "output.nonnull" does not check for the presence of a previous empty +% item. +% +% "output" does check for the presence of a previous empty item and will +% remove an empty item rather than outputing it. +% +% "output.warn" is like "output", but will issue a warning if it detects +% an empty item. + +FUNCTION {output.nonnull} +{ swap$ + prev.status.punct punct.comma = + { "," * } + { skip$ } + if$ + prev.status.punct punct.period = + { add.period$ } + { skip$ } + if$ + prev.status.quote quote.close = + { "''" * } + { skip$ } + if$ + prev.status.space space.normal = + { " " * } + { skip$ } + if$ + prev.status.space space.large = + { large.space * } + { skip$ } + if$ + write$ + prev.status.nline nline.newblock = + { newline$ "\newblock " write$ } + { skip$ } + if$ +} + +FUNCTION {output} +{ duplicate$ empty$ + 'pop$ + 'output.nonnull + if$ +} + +FUNCTION {output.warn} +{ 't := + duplicate$ empty$ + { pop$ "empty " t * " in " * cite$ * warning$ } + 'output.nonnull + if$ +} + +% "fin.entry" is the output routine that handles the last item of the entry +% (which will be on the top of the stack when "fin.entry" is called). + +FUNCTION {fin.entry} +{ this.status.punct punct.no = + { skip$ } + { add.period$ } + if$ + this.status.quote quote.close = + { "''" * } + { skip$ } + if$ +write$ +newline$ +} + + +FUNCTION {is.last.char.not.punct} +{ duplicate$ + "}" * add.period$ + #-1 #1 substring$ "." = +} + +FUNCTION {is.multiple.pages} +{ 't := + #0 'multiresult := + { multiresult not + t empty$ not + and + } + { t #1 #1 substring$ + duplicate$ "-" = + swap$ duplicate$ "," = + swap$ "+" = + or or + { #1 'multiresult := } + { t #2 global.max$ substring$ 't := } + if$ + } + while$ + + multiresult +} + +FUNCTION {capitalize}{ "u" change.case$ "t" change.case$ } + +FUNCTION {emphasize} +{ duplicate$ empty$ + { pop$ "" } + { "\emph{" swap$ * "}" * } + if$ +} + +FUNCTION {do.name.latex.cmd} +{ name.latex.cmd + empty$ + { skip$ } + { name.latex.cmd "{" * swap$ * "}" * } + if$ +} + +% IEEEtran.bst uses its own \BIBforeignlanguage command which directly +% invokes the TeX hyphenation patterns without the need of the Babel +% package. Babel does a lot more than switch hyphenation patterns and +% its loading can cause unintended effects in many class files (such as +% IEEEtran.cls). +FUNCTION {select.language} +{ duplicate$ empty$ 'pop$ + { language empty$ 'skip$ + { "\BIBforeignlanguage{" language * "}{" * swap$ * "}" * } + if$ + } + if$ +} + +FUNCTION {tie.or.space.prefix} +{ duplicate$ text.length$ #3 < + { "~" } + { " " } + if$ + swap$ +} + +FUNCTION {get.bbl.editor} +{ editor num.names$ #1 > 'bbl.editors 'bbl.editor if$ } + +FUNCTION {space.word}{ " " swap$ * " " * } + + +% Field Conditioners, Converters, Checkers and External Interfaces + +FUNCTION {empty.field.to.null.string} +{ duplicate$ empty$ + { pop$ "" } + { skip$ } + if$ +} + +FUNCTION {either.or.check} +{ empty$ + { pop$ } + { "can't use both " swap$ * " fields in " * cite$ * warning$ } + if$ +} + +FUNCTION {empty.entry.warn} +{ author empty$ title empty$ howpublished empty$ + month empty$ year empty$ note empty$ url empty$ + and and and and and and + { "all relevant fields are empty in " cite$ * warning$ } + 'skip$ + if$ +} + + +% The bibinfo system provides a way for the electronic parsing/acquisition +% of a bibliography's contents as is done by ReVTeX. For example, a field +% could be entered into the bibliography as: +% \bibinfo{volume}{2} +% Only the "2" would show up in the document, but the LaTeX \bibinfo command +% could do additional things with the information. IEEEtran.bst does provide +% a \bibinfo command via "\providecommand{\bibinfo}[2]{#2}". However, it is +% currently not used as the bogus bibinfo functions defined here output the +% entry values directly without the \bibinfo wrapper. The bibinfo functions +% themselves (and the calls to them) are retained for possible future use. +% +% bibinfo.check avoids acting on missing fields while bibinfo.warn will +% issue a warning message if a missing field is detected. Prior to calling +% the bibinfo functions, the user should push the field value and then its +% name string, in that order. + +FUNCTION {bibinfo.check} +{ swap$ duplicate$ missing$ + { pop$ pop$ "" } + { duplicate$ empty$ + { swap$ pop$ } + { swap$ pop$ } + if$ + } + if$ +} + +FUNCTION {bibinfo.warn} +{ swap$ duplicate$ missing$ + { swap$ "missing " swap$ * " in " * cite$ * warning$ pop$ "" } + { duplicate$ empty$ + { swap$ "empty " swap$ * " in " * cite$ * warning$ } + { swap$ pop$ } + if$ + } + if$ +} + + +% IEEE separates large numbers with more than 4 digits into groups of +% three. IEEE uses a small space to separate these number groups. +% Typical applications include patent and page numbers. + +% number of consecutive digits required to trigger the group separation. +FUNCTION {large.number.trigger}{ #5 } + +% For numbers longer than the trigger, this is the blocksize of the groups. +% The blocksize must be less than the trigger threshold, and 2 * blocksize +% must be greater than the trigger threshold (can't do more than one +% separation on the initial trigger). +FUNCTION {large.number.blocksize}{ #3 } + +% What is actually inserted between the number groups. +FUNCTION {large.number.separator}{ "\," } + +% So as to save on integer variables by reusing existing ones, numnames +% holds the current number of consecutive digits read and nameptr holds +% the number that will trigger an inserted space. +FUNCTION {large.number.separate} +{ 't := + "" + #0 'numnames := + large.number.trigger 'nameptr := + { t empty$ not } + { t #-1 #1 substring$ is.num + { numnames #1 + 'numnames := } + { #0 'numnames := + large.number.trigger 'nameptr := + } + if$ + t #-1 #1 substring$ swap$ * + t #-2 global.max$ substring$ 't := + numnames nameptr = + { duplicate$ #1 nameptr large.number.blocksize - substring$ swap$ + nameptr large.number.blocksize - #1 + global.max$ substring$ + large.number.separator swap$ * * + nameptr large.number.blocksize - 'numnames := + large.number.blocksize #1 + 'nameptr := + } + { skip$ } + if$ + } + while$ +} + +% Converts all single dashes "-" to double dashes "--". +FUNCTION {n.dashify} +{ large.number.separate + 't := + "" + { t empty$ not } + { t #1 #1 substring$ "-" = + { t #1 #2 substring$ "--" = not + { "--" * + t #2 global.max$ substring$ 't := + } + { { t #1 #1 substring$ "-" = } + { "-" * + t #2 global.max$ substring$ 't := + } + while$ + } + if$ + } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + if$ + } + while$ +} + + +% This function detects entries with names that are identical to that of +% the previous entry and replaces the repeated names with dashes (if the +% "is.dash.repeated.names" user control is nonzero). +FUNCTION {name.or.dash} +{ 's := + oldname empty$ + { s 'oldname := s } + { s oldname = + { is.dash.repeated.names + { repeated.name.dashes } + { s 'oldname := s } + if$ + } + { s 'oldname := s } + if$ + } + if$ +} + +% Converts the number string on the top of the stack to +% "numerical ordinal form" (e.g., "7" to "7th"). There is +% no artificial limit to the upper bound of the numbers as the +% least significant digit always determines the ordinal form. +FUNCTION {num.to.ordinal} +{ duplicate$ #-1 #1 substring$ "1" = + { bbl.st * } + { duplicate$ #-1 #1 substring$ "2" = + { bbl.nd * } + { duplicate$ #-1 #1 substring$ "3" = + { bbl.rd * } + { bbl.th * } + if$ + } + if$ + } + if$ +} + +% If the string on the top of the stack begins with a number, +% (e.g., 11th) then replace the string with the leading number +% it contains. Otherwise retain the string as-is. s holds the +% extracted number, t holds the part of the string that remains +% to be scanned. +FUNCTION {extract.num} +{ duplicate$ 't := + "" 's := + { t empty$ not } + { t #1 #1 substring$ + t #2 global.max$ substring$ 't := + duplicate$ is.num + { s swap$ * 's := } + { pop$ "" 't := } + if$ + } + while$ + s empty$ + 'skip$ + { pop$ s } + if$ +} + +% Converts the word number string on the top of the stack to +% Arabic string form. Will be successful up to "tenth". +FUNCTION {word.to.num} +{ duplicate$ "l" change.case$ 's := + s "first" = + { pop$ "1" } + { skip$ } + if$ + s "second" = + { pop$ "2" } + { skip$ } + if$ + s "third" = + { pop$ "3" } + { skip$ } + if$ + s "fourth" = + { pop$ "4" } + { skip$ } + if$ + s "fifth" = + { pop$ "5" } + { skip$ } + if$ + s "sixth" = + { pop$ "6" } + { skip$ } + if$ + s "seventh" = + { pop$ "7" } + { skip$ } + if$ + s "eighth" = + { pop$ "8" } + { skip$ } + if$ + s "ninth" = + { pop$ "9" } + { skip$ } + if$ + s "tenth" = + { pop$ "10" } + { skip$ } + if$ +} + + +% Converts the string on the top of the stack to numerical +% ordinal (e.g., "11th") form. +FUNCTION {convert.edition} +{ duplicate$ empty$ 'skip$ + { duplicate$ #1 #1 substring$ is.num + { extract.num + num.to.ordinal + } + { word.to.num + duplicate$ #1 #1 substring$ is.num + { num.to.ordinal } + { "edition ordinal word " quote$ * edition * quote$ * + " may be too high (or improper) for conversion" * " in " * cite$ * warning$ + } + if$ + } + if$ + } + if$ +} + + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%% LATEX BIBLIOGRAPHY CODE %% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +FUNCTION {start.entry} +{ newline$ + "\bibitem{" write$ + cite$ write$ + "}" write$ + newline$ + "" + initialize.prev.this.status +} + +% Here we write out all the LaTeX code that we will need. The most involved +% code sequences are those that control the alternate interword spacing and +% foreign language hyphenation patterns. The heavy use of \providecommand +% gives users a way to override the defaults. Special thanks to Javier Bezos, +% Johannes Braams, Robin Fairburns, Heiko Oberdiek, Donald Arseneau and all +% the other gurus on comp.text.tex for their help and advice on the topic of +% \selectlanguage, Babel and BibTeX. +FUNCTION {begin.bib} +{ preamble$ empty$ 'skip$ + { preamble$ write$ newline$ } + if$ + "\begin{thebibliography}{" longest.label * "}" * + write$ newline$ + "\providecommand{\url}[1]{#1}" + write$ newline$ + "\csname url@rmstyle\endcsname" + write$ newline$ + "\providecommand{\newblock}{\relax}" + write$ newline$ + "\providecommand{\bibinfo}[2]{#2}" + write$ newline$ + "\providecommand\BIBentrySTDinterwordspacing{\spaceskip=0pt\relax}" + write$ newline$ + "\providecommand\BIBentryALTinterwordstretchfactor{" + ALTinterwordstretchfactor * "}" * + write$ newline$ + "\providecommand\BIBentryALTinterwordspacing{\spaceskip=\fontdimen2\font plus " + write$ newline$ + "\BIBentryALTinterwordstretchfactor\fontdimen3\font minus \fontdimen4\font\relax}" + write$ newline$ + "\providecommand\BIBforeignlanguage[2]{{%" + write$ newline$ + "\expandafter\ifx\csname l@#1\endcsname\relax" + write$ newline$ + "\typeout{** WARNING: IEEEtran.bst: No hyphenation pattern has been}%" + write$ newline$ + "\typeout{** loaded for the language `#1'. Using the pattern for}%" + write$ newline$ + "\typeout{** the default language instead.}%" + write$ newline$ + "\else" + write$ newline$ + "\language=\csname l@#1\endcsname" + write$ newline$ + "\fi" + write$ newline$ + "#2}}" + write$ newline$ +} + +FUNCTION {end.bib} +{ newline$ "\end{thebibliography}" write$ newline$ } + +FUNCTION {if.url.alt.interword.spacing} +{ is.use.alt.interword.spacing + {url empty$ 'skip$ {"\BIBentryALTinterwordspacing" write$ newline$} if$} + { skip$ } + if$ +} + +FUNCTION {if.url.std.interword.spacing} +{ is.use.alt.interword.spacing + {url empty$ 'skip$ {"\BIBentrySTDinterwordspacing" write$ newline$} if$} + { skip$ } + if$ +} + + + + +%%%%%%%%%%%%%%%%%%%%%%%% +%% LONGEST LABEL PASS %% +%%%%%%%%%%%%%%%%%%%%%%%% + +FUNCTION {initialize.longest.label} +{ "" 'longest.label := + #1 'number.label := + #0 'longest.label.width := +} + +FUNCTION {longest.label.pass} +{ number.label int.to.str$ 'label := + number.label #1 + 'number.label := + label width$ longest.label.width > + { label 'longest.label := + label width$ 'longest.label.width := + } + 'skip$ + if$ +} + + + + +%%%%%%%%%%%%%%%%%%%%% +%% FORMAT HANDLERS %% +%%%%%%%%%%%%%%%%%%%%% + +%% Lower Level Formats (used by higher level formats) + +FUNCTION {format.address.org.or.pub.date} +{ 't := + "" + year empty$ + { "empty year in " cite$ * warning$ } + { skip$ } + if$ + address empty$ t empty$ and + year empty$ and month empty$ and + { skip$ } + { this.to.prev.status + this.status.std + cap.status.std + address "address" bibinfo.check * + t empty$ + { skip$ } + { punct.period 'prev.status.punct := + space.large 'prev.status.space := + address empty$ + { skip$ } + { ": " * } + if$ + t * + } + if$ + year empty$ month empty$ and + { skip$ } + { t empty$ address empty$ and + { skip$ } + { ", " * } + if$ + month empty$ + { year empty$ + { skip$ } + { year "year" bibinfo.check * } + if$ + } + { month "month" bibinfo.check * + year empty$ + { skip$ } + { " " * year "year" bibinfo.check * } + if$ + } + if$ + } + if$ + } + if$ +} + + +FUNCTION {format.names} +{ 'bibinfo := + duplicate$ empty$ 'skip$ { + this.to.prev.status + this.status.std + 's := + "" 't := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + name.format.string + format.name$ + bibinfo bibinfo.check + 't := + nameptr #1 > + { nameptr num.names.shown.with.forced.et.al #1 + = + numnames max.num.names.before.forced.et.al > + is.forced.et.al and and + { "others" 't := + #1 'namesleft := + } + { skip$ } + if$ + namesleft #1 > + { ", " * t do.name.latex.cmd * } + { + numnames #2 > + { "," * } + 'skip$ + if$ + s nameptr "{ll}" format.name$ duplicate$ "others" = + { 't := } + { pop$ } + if$ + t "others" = + { + " " * bbl.etal emphasize * + } + { + bbl.and + space.word * t do.name.latex.cmd * + } + if$ + } + if$ + } + { t do.name.latex.cmd } + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ + cap.status.std + } if$ +} + + + + +%% Higher Level Formats + +%% addresses/locations + +FUNCTION {format.address} +{ address duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + cap.status.std + } + if$ +} + + + +%% author/editor names + +FUNCTION {format.authors}{ author "author" format.names } + +FUNCTION {format.editors} +{ editor "editor" format.names duplicate$ empty$ 'skip$ + { ", " * + get.bbl.editor + capitalize + * + } + if$ +} + + + +%% date + +FUNCTION {format.date} +{ + month "month" bibinfo.check duplicate$ empty$ + year "year" bibinfo.check duplicate$ empty$ + { swap$ 'skip$ + { this.to.prev.status + this.status.std + cap.status.std + "there's a month but no year in " cite$ * warning$ } + if$ + * + } + { this.to.prev.status + this.status.std + cap.status.std + swap$ 'skip$ + { + swap$ + " " * swap$ + } + if$ + * + } + if$ +} + +FUNCTION {format.date.electronic} +{ month "month" bibinfo.check duplicate$ empty$ + year "year" bibinfo.check duplicate$ empty$ + { swap$ + { pop$ } + { "there's a month but no year in " cite$ * warning$ + pop$ ")" * "(" swap$ * + this.to.prev.status + punct.no 'this.status.punct := + space.normal 'this.status.space := + quote.no 'this.status.quote := + cap.yes 'status.cap := + } + if$ + } + { swap$ + { swap$ pop$ ")" * "(" swap$ * } + { "(" swap$ * ", " * swap$ * ")" * } + if$ + this.to.prev.status + punct.no 'this.status.punct := + space.normal 'this.status.space := + quote.no 'this.status.quote := + cap.yes 'status.cap := + } + if$ +} + + + +%% edition/title + +% Note: IEEE considers the edition to be closely associated with +% the title of a book. So, in IEEEtran.bst the edition is normally handled +% within the formatting of the title. The format.edition function is +% retained here for possible future use. +FUNCTION {format.edition} +{ edition duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + convert.edition + status.cap + { "t" } + { "l" } + if$ change.case$ + "edition" bibinfo.check + "~" * bbl.edition * + cap.status.std + } + if$ +} + +% This is used to format the booktitle of a conference proceedings. +% Here we use the "intype" field to provide the user a way to +% override the word "in" (e.g., with things like "presented at") +% Use of intype stops the emphasis of the booktitle to indicate that +% we no longer mean the written conference proceedings, but the +% conference itself. +FUNCTION {format.in.booktitle} +{ booktitle "booktitle" bibinfo.check duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + select.language + intype missing$ + { emphasize + bbl.in " " * + } + { intype " " * } + if$ + swap$ * + cap.status.std + } + if$ +} + +% This is used to format the booktitle of collection. +% Here the "intype" field is not supported, but "edition" is. +FUNCTION {format.in.booktitle.edition} +{ booktitle "booktitle" bibinfo.check duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + select.language + emphasize + edition empty$ 'skip$ + { ", " * + edition + convert.edition + "l" change.case$ + * "~" * bbl.edition * + } + if$ + bbl.in " " * swap$ * + cap.status.std + } + if$ +} + +FUNCTION {format.article.title} +{ title duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + "t" change.case$ + } + if$ + "title" bibinfo.check + duplicate$ empty$ 'skip$ + { quote.close 'this.status.quote := + is.last.char.not.punct + { punct.std 'this.status.punct := } + { punct.no 'this.status.punct := } + if$ + select.language + "``" swap$ * + cap.status.std + } + if$ +} + +FUNCTION {format.article.title.electronic} +{ title duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + cap.status.std + "t" change.case$ + } + if$ + "title" bibinfo.check + duplicate$ empty$ + { skip$ } + { select.language } + if$ +} + +FUNCTION {format.book.title.edition} +{ title "title" bibinfo.check + duplicate$ empty$ + { "empty title in " cite$ * warning$ } + { this.to.prev.status + this.status.std + select.language + emphasize + edition empty$ 'skip$ + { ", " * + edition + convert.edition + status.cap + { "t" } + { "l" } + if$ + change.case$ + * "~" * bbl.edition * + } + if$ + cap.status.std + } + if$ +} + +FUNCTION {format.book.title} +{ title "title" bibinfo.check + duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + cap.status.std + select.language + emphasize + } + if$ +} + + + +%% journal + +FUNCTION {format.journal} +{ journal duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + cap.status.std + select.language + emphasize + } + if$ +} + + + +%% how published + +FUNCTION {format.howpublished} +{ howpublished duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + cap.status.std + } + if$ +} + + + +%% institutions/organization/publishers/school + +FUNCTION {format.institution} +{ institution duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + cap.status.std + } + if$ +} + +FUNCTION {format.organization} +{ organization duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + cap.status.std + } + if$ +} + +FUNCTION {format.address.publisher.date} +{ publisher "publisher" bibinfo.warn format.address.org.or.pub.date } + +FUNCTION {format.address.publisher.date.nowarn} +{ publisher "publisher" bibinfo.check format.address.org.or.pub.date } + +FUNCTION {format.address.organization.date} +{ organization "organization" bibinfo.check format.address.org.or.pub.date } + +FUNCTION {format.school} +{ school duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + cap.status.std + } + if$ +} + + + +%% volume/number/series/chapter/pages + +FUNCTION {format.volume} +{ volume empty.field.to.null.string + duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + bbl.volume + status.cap + { capitalize } + { skip$ } + if$ + swap$ tie.or.space.prefix + "volume" bibinfo.check + * * + cap.status.std + } + if$ +} + +FUNCTION {format.number} +{ number empty.field.to.null.string + duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + status.cap + { bbl.number capitalize } + { bbl.number } + if$ + swap$ tie.or.space.prefix + "number" bibinfo.check + * * + cap.status.std + } + if$ +} + +FUNCTION {format.number.if.use.for.article} +{ is.use.number.for.article + { format.number } + { "" } + if$ +} + +% IEEE does not seem to tie the series so closely with the volume +% and number as is done in other bibliography styles. Instead the +% series is treated somewhat like an extension of the title. +FUNCTION {format.series} +{ series empty$ + { "" } + { this.to.prev.status + this.status.std + bbl.series " " * + series "series" bibinfo.check * + cap.status.std + } + if$ +} + + +FUNCTION {format.chapter} +{ chapter empty$ + { "" } + { this.to.prev.status + this.status.std + type empty$ + { bbl.chapter } + { type "l" change.case$ + "type" bibinfo.check + } + if$ + chapter tie.or.space.prefix + "chapter" bibinfo.check + * * + cap.status.std + } + if$ +} + + +% The intended use of format.paper is for paper numbers of inproceedings. +% The paper type can be overridden via the type field. +% We allow the type to be displayed even if the paper number is absent +% for things like "postdeadline paper" +FUNCTION {format.paper} +{ is.use.paper + { paper empty$ + { type empty$ + { "" } + { this.to.prev.status + this.status.std + type "type" bibinfo.check + cap.status.std + } + if$ + } + { this.to.prev.status + this.status.std + type empty$ + { bbl.paper } + { type "type" bibinfo.check } + if$ + " " * paper + "paper" bibinfo.check + * + cap.status.std + } + if$ + } + { "" } + if$ +} + + +FUNCTION {format.pages} +{ pages duplicate$ empty$ 'skip$ + { this.to.prev.status + this.status.std + duplicate$ is.multiple.pages + { + bbl.pages swap$ + n.dashify + } + { + bbl.page swap$ + } + if$ + tie.or.space.prefix + "pages" bibinfo.check + * * + cap.status.std + } + if$ +} + + + +%% technical report number + +FUNCTION {format.tech.report.number} +{ number "number" bibinfo.check + type duplicate$ empty$ + { pop$ + this.to.prev.status + this.status.std + cap.status.std + bbl.techrep + } + { skip$ } + if$ + "type" bibinfo.check + swap$ duplicate$ empty$ + { pop$ } + { this.to.prev.status + this.status.std + cap.status.std + tie.or.space.prefix * * } + if$ +} + +%% isbn + +FUNCTION {format.isbn} +{ isbn empty$ + { "" } + { this.to.prev.status + this.status.std + punct.period 'this.status.punct := + isbn #1 #1 substring$ + duplicate$ "{" = + { skip$ } + { status.cap + { "u" } + { "l" } + if$ + change.case$ + } + if$ + isbn #2 global.max$ substring$ * "isbn" bibinfo.check + cap.yes 'status.cap := + } + if$ +} + + +%% note + +FUNCTION {format.note} +{ note empty$ + { "" } + { this.to.prev.status + this.status.std + punct.period 'this.status.punct := + note #1 #1 substring$ + duplicate$ "{" = + { skip$ } + { status.cap + { "u" } + { "l" } + if$ + change.case$ + } + if$ + note #2 global.max$ substring$ * "note" bibinfo.check + cap.yes 'status.cap := + } + if$ +} + + + +%% patent + +FUNCTION {format.patent.date} +{ this.to.prev.status + this.status.std + year empty$ + { monthfiled duplicate$ empty$ + { "monthfiled" bibinfo.check pop$ "" } + { "monthfiled" bibinfo.check } + if$ + dayfiled duplicate$ empty$ + { "dayfiled" bibinfo.check pop$ "" * } + { "dayfiled" bibinfo.check + monthfiled empty$ + { "dayfiled without a monthfiled in " cite$ * warning$ + * + } + { " " swap$ * * } + if$ + } + if$ + yearfiled empty$ + { "no year or yearfiled in " cite$ * warning$ } + { yearfiled "yearfiled" bibinfo.check + swap$ + duplicate$ empty$ + { pop$ } + { ", " * swap$ * } + if$ + } + if$ + } + { month duplicate$ empty$ + { "month" bibinfo.check pop$ "" } + { "month" bibinfo.check } + if$ + day duplicate$ empty$ + { "day" bibinfo.check pop$ "" * } + { "day" bibinfo.check + month empty$ + { "day without a month in " cite$ * warning$ + * + } + { " " swap$ * * } + if$ + } + if$ + year "year" bibinfo.check + swap$ + duplicate$ empty$ + { pop$ } + { ", " * swap$ * } + if$ + } + if$ + cap.status.std +} + +FUNCTION {format.patent.nationality.type.number} +{ this.to.prev.status + this.status.std + nationality duplicate$ empty$ + { "nationality" bibinfo.warn pop$ "" } + { "nationality" bibinfo.check + duplicate$ "l" change.case$ "united states" = + { pop$ bbl.patentUS } + { skip$ } + if$ + " " * + } + if$ + type empty$ + { bbl.patent "type" bibinfo.check } + { type "type" bibinfo.check } + if$ + * + number duplicate$ empty$ + { "number" bibinfo.warn pop$ } + { "number" bibinfo.check + large.number.separate + swap$ " " * swap$ * + } + if$ + cap.status.std +} + + + +%% standard + +FUNCTION {format.organization.institution.standard.type.number} +{ this.to.prev.status + this.status.std + organization duplicate$ empty$ + { pop$ + institution duplicate$ empty$ + { "institution" bibinfo.warn } + { "institution" bibinfo.warn " " * } + if$ + } + { "organization" bibinfo.warn " " * } + if$ + type empty$ + { bbl.standard "type" bibinfo.check } + { type "type" bibinfo.check } + if$ + * + number duplicate$ empty$ + { "number" bibinfo.check pop$ } + { "number" bibinfo.check + large.number.separate + swap$ " " * swap$ * + } + if$ + cap.status.std +} + +FUNCTION {format.revision} +{ revision empty$ + { "" } + { this.to.prev.status + this.status.std + bbl.revision + revision tie.or.space.prefix + "revision" bibinfo.check + * * + cap.status.std + } + if$ +} + + +%% thesis + +FUNCTION {format.master.thesis.type} +{ this.to.prev.status + this.status.std + type empty$ + { + bbl.mthesis + } + { + type "type" bibinfo.check + } + if$ +cap.status.std +} + +FUNCTION {format.phd.thesis.type} +{ this.to.prev.status + this.status.std + type empty$ + { + bbl.phdthesis + } + { + type "type" bibinfo.check + } + if$ +cap.status.std +} + + + +%% URL + +FUNCTION {format.url} +{ url empty$ + { "" } + { this.to.prev.status + this.status.std + cap.yes 'status.cap := + bbl.urlprefix " " * + "\url{" * url * "}" * + punct.no 'this.status.punct := + punct.period 'prev.status.punct := + space.normal 'this.status.space := + space.normal 'prev.status.space := + quote.no 'this.status.quote := + } + if$ +} + + + + +%%%%%%%%%%%%%%%%%%%% +%% ENTRY HANDLERS %% +%%%%%%%%%%%%%%%%%%%% + + +% Note: In many journals, IEEE (or the authors) tend not to show the number +% for articles, so the display of the number is controlled here by the +% switch "is.use.number.for.article" +FUNCTION {article} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors "author" output.warn + name.or.dash + format.article.title "title" output.warn + format.journal "journal" bibinfo.check "journal" output.warn + format.volume output + format.number.if.use.for.article output + format.pages output + format.date "year" output.warn + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {book} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + author empty$ + { format.editors "author and editor" output.warn } + { format.authors output.nonnull } + if$ + name.or.dash + format.book.title.edition output + format.series output + author empty$ + { skip$ } + { format.editors output } + if$ + format.address.publisher.date output + format.volume output + format.number output + format.pages output + format.note output + format.url output + format.isbn output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {booklet} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors output + name.or.dash + format.article.title "title" output.warn + format.howpublished "howpublished" bibinfo.check output + format.organization "organization" bibinfo.check output + format.address "address" bibinfo.check output + format.date output + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {electronic} +{ std.status.using.period + start.entry + if.url.alt.interword.spacing + format.authors output + name.or.dash + format.date.electronic output + format.article.title.electronic output + format.howpublished "howpublished" bibinfo.check output + format.organization "organization" bibinfo.check output + format.address "address" bibinfo.check output + format.note output + format.url output + fin.entry + empty.entry.warn + if.url.std.interword.spacing +% TB: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {inbook} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + author empty$ + { format.editors "author and editor" output.warn } + { format.authors output.nonnull } + if$ + name.or.dash + format.book.title.edition output + format.series output + format.address.publisher.date output + format.volume output + format.number output + format.chapter output + format.pages output + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {incollection} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors "author" output.warn + name.or.dash + format.article.title "title" output.warn + format.in.booktitle.edition "booktitle" output.warn + format.series output + format.editors output + format.address.publisher.date.nowarn output + format.volume output + format.number output + format.chapter output + format.pages output + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {inproceedings} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors "author" output.warn + name.or.dash + format.article.title "title" output.warn + format.in.booktitle "booktitle" output.warn + format.series output + format.editors output + format.volume output + format.number output + publisher empty$ + { format.address.organization.date output } + { format.organization "organization" bibinfo.check output + format.address.publisher.date output + } + if$ + format.paper output + format.pages output + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {manual} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors output + name.or.dash + format.book.title.edition "title" output.warn + format.howpublished "howpublished" bibinfo.check output + format.organization "organization" bibinfo.check output + format.address "address" bibinfo.check output + format.date output + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {mastersthesis} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors "author" output.warn + name.or.dash + format.article.title "title" output.warn + format.master.thesis.type output.nonnull + format.school "school" bibinfo.warn output + format.address "address" bibinfo.check output + format.date "year" output.warn + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {misc} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors output + name.or.dash + format.article.title output + format.howpublished "howpublished" bibinfo.check output + format.organization "organization" bibinfo.check output + format.address "address" bibinfo.check output + format.pages output + format.date output + format.note output + format.url output + fin.entry + empty.entry.warn + if.url.std.interword.spacing +% TB: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {patent} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors output + name.or.dash + format.article.title output + format.patent.nationality.type.number output + format.patent.date output + format.note output + format.url output + fin.entry + empty.entry.warn + if.url.std.interword.spacing +% TB: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {periodical} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.editors output + name.or.dash + format.book.title "title" output.warn + format.series output + format.volume output + format.number output + format.organization "organization" bibinfo.check output + format.date "year" output.warn + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {phdthesis} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors "author" output.warn + name.or.dash + format.article.title "title" output.warn + format.phd.thesis.type output.nonnull + format.school "school" bibinfo.warn output + format.address "address" bibinfo.check output + format.date "year" output.warn + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {proceedings} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.editors output + name.or.dash + format.book.title "title" output.warn + format.series output + format.volume output + format.number output + publisher empty$ + { format.address.organization.date output } + { format.organization "organization" bibinfo.check output + format.address.publisher.date output + } + if$ + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {standard} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors output + name.or.dash + format.book.title "title" output.warn + format.howpublished "howpublished" bibinfo.check output + format.organization.institution.standard.type.number output + format.revision output + format.date output + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {techreport} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors "author" output.warn + name.or.dash + format.article.title "title" output.warn + format.howpublished "howpublished" bibinfo.check output + format.institution "institution" bibinfo.warn output + format.address "address" bibinfo.check output + format.tech.report.number output.nonnull + format.date "year" output.warn + format.note output + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {unpublished} +{ std.status.using.comma + start.entry + if.url.alt.interword.spacing + format.authors "author" output.warn + name.or.dash + format.article.title "title" output.warn + format.date output + format.note "note" output.warn + format.url output + fin.entry + if.url.std.interword.spacing +% TB: added for annotation +% format.annotate write$ + newline$ +} + + +% The special entry type which provides the user interface to the +% BST controls +FUNCTION {IEEEtranBSTCTL} +{ is.print.banners.to.terminal + { "** IEEEtran BST control entry " quote$ * cite$ * quote$ * " detected." * + top$ + } + { skip$ } + if$ + CTLuse_article_number + empty$ + { skip$ } + { CTLuse_article_number + yes.no.to.int + 'is.use.number.for.article := + } + if$ + CTLuse_paper + empty$ + { skip$ } + { CTLuse_paper + yes.no.to.int + 'is.use.paper := + } + if$ + CTLuse_forced_etal + empty$ + { skip$ } + { CTLuse_forced_etal + yes.no.to.int + 'is.forced.et.al := + } + if$ + CTLmax_names_forced_etal + empty$ + { skip$ } + { CTLmax_names_forced_etal + string.to.integer + 'max.num.names.before.forced.et.al := + } + if$ + CTLnames_show_etal + empty$ + { skip$ } + { CTLnames_show_etal + string.to.integer + 'num.names.shown.with.forced.et.al := + } + if$ + CTLuse_alt_spacing + empty$ + { skip$ } + { CTLuse_alt_spacing + yes.no.to.int + 'is.use.alt.interword.spacing := + } + if$ + CTLalt_stretch_factor + empty$ + { skip$ } + { CTLalt_stretch_factor + 'ALTinterwordstretchfactor := + "\renewcommand\BIBentryALTinterwordstretchfactor{" + ALTinterwordstretchfactor * "}" * + write$ newline$ + } + if$ + CTLdash_repeated_names + empty$ + { skip$ } + { CTLdash_repeated_names + yes.no.to.int + 'is.dash.repeated.names := + } + if$ + CTLname_format_string + empty$ + { skip$ } + { CTLname_format_string + 'name.format.string := + } + if$ + CTLname_latex_cmd + empty$ + { skip$ } + { CTLname_latex_cmd + 'name.latex.cmd := + } + if$ + + + num.names.shown.with.forced.et.al max.num.names.before.forced.et.al > + { "CTLnames_show_etal cannot be greater than CTLmax_names_forced_etal in " cite$ * warning$ + max.num.names.before.forced.et.al 'num.names.shown.with.forced.et.al := + } + { skip$ } + if$ +} + + +%%%%%%%%%%%%%%%%%%% +%% ENTRY ALIASES %% +%%%%%%%%%%%%%%%%%%% +FUNCTION {conference}{inproceedings} +FUNCTION {online}{electronic} +FUNCTION {internet}{electronic} +FUNCTION {webpage}{electronic} +FUNCTION {default.type}{misc} + + + +%%%%%%%%%%%%%%%%%% +%% MAIN PROGRAM %% +%%%%%%%%%%%%%%%%%% + +READ + +EXECUTE {initialize.controls} +EXECUTE {initialize.status.constants} +EXECUTE {banner.message} + +EXECUTE {initialize.longest.label} +ITERATE {longest.label.pass} + +EXECUTE {begin.bib} +ITERATE {call.type$} +EXECUTE {end.bib} + +EXECUTE{completed.message} + +%% That's all folks, mds. diff --git a/docs/report/StylesAndReferences/authordate2annot.bst b/docs/report/StylesAndReferences/authordate2annot.bst new file mode 100644 index 0000000..62da09a --- /dev/null +++ b/docs/report/StylesAndReferences/authordate2annot.bst @@ -0,0 +1,1364 @@ +% This BibTeX 0.99 style file is intended for documents that use the +% author-date citation system. It should be used in conjunction with the +% authordate1-4.sty (or equivalent) LaTeX style-option. +% +% In deciding on the bibliography layout to be implemented, the following +% works have been consulted: +% 1. British Standard 5605: "Citing publications by bibliographic +% references", 1978. +% 2. British Standard 1629: "Bibliographic references", 1976. +% (Note: There is now a 1989 edition.) +% 3. "Copy-editing" by Judith Butcher, Cambridge University Press, 1981. +% 4. "The Oxford Dictionary for Writers and Editors", Oxford University +% Press, 1981 (for abbreviations). +% 5. "The Chicago Manual of Style", Chicago University Press, 1982. +% +% Discretion has been used in certain matters. In particular: +% - Titles are italic except when there is a "contribution title" and +% a "main publication title", in which case the "contribution title" +% is roman while the "main publication title" is italic. +% - When there is a PUBLISHER, it is assumed that ADDRESS contains "place of +% publication"; output is of the form "place-of-publication: publisher". +% When there is an ORGANIZATION as well as a PUBLISHER, output is of the +% form "place-of-publication: publisher, for organization". Otherwise, +% it is assumed that ADDRESS is a postal address, and output is of the +% form "institution, address", "organization, address", "school, address" +% or "howpublished, address". +% - If there is a MONTH but no VOLUME or NUMBER for a journal-article, the +% MONTH is used on the assumption that it contains information that is +% equivalent to VOLUME or NUMBER. MONTH is ignored for other documents +% that have a PUBLISHER, but output after YEAR for anything else. +% - When CHAPTER and/or PAGES are specified with INBOOK, it is assumed that +% these fields are being used to pick out particular pages of interest +% (as an alternative to using the optional [...] argument of \cite); +% the information is put at the very end of the entry, in line with BS 1629. +% When CHAPTER and/or PAGES are specified for INCOLLECTION or INPROCEEDINGS, +% it is assumed that the fields are being used to specify the location of +% the part/article of interest; the information is put before the +% BOOKTITLE, in line with Chicago's treatment of "parts" and "chapters". +% - Since "volume" can be used in various ways (see page 219 of Butcher), +% this file assumes that, when there is a SERIES, any VOLUME and NUMBER +% refer to position in the SERIES (i.e. Butcher's meaning 4). +% If there is a VOLUME but no SERIES, it is assumed that VOLUME refers +% to a volume within a particular work (i.e. Butcher's meaning 1, 2 or 3). +% For INPROCEEDINGS and INCOLLECTION, this information goes after the +% BOOKTITLE. (If you prefer to have volume information before EDITOR, +% as on page 449 of Chicago, you can set TYPE = "Vol." with INCOLLECTION.) +% +% This file differs from authordate1.bst, authordate3.bst and authordate4.bst +% in that: +% - Titles of journals, articles and boooks are "downstyle". Apart from the +% first character, and the first character following : and white space, +% uppercase letters are converted to lowercase unless protected by {}. +% - Author's and editor's names are in roman. +% +% The combination of authordate2.bst and authordate1-4.sty allows citations +% of the form \shortcite{bloggs-60} as well as the usual \cite{bloggs-60}. +% When +% ... \cite{bloggs-60} ... \shortcite{bloggs-60} ... +% appears in the input file, +% ... (Bloggs, 1960) ... (1960) ... +% appears in the final document. +% +% This file was developed from apalike.bst. It also uses code taken from +% acm.bst, aaai-named.bst, btxbst.doc, ieeetr.bst and siam.bst. +% +% David Rhead +% Cripps Computing Centre +% Nottingham University +% March 1990 +% + +%nst - added annot +ENTRY + { address + annote + author + booktitle + chapter + edition + editor + howpublished + institution + journal + key + month + note + number + organization + pages + publisher + school + series + title + type + volume + year + } + {} + { label extra.label sort.label } + +INTEGERS { output.state before.all mid.sentence after.sentence after.block } + +FUNCTION {init.state.consts} +{ #0 'before.all := + #1 'mid.sentence := + #2 'after.sentence := + #3 'after.block := +} + +STRINGS { s t } + +% annotation addition +FUNCTION {format.annotate} +{ annote empty$ + { "" } + { " \begin{quotation}\noindent " + annote + * " \end{quotation} " * + } + if$ +} + +FUNCTION {output.nonnull} +{ 's := + output.state mid.sentence = + { ", " * write$ } + { output.state after.block = + { add.period$ write$ + newline$ + "\newblock " write$ + } + { output.state before.all = + 'write$ + { add.period$ " " * write$ } + if$ + } + if$ + mid.sentence 'output.state := + } + if$ + s +} + +FUNCTION {output} +{ duplicate$ empty$ + 'pop$ + 'output.nonnull + if$ +} + +FUNCTION {output.check} +{ 't := + duplicate$ empty$ + { pop$ "empty " t * " in " * cite$ * warning$ } + 'output.nonnull + if$ +} + +FUNCTION {output.year.month.check} +{ year empty$ + { "empty year in " cite$ * warning$ } + { add.period$ write$ + month empty$ + { " " year * extra.label * "." * + after.sentence 'output.state := + } + { " " year * extra.label * " (" * month * ")." * + after.sentence 'output.state := + } + if$ + } + if$ +} + +FUNCTION {output.year.check} +{ year empty$ + { "empty year in " cite$ * warning$ } + { add.period$ write$ + " " year * extra.label * "." * + after.sentence 'output.state := + } + if$ +} + +FUNCTION {output.bibitem} +{ newline$ + "\bibitem[" write$ + label write$ + "]{" write$ + cite$ write$ + "}" write$ + newline$ + "" + before.all 'output.state := +} + +FUNCTION {fin.entry} +{ add.period$ + write$ + newline$ +} + +FUNCTION {new.block} +{ output.state before.all = + 'skip$ + { after.block 'output.state := } + if$ +} + +FUNCTION {new.sentence} +{ output.state after.block = + 'skip$ + { output.state before.all = + 'skip$ + { after.sentence 'output.state := } + if$ + } + if$ +} + +FUNCTION {not} +{ { #0 } + { #1 } + if$ +} + +FUNCTION {and} +{ 'skip$ + { pop$ #0 } + if$ +} + +FUNCTION {or} +{ { pop$ #1 } + 'skip$ + if$ +} + +FUNCTION {new.block.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.block + if$ +} + +FUNCTION {field.or.null} +{ duplicate$ empty$ + { pop$ "" } + 'skip$ + if$ +} + +FUNCTION {boldface} +{ duplicate$ empty$ + { pop$ "" } + { "{\bf " swap$ * "}" * } + if$ +} + +FUNCTION {emphasize} +{ duplicate$ empty$ + { pop$ "" } + { "{\em " swap$ * "}" * } + if$ +} + +INTEGERS { nameptr namesleft numnames } + +FUNCTION {format.names} +{ 's := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr "{vv~}{ll}{, jj}{, ff}" format.name$ 't := + nameptr #1 > + { namesleft #1 > + { ", " * t * } + { t "others" = + { ", {\em et~al.}" * } + { ", \& " * t * } % Butcher, pages + if$ % 186-189. + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {format.authors} +{ author empty$ + { "" } + { author format.names } + if$ +} + +FUNCTION {format.key} +{ empty$ + { key field.or.null } + { "" } + if$ +} + +FUNCTION {format.editors} +{ editor empty$ + { "" } + { editor format.names + editor num.names$ #1 > % Use ODWE abbrevs. + { " (eds)" * } % to avoid + { " (ed)" * } % ambiguity between + if$ % "editor" and + } % "edition". + if$ +} + +FUNCTION {format.title} % Howells example +{ title empty$ % in BS 5605 comes + { "" } % out wrong because + { title "t" change.case$ } % Patashnik + if$ % capitalizes +} % after a colon. + +FUNCTION {n.dashify} +{ 't := + "" + { t empty$ not } + { t #1 #1 substring$ "-" = + { t #1 #2 substring$ "--" = not + { "--" * + t #2 global.max$ substring$ 't := + } + { { t #1 #1 substring$ "-" = } + { "-" * + t #2 global.max$ substring$ 't := + } + while$ + } + if$ + } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + if$ + } + while$ +} + +FUNCTION {format.btitle} +{ title empty$ + { "" } + { title "t" change.case$ emphasize } + if$ +} + +FUNCTION {tie.or.space.connect} +{ duplicate$ text.length$ #3 < + { "~" } + { " " } + if$ + swap$ * * +} + +FUNCTION {either.or.check} +{ empty$ + 'pop$ + { "can't use both " swap$ * " fields in " * cite$ * warning$ } + if$ +} + +INTEGERS { multiresult } + +FUNCTION {multi.page.check} +{ 't := + #0 'multiresult := + { multiresult not + t empty$ not + and + } + { t #1 #1 substring$ + duplicate$ "-" = + swap$ duplicate$ "," = + swap$ "+" = + or or + { #1 'multiresult := } + { t #2 global.max$ substring$ 't := } + if$ + } + while$ + multiresult +} + +FUNCTION {format.numberinseries} +{ number empty$ + { "" } + { number multi.page.check + { ", nos. " number n.dashify tie.or.space.connect } + { ", no. " number tie.or.space.connect } + if$ + } + if$ +} + +FUNCTION {booklike.series.volume.number} % Chicago, pages +{ series empty$ % 450-451. + { volume empty$ + { " " } + { " Vol. " volume * } + if$ + } + { + volume empty$ + { number empty$ + { series } + { series format.numberinseries * } + if$ + } + { number empty$ + { series ", vol. " volume * * } + { series ", vol. " * volume * format.numberinseries * } + if$ + } + if$ + } + if$ +} + +FUNCTION {incollectionlike.series.volume.number} +{ series empty$ + { volume empty$ + { " " } + { " vol. " volume * } + if$ + } + { new.block + volume empty$ + { number empty$ + { series } + { series format.numberinseries * } + if$ + } + { number empty$ + { series ", vol. " volume * * } + { series ", vol. " * volume * format.numberinseries * } + if$ + } + if$ + } + if$ +} + +FUNCTION {format.edition} +{ edition empty$ + { "" } + { output.state mid.sentence = + { edition "l" change.case$ " edn." * } + { edition "t" change.case$ " edn." * } + if$ + } + if$ +} + +FUNCTION {format.pages} +{ pages empty$ + { "" } + { pages multi.page.check + { "" pages n.dashify tie.or.space.connect } + { "" pages tie.or.space.connect } + if$ + } + if$ +} + +FUNCTION {format.pagesinbook} % By the time the +{ pages empty$ % reader has read + { "" } % address, pub'r, + { pages multi.page.check % note (where the + { "Pages " pages n.dashify tie.or.space.connect } % note may end with + { "Page " pages tie.or.space.connect } % numbers), s/he + if$ % may not recognise + } % a number-range as + if$ % meaning pages. +} % Avoid ambiguity + % (Butcher, p.181). + +FUNCTION {format.vol.num.date.pages} +{ volume empty$ + { month empty$ + { "" } + { month } + if$ + } + { volume boldface field.or.null + number empty$ + { month empty$ + 'skip$ + { "(" month * ")" * * } + if$ + } + { "(" number * ")" * * + volume empty$ + { "there's a number but no volume in " cite$ * warning$ } + 'skip$ + if$ + } + if$ + } + if$ + pages empty$ + 'skip$ + { duplicate$ empty$ + { pop$ format.pages } + { ", " * pages n.dashify * } + if$ + } + if$ +} + +FUNCTION {format.chapter.pages.inbook} +{ chapter empty$ + 'format.pagesinbook + { type empty$ + { "Chap." } + { type } + if$ + chapter tie.or.space.connect + pages empty$ + 'skip$ + { ", " * format.pagesinbook "l" change.case$ * } + if$ + } + if$ +} + +FUNCTION {format.chapter.pages.incoll} +{ chapter empty$ + { pages empty$ + { "{\em In:} " } + { "{\em " format.pagesinbook " of:} " * * } + if$ + } + { type empty$ + { "{\em Chap. " chapter * } + { "{\em " type * " " * chapter * } + if$ + pages empty$ + { " of:} " * } + { ", " * format.pagesinbook "l" change.case$ " of:} " * * } + if$ + } + if$ +} + +FUNCTION {format.in.ed.booktitle} % Achieves effect +{ booktitle empty$ % shown in 16.51 + { "" } % of Chicago, at + { editor empty$ % expense of not + { format.chapter.pages.incoll % achieving effects + booktitle "t" change.case$ emphasize * } % shown in 16.50 + { format.chapter.pages.incoll % of Chicago, on + format.editors * ", " * % page 189 of + booktitle "t" change.case$ emphasize * } % Butcher and in + if$ % 4.4 of BS 1629. + } + if$ +} + +FUNCTION {format.thesis.type} +{ type empty$ + 'skip$ + { pop$ + type "t" change.case$ + } + if$ +} + +FUNCTION {format.tr.number} +{ type empty$ + { "Tech. rept." } % ODWE abbrevs. + 'type + if$ + number empty$ + { "t" change.case$ } + { number tie.or.space.connect } + if$ +} + +FUNCTION {format.addr.pub} +{ publisher empty$ + { "" } + { address empty$ + { "" } + { address ": " * } + if$ + publisher * + } + if$ +} + +FUNCTION {format.addr.pub.org} % If there's an +{ address empty$ % an organization + { publisher * ", for " * organization * } % and a publisher + { address ": " * publisher * ", for " * organization * } % too. + if$ +} + +FUNCTION {format.addr.inst} +{ address empty$ + { institution empty$ + { "" } + { institution } + if$ + } + { institution empty$ + { "" } + { institution ", " * } + if$ + address * + } + if$ +} + +FUNCTION {format.addr.org} +{ address empty$ + { organization empty$ + { "" } + { organization } + if$ + } + { organization empty$ + { "" } + { organization ", " * } + if$ + address * + } + if$ +} + +FUNCTION {format.article.crossref} +{ "{\em In:}" + " \cite{" * crossref * "}" * +} + +FUNCTION {format.book.crossref} +{ volume empty$ + { "empty volume in " cite$ * "'s crossref of " * crossref * warning$ + "{\em In:}" + } + { " Vol." volume tie.or.space.connect + " of " * + } + if$ + "\cite{" * crossref * "}" * +} + +FUNCTION {format.incoll.inproc.crossref} +{ "{\em In:}" + " \cite{" * crossref * "}" * +} + + +FUNCTION {article} +{ output.bibitem + format.authors "author" output.check + author format.key output + output.year.check + new.block + format.title "title" output.check + new.block + crossref missing$ + { journal "t" change.case$ emphasize + "journal" output.check + format.vol.num.date.pages output + } + { format.article.crossref output.nonnull + format.pages output + } + if$ + new.block + note output + fin.entry +% NST: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {book} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check + editor format.key output + } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + output.year.check + new.block + format.btitle "title" output.check + crossref missing$ + { new.sentence + format.edition output + new.block + booklike.series.volume.number output + new.block + format.addr.pub "publisher" output.check + } + { new.block + format.book.crossref output.nonnull + } + if$ + new.block + note output + fin.entry +% NST: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {booklet} +{ output.bibitem + format.authors output + author format.key output + output.year.month.check + new.block + format.btitle "title" output.check + new.block + howpublished output + address output + new.block + note output + fin.entry +% NST: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {inbook} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check + editor format.key output + } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + output.year.check + new.block + format.btitle "title" output.check + crossref missing$ + { new.sentence + format.edition output + new.block + booklike.series.volume.number output + new.block + format.addr.pub "publisher" output.check + } + { new.block + format.book.crossref output.nonnull + } + if$ + new.block + note output + new.block % BS 1629 (rather + format.chapter.pages.inbook "chapter and pages" output.check + fin.entry % than Chicago, p. 451 +% NST: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {incollection} +{ output.bibitem + author empty$ + { format.editors "editor" output.check + editor format.key output } + { format.authors "author" output.check + author format.key output } + if$ + output.year.check + new.block + format.title "title" output.check + new.block + crossref missing$ % Chapter and/or + { format.in.ed.booktitle output % page numbers can + format.edition output % come out via this + incollectionlike.series.volume.number output % route, too. + new.block + format.addr.pub "publisher" output.check + } + { format.incoll.inproc.crossref output.nonnull + new.block + } + if$ + new.block + note output + fin.entry + % NST: added for annotation + % format.annotate write$ + newline$ +} + +FUNCTION {inproceedings} +{ output.bibitem + format.authors "author" output.check + author format.key output + publisher empty$ + { output.year.month.check } + { output.year.check } + if$ + new.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + incollectionlike.series.volume.number output + new.block + publisher empty$ + { + organization empty$ + 'skip$ + { format.addr.org output } + if$ + } + { + organization empty$ + { format.addr.pub output } + { format.addr.pub.org output } + if$ + } + if$ + } + { format.incoll.inproc.crossref output.nonnull + } + if$ + new.block + note output + fin.entry + % NST: added for annotation + % format.annotate write$ + newline$ +} + +FUNCTION {conference} { inproceedings } + +FUNCTION {manual} +{ output.bibitem + format.authors output + author format.key output + output.year.month.check + new.block + format.btitle "title" output.check + new.sentence + format.edition output + new.block + organization address new.block.checkb + format.addr.org output + new.block + note output + fin.entry + % NST: added for annotation + % format.annotate write$ + newline$ +} + +FUNCTION {mastersthesis} +{ output.bibitem + format.authors "author" output.check + author format.key output + output.year.month.check + new.block + format.btitle "title" output.check + new.block + "M.Phil. thesis" format.thesis.type output.nonnull % ODWE abbrev. + school "school" output.check + address output + new.block + note output + fin.entry +% NST: added for annotation +% format.annotate write$ + newline$ + +} + +FUNCTION {misc} +{ output.bibitem + format.authors output + author format.key output + output.year.month.check + new.block + format.btitle output + new.block + howpublished output + new.block + note output + fin.entry +% NST: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {phdthesis} +{ output.bibitem + format.authors "author" output.check + author format.key output + output.year.month.check + new.block + format.btitle "title" output.check + new.block + "Ph.D. thesis" format.thesis.type output.nonnull % Butcher, + school "school" output.check % page 174. + address output + new.block + note output + fin.entry +% NST: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {proceedings} +{ output.bibitem + format.editors "author and editor" output.check + editor format.key output + publisher empty$ + { output.year.month.check } + { output.year.check } + if$ + new.block + format.btitle "title" output.check + new.block + booklike.series.volume.number output + new.block + publisher empty$ + { + organization empty$ + 'skip$ + { format.addr.org output } + if$ + } + { + organization empty$ + { format.addr.pub output } + { format.addr.pub.org output } + if$ + } + if$ + new.block + note output + fin.entry +% NST: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {techreport} +{ output.bibitem + format.authors "author" output.check + author format.key output + output.year.month.check + new.block + format.btitle "title" output.check + new.block + format.tr.number output.nonnull + new.sentence + format.addr.inst "institution" output.check + new.block + note output + fin.entry +% NST: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {unpublished} +{ output.bibitem + format.authors "author" output.check + author format.key output + output.year.month.check + new.block + format.btitle "title" output.check + new.block + note "note" output.check + fin.entry +% NST: added for annotation +% format.annotate write$ + newline$ +} + +FUNCTION {default.type} { misc } + +MACRO {jan} {"Jan."} % ODWE, "months", & + % Chicago, p. 383. +MACRO {feb} {"Feb."} + +MACRO {mar} {"Mar."} + +MACRO {apr} {"Apr."} + +MACRO {may} {"May"} + +MACRO {jun} {"June"} + +MACRO {jul} {"July"} + +MACRO {aug} {"Aug."} + +MACRO {sep} {"Sept."} + +MACRO {oct} {"Oct."} + +MACRO {nov} {"Nov."} + +MACRO {dec} {"Dec."} + +MACRO {acmcs} {"ACM Computing Surveys"} + +MACRO {acta} {"Acta Informatica"} + +MACRO {cacm} {"Communications of the ACM"} + +MACRO {ibmjrd} {"IBM Journal of Research and Development"} + +MACRO {ibmsj} {"IBM Systems Journal"} + +MACRO {ieeese} {"IEEE Transactions on Software Engineering"} + +MACRO {ieeetc} {"IEEE Transactions on Computers"} + +MACRO {ieeetcad} + {"IEEE Transactions on Computer-Aided Design of Integrated Circuits"} + +MACRO {ipl} {"Information Processing Letters"} + +MACRO {jacm} {"Journal of the ACM"} + +MACRO {jcss} {"Journal of Computer and System Sciences"} + +MACRO {scp} {"Science of Computer Programming"} + +MACRO {sicomp} {"SIAM Journal on Computing"} + +MACRO {tocs} {"ACM Transactions on Computer Systems"} + +MACRO {tods} {"ACM Transactions on Database Systems"} + +MACRO {tog} {"ACM Transactions on Graphics"} + +MACRO {toms} {"ACM Transactions on Mathematical Software"} + +MACRO {toois} {"ACM Transactions on Office Information Systems"} + +MACRO {toplas} {"ACM Transactions on Programming Languages and Systems"} + +MACRO {tcs} {"Theoretical Computer Science"} + +READ + +FUNCTION {sortify} +{ purify$ + "l" change.case$ +} + +INTEGERS { len } + +FUNCTION {chop.word} +{ 's := + 'len := + s #1 len substring$ = + { s len #1 + global.max$ substring$ } + 's + if$ +} + +FUNCTION {format.lab.names} +{ 's := + s #1 "{vv~}{ll}" format.name$ + s num.names$ duplicate$ + #2 > + { pop$ " {\em et~al.}" * } + { #2 < + 'skip$ + { s #2 "{ff }{vv }{ll}{ jj}" format.name$ "others" = + { " {\em et~al.}" * } + { " \& " * s #2 "{vv~}{ll}" format.name$ * } + if$ + } + if$ + } + if$ +} + +FUNCTION {author.key.label} +{ author empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.editor.key.label} +{ author empty$ + { editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.lab.names } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {editor.key.label} +{ editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.lab.names } + if$ +} + +FUNCTION {calc.label} + { type$ "book" = + type$ "inbook" = + type$ "incollection" = % For sensible + or or % treatment of + 'author.editor.key.label % Singer in + { type$ "proceedings" = % BS 1629. + 'editor.key.label + 'author.key.label + if$ + } + if$ + duplicate$ + year empty$ + { + "\protect\citename{" swap$ * ", }" * + "n.d." * 'label := % Chicago, + } % page 457. + { + "\protect\citename{" swap$ * ", }" * + year + * + 'label := + } + if$ + year field.or.null purify$ * + sortify 'sort.label := +} + + +FUNCTION {sort.format.names} % To produce the +{ 's := % order of entries + #1 'nameptr := % specified in item + "" % (3) on page 187 + s num.names$ 'numnames := % of Butcher. + numnames 'namesleft := + { namesleft #0 > nameptr #3 < and } % Only 1st 2 names + { nameptr #1 > % matter for + { " " * } % sorting. + 'skip$ + if$ % Anything that's + nameptr #2 = numnames #2 > and % "et al" goes + { "zzzzz" * } % after works by 2 + { % authors. + s nameptr "{vv{ } }{ll{ }}{ ff{ }}{ jj{ }}" format.name$ 't := + nameptr numnames = t "others" = and + { "zzzzz" * } + { t sortify * } + if$ + } + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {sort.format.title} +{ 't := + "A " #2 + "An " #3 + "The " #4 t chop.word + chop.word + chop.word + sortify + #1 global.max$ substring$ +} + +FUNCTION {author.sort} +{ author empty$ + { key empty$ + { "to sort, need author or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.editor.sort} +{ author empty$ + { editor empty$ + { key empty$ + { "to sort, need author, editor, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {editor.sort} +{ editor empty$ + { key empty$ + { "to sort, need editor or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ +} + +FUNCTION {presort} % Two sorting +{ calc.label % passes, from + label sortify % apalike.bst. + " " + * + type$ "book" = + type$ "inbook" = + type$ "incollection" = % For Singer + or or % in BS 1629. + 'author.editor.sort + { type$ "proceedings" = + 'editor.sort + 'author.sort + if$ + } + if$ + #1 entry.max$ substring$ + 'sort.label := + sort.label + * + " " + * + title field.or.null + sort.format.title + * + #1 entry.max$ substring$ + 'sort.key$ := +} + +ITERATE {presort} + +SORT + +STRINGS { last.label next.extra } + +INTEGERS { last.extra.num } + +FUNCTION {initialize.extra.label.stuff} +{ #0 int.to.chr$ 'last.label := + "" 'next.extra := + #0 'last.extra.num := +} + +FUNCTION {forward.pass} +{ last.label label = + { last.extra.num #1 + 'last.extra.num := + last.extra.num int.to.chr$ 'extra.label := + } + { "a" chr.to.int$ 'last.extra.num := + "" 'extra.label := + label 'last.label := + } + if$ +} + +FUNCTION {reverse.pass} +{ next.extra "b" = + { "a" 'extra.label := } + 'skip$ + if$ % Code needed here + % if \citeauthor + % and \citeyear + label extra.label * 'label := % were supported. + extra.label 'next.extra := +} + +EXECUTE {initialize.extra.label.stuff} + +ITERATE {forward.pass} + +REVERSE {reverse.pass} + +FUNCTION {bib.sort.order} +{ sort.label + " " + * + year field.or.null sortify + * + " " + * + title field.or.null + sort.format.title + * + #1 entry.max$ substring$ + 'sort.key$ := +} + +ITERATE {bib.sort.order} + +SORT + +FUNCTION {begin.bib} +{ preamble$ empty$ + 'skip$ + { preamble$ write$ newline$ } + if$ + "\begin{thebibliography}{}" write$ newline$ +} + +EXECUTE {begin.bib} + +EXECUTE {init.state.consts} + +ITERATE {call.type$} + +FUNCTION {end.bib} +{ newline$ + "\end{thebibliography}" write$ newline$ +} + +EXECUTE {end.bib} diff --git a/docs/report/StylesAndReferences/mmp-report.sty b/docs/report/StylesAndReferences/mmp-report.sty new file mode 100644 index 0000000..ca3bcbd --- /dev/null +++ b/docs/report/StylesAndReferences/mmp-report.sty @@ -0,0 +1,358 @@ +%% LaTeX class to write Major/Minor projects for the Computer Science Department, +%% Aberystwyth University. +%% +%% Written by Neil Taylor +%% Comments and bugs to nst@aber.ac.uk +%% +%% See the accompanying file MMP_ProgressReport_example.tex for an example on how to +%% use it. +%% +\ProvidesPackage{mmp-report} + +%\usepackage[a4paper,margin=2.5cm,nohead, headheight=3cm, headsep=20pt]{geometry} + +\usepackage{graphicx} %to allow images to be imported see example at end of template + +\usepackage{palatino} %or {times} etc +\usepackage{plain} %bibliography style +\usepackage{amsmath} %math fonts - just in case +\usepackage{amsfonts} %math fonts +\usepackage{amssymb} %math fonts + +% Packages used to change colours for fonts +\usepackage{xcolor} +\usepackage{sectsty} + +% packages for figures +\usepackage{graphicx} +\usepackage{subcaption} +\usepackage{float} + +% Fonts + +% The following font will use a Sans Serif font throughout the document +% See https://www.overleaf.com/learn/latex/Font_typefaces for discussion +% of other fonts. Include both lines to use a sans serif font throughout the +% document. To use a Serif font (e.g. Times), then comment out the following +% two lines. +\usepackage{tgheros} +\renewcommand{\familydefault}{\sfdefault} + +% To use a specific Serif font, comment out the following line and +% change palatino to a font of your choice. +%\usepackage{palatino} + +% package for page headers +\usepackage{fancyhdr} +\usepackage{lastpage} + +% Package for url formatting and also creates hyperlinks. +\usepackage[hidelinks]{hyperref} + +% Various parameters +\setlength{\textheight}{229mm} +\setlength{\topmargin}{-5.4mm} +\setlength{\textwidth}{150mm} + +% Adjust the following if you want to introduce some indentation for +% margins (e.g. if printing). +\setlength{\oddsidemargin}{0mm} +\setlength{\evensidemargin}{0mm} +\setlength{\headheight}{0pt} + +\parskip=8pt + +% index and section numbering depths +\setcounter{secnumdepth}{3} +\setcounter{tocdepth}{4} + +\newcommand{\is}{\hspace*{0.2in}} %little indent space + +\newcommand{\reporttype}[1]{ + \newcommand{\showreporttype}{#1} +} + + + +\newcommand{\mmpdocdate}{\today} + +\newcommand{\documentdate}[1]{ + \renewcommand{\mmpdocdate}{#1} +} + +\newcommand{\name}[1]{ + \newcommand{\showname}{#1} +} + +\newcommand{\userid}[1]{ + \newcommand{\showuserid}{#1} +} + +\newcommand{\supervisor}[1]{ + \newcommand{\showsupervisor}{#1} +} + +\newcommand{\supervisorid}[1]{ + \newcommand{\showsupervisorid}{#1} +} + +\newcommand{\projecttitle}[1]{ + \newcommand{\showprojecttitle}{#1} +} + +\newcommand{\reporttitle}[1]{ + \newcommand{\showreporttitle}{#1} +} + +\newcommand{\projecttitlememoir}[1]{ + \newcommand{\showprojecttitlememoir}{#1} +} + +\newcommand{\version}[1]{ + \newcommand{\showversion}{#1} +} + +\newcommand{\docstatus}[1]{ + \newcommand{\showdocstatus}{#1} +} + +\newcommand{\degreeschemecode}[1]{ + \newcommand{\showdegreeschemecode}{#1} +} + +\newcommand{\degreeschemename}[1]{ + \newcommand{\showdegreeschemename}{#1} +} + +\newcommand{\modulecode}[1]{ + \newcommand{\showmodulecode}{#1} +} + +\newcommand{\wordcount}[1]{ + \newcommand{\showwordcount}{#1} +} + +\newcommand{\helv}{ + %bold, 18point, 21point line spacing + \fontfamily{phv}\fontseries{b}\fontsize{18}{21}\selectfont +} + +\def\labelenumi{\arabic{enumi}.} +\def\theenumi{\arabic{enumi}} +\def\labelenumii{(\alph{enumii})} +\def\theenumii{\alph{enumii}} +\def\p@enumii{\theenumi} +\def\labelenumiii{\roman{enumiii}.} +\def\theenumiii{\roman{enumiii}} +\def\p@enumiii{\theenumi(\theenumii)} +\def\labelenumiv{\Alph{enumiv}.} +\def\theenumiv{\Alph{enumiv}} +\def\p@enumiv{\p@enumiii\theenumiii} + +\def\labelitemi{$\bullet$} +\def\labelitemii{\bf --} +\def\labelitemiii{$\ast$} +\def\labelitemiv{$\cdot$} + +\def\verse{\let\\=\@centercr + \list{}{\itemsep\z@ \itemindent -1.5em\listparindent \itemindent + \rightmargin\leftmargin\advance\leftmargin 1.5em}\item[]} +\let\endverse\endlist +\def\quotation{\list{}{\listparindent 1.5em + \itemindent\listparindent + \rightmargin\leftmargin \parsep 0pt plus 1pt}\item[]} +\let\endquotation=\endlist +\def\quote{\list{}{\rightmargin\leftmargin}\item[]} +\let\endquote=\endlist + +\def\descriptionlabel#1{\hspace\labelsep \bf #1} +\def\description{\list{}{\labelwidth\z@ \itemindent-\leftmargin + \let\makelabel\descriptionlabel}} +\let\enddescription\endlist + +\def\theequation{\arabic{equation}} + + +\def\titlepage{\@restonecolfalse\if@twocolumn\@restonecoltrue\onecolumn + \else \newpage \fi \thispagestyle{empty}\c@page\z@} +\def\endtitlepage{\if@restonecol\twocolumn \else \newpage \fi} + +\arraycolsep 5pt \tabcolsep 6pt \arrayrulewidth .4pt \doublerulesep 2pt +\tabbingsep \labelsep + +\skip\@mpfootins = \skip\footins +\fboxsep = 3pt \fboxrule = .4pt + + +\def\thepart{\Roman{part}} +\def\thesection {\arabic{chapter}.\arabic{section}} +\def\thesubsection {\thesection.\arabic{subsection}} +\def\thesubsubsection {\thesubsection .\arabic{subsubsection}} +\def\theparagraph {\thesubsubsection.\arabic{paragraph}} +\def\thesubparagraph {\theparagraph.\arabic{subparagraph}} + +\def\@pnumwidth{1.55em} +\def\@tocrmarg {2.55em} +\def\@dotsep{4.5} +\setcounter{tocdepth}{2} + + +% set up the information for the title page +% title redefined to also set shorttitle + +\def\title#1{\gdef\@title{#1} \gdef\@shorttitle{#1}} +\def\subtitle#1{\gdef\@subtitle{#1}} +\def\authoremail#1{\gdef\@authoremail{#1}} + +\def\degreeschemecode#1{\gdef\@degreeschemecode{#1}} +\def\degreeschemetitle#1{\gdef\@degreeschemetitle{#1}} +\def\degreetype#1{\gdef\@degreetype{#1}} + +\def\modulecode#1{\gdef\@modulecode{#1}} +\def\moduletitle#1{\gdef\@moduletitle{#1}} +\def\supervisor#1{\gdef\@supervisor{#1}} +\def\supervisoremail#1{\gdef\@supervisoremail{#1}} + +\def\shorttitle#1{\gdef\@shorttitle{#1}} +\def\client#1{\gdef\@client{{\it Client:} & #1 \\}} \gdef\@client{} +\def\configref#1{\gdef\@configref{#1}} +\def\projref#1{\gdef\@projref{{\it Proj. Ref.:} & #1 \\}} \gdef\@projref{} +\def\version#1{\gdef\@version{#1}} +\def\status#1{\gdef\@status{#1}} + + + +% set parskip to zero locally within the lists + +\def\tableofcontents{\section*{\centering Contents} + {\parskip=0pt \@starttoc{toc}}} + +\def\l@part#1#2{\addpenalty{\@secpenalty} + \addvspace{2.25em plus 1pt} \begingroup + \@tempdima 3em \parindent \z@ \rightskip \@pnumwidth \parfillskip +-\@pnumwidth + {\large \bf \leavevmode #1\hfil \hbox to\@pnumwidth{\hss #2}}\par + \nobreak \endgroup} +%\def\l@section#1#2{\addpenalty{\@secpenalty} \addvspace{1.0em plus 1pt} +%\@tempdima 1.5em \begingroup +% \parindent \z@ \rightskip \@pnumwidth +% \parfillskip -\@pnumwidth +% \bf \leavevmode #1\hfil \hbox to\@pnumwidth{\hss #2}\par +% \endgroup} +\def\l@section{\@dottedtocline{1}{1.5em}{2.3em}} +\def\l@subsection{\@dottedtocline{2}{3.8em}{2.9em}} + +\def\l@subsubsection{\@dottedtocline{3}{3.8em}{3.2em}} +\def\l@paragraph{\@dottedtocline{4}{7.0em}{4.1em}} +\def\l@subparagraph{\@dottedtocline{5}{10em}{5em}} + +\def\listoffigures{\section*{List of Figures} + {\parskip=0pt \@starttoc{lof}}} +\def\l@figure{\@dottedtocline{1}{1.5em}{2.3em}} + +\def\listoftables{\section*{List of Tables} + {\parskip=0pt \@starttoc{lot}}} +\let\l@table\l@figure + +%%%% Title Page %%%% + +\def\maketitle{\par + \begingroup + \def\thefootnote{\fnsymbol{footnote}} + \def\@makefnmark{\hbox + to 0pt{$^{\@thefnmark}$\hss}} + \if@twocolumn + \twocolumn[\@maketitle] + \else \newpage + \global\@topnum\z@ \@maketitle \fi\thispagestyle{myheadings}\@thanks + \endgroup + \setcounter{footnote}{0} + \let\maketitle\relax + \let\@maketitle\relax + \gdef\@thanks{}\gdef\@author{}\gdef\@title{}\let\thanks\relax} + +\def\@maketitle{{\headheight 12pt\newpage +\thispagestyle{empty}\c@page\z@ + \null + \vskip 0.4in + \hskip 0.3in +\begin{minipage}{5.8in} + \vskip 0.3in + + \centering\huge{\bf\textcolor{mmpTitle}\@title\par} + + \normalsize + \vskip 0.3in + \centering {\@modulecode} {\@moduletitle} Report + + \vskip 0.4in + \centering Author:\hskip 0.05in \@author\hskip 0.05in (\@authoremail) + \vskip 0.05in + \centering Supervisor:\hskip 0.05in \@supervisor\hskip 0.05in (\@supervisoremail) + + + \vskip 0.3in + \centering {\@date} \vskip 0.05in + \centering Version: {\@version} ({\@status}) + + \vskip 0.6in + This report was submitted as partial fulfilment of a {\@degreetype} degree in + {\@degreeschemetitle} ({\@degreeschemecode}) + + +\end{minipage} + +\vfill +\hskip 0.3in +\begin{minipage}{5.2in} +\begin{tabular}{l} +Department of Computer Science\\ +Aberystwyth University\\ +Aberystwyth \\ +Ceredigion \\ +SY23 3DB \\ +Wales, U.K. \\ +\end{tabular} +\end{minipage} +\newpage}} + +%%%% end of Title Page %%%% + +%%%%% Header and Footer %%%% + +\def\setchapterheaderfooter{ +%%%% The following block affects the header and footer on the first page of a chapter +\fancypagestyle{plain}{% +%\fancyhf{} % clear all header and footer fields +\fancyhead[L]{Chapter\ \thechapter} +\fancyhead[R]{\leftmark} + +\fancyfoot[C]{{\thepage} of \pageref{LastPage}} % except the center +\renewcommand{\headrulewidth}{0.2pt} +\renewcommand{\footrulewidth}{0pt}} +%%%% + +%%%% Setting the header and footer for pages in a section, other than the first page +\fancyhead[L]{Chapter\ \thechapter} +\fancyhead[R]{\leftmark} +\fancyfoot[C]{{\thepage} of \pageref{LastPage}} +\renewcommand{\headrulewidth}{0.2pt} +\renewcommand{\footrulewidth}{0pt} +%%%% +} + + +\def\setemptyheader{ +\fancypagestyle{plain}{% +\fancyhead{}} + +\renewcommand{\headrulewidth}{0pt} +} + +%%%%% End of Header and Footer %%%% + +%%%% Paragraph Indentation %%%%% + +\setlength{\parindent}{0in} + +%%%% end of Paragraph Indentation %%%% diff --git a/docs/report/StylesAndReferences/references.bib b/docs/report/StylesAndReferences/references.bib new file mode 100644 index 0000000..b8d262e --- /dev/null +++ b/docs/report/StylesAndReferences/references.bib @@ -0,0 +1,576 @@ + +@article{dcnn, + title = {Photo {Aesthetics} {Analysis} via {DCNN} {Feature} {Encoding}}, + volume = {19}, + issn = {1941-0077}, + doi = {10.1109/TMM.2017.2687759}, + abstract = {We propose an automatic framework for quality assessment of a photograph as well as analysis of its aesthetic attributes. In contrast to the previous methods that rely on manually designed features to account for photo aesthetics, our method automatically extracts such features using a pretrained deep convolutional neural network (DCNN). To make the DCNN-extracted features more suited to our target tasks of photo quality assessment and aesthetic attribute analysis, we propose a novel feature encoding scheme, which supports vector machines-driven sparse restricted Boltzmann machines, which enhances sparseness of features and discrimination between target classes. Experimental results show that our method outperforms the current state-of-the-art methods in automatic photo quality assessment, and gives aesthetic attribute ratings that can be used for photo editing. We demonstrate that our feature encoding scheme can also be applied to general object classification task to achieve performance gains.}, + number = {8}, + journal = {IEEE Transactions on Multimedia}, + author = {Lee, Hui-Jin and Hong, Ki-Sang and Kang, Henry and Lee, Seungyong}, + month = aug, + year = {2017}, + note = {Conference Name: IEEE Transactions on Multimedia}, + keywords = {Aesthetic attributes, deep convolutional neural network (DCNN), Encoding, feature encoding, Feature extraction, Mathematical model, Neural networks, photo aesthetics, Quality assessment, restricted Boltzmann machines, Support vector machines, Training}, + pages = {1921--1932}, + file = {IEEE Xplore Abstract Record:/home/noble/Zotero/storage/E6YUFLQE/7886320.html:text/html}, +} + +@inproceedings{ava_paper, + title = {{AVA}: {A} large-scale database for aesthetic visual analysis}, + shorttitle = {{AVA}}, + doi = {10.1109/CVPR.2012.6247954}, + abstract = {With the ever-expanding volume of visual content available, the ability to organize and navigate such content by aesthetic preference is becoming increasingly important. While still in its nascent stage, research into computational models of aesthetic preference already shows great potential. However, to advance research, realistic, diverse and challenging databases are needed. To this end, we introduce a new large-scale database for conducting Aesthetic Visual Analysis: AVA. It contains over 250,000 images along with a rich variety of meta-data including a large number of aesthetic scores for each image, semantic labels for over 60 categories as well as labels related to photographic style. We show the advantages of AVA with respect to existing databases in terms of scale, diversity, and heterogeneity of annotations. We then describe several key insights into aesthetic preference afforded by AVA. Finally, we demonstrate, through three applications, how the large scale of AVA can be leveraged to improve performance on existing preference tasks.}, + booktitle = {2012 {IEEE} {Conference} on {Computer} {Vision} and {Pattern} {Recognition}}, + author = {Murray, Naila and Marchesotti, Luca and Perronnin, Florent}, + month = jun, + year = {2012}, + note = {ISSN: 1063-6919}, + keywords = {Communities, Image color analysis, Semantics, Social network services, Visual databases, Visualization}, + pages = {2408--2415}, + file = {IEEE Xplore Abstract Record:/home/noble/Zotero/storage/HE3EFVJV/6247954.html:text/html}, +} + +@misc{kong_photo_2022, + title = {Photo {Aesthetics} {Ranking} {Network} with {Attributes} and {Content} {Adaptation}}, + url = {https://github.com/aimerykong/deepImageAestheticsAnalysis}, + abstract = {ECCV2016 - fine-grained photo aesthetics rating with interpretability}, + urldate = {2022-02-11}, + author = {Kong, Shu}, + month = jan, + year = {2022}, + note = {original-date: 2016-06-05T06:08:10Z}, +} + +@misc{pytorch, + title = {{PyTorch}.org}, + url = {https://www.pytorch.org}, + abstract = {An open source machine learning framework that accelerates the path from research prototyping to production deployment.}, + language = {en}, + urldate = {2022-02-11}, + author = {{Adam Paszke} and {Sam Gross} and {Soumith Chintala} and {Gregory Chanan}}, + file = {Snapshot:/home/noble/Zotero/storage/HPSFJGU3/pytorch.org.html:text/html}, +} + +@misc{opencv, + title = {{OpenCV}}, + url = {https://opencv.org}, + abstract = {OpenCV provides a real-time optimized Computer Vision library, tools, and hardware. It also supports model execution for Machine Learning (ML) and Artificial Intelligence (AI).}, + language = {en-US}, + urldate = {2022-02-11}, + journal = {OpenCV}, + author = {{Intel Corporation} and {Willow Garage} and {Itseez}}, + file = {Snapshot:/home/noble/Zotero/storage/JYX6KIPC/opencv.org.html:text/html}, +} + +@misc{ava_dataset, + title = {{AVA} {Dataset}}, + url = {https://github.com/imfing/ava_downloader}, + abstract = {:arrow\_double\_down: Download AVA dataset (A Large-Scale Database for Aesthetic Visual Analysis)}, + urldate = {2022-02-11}, + author = {Fing}, + month = feb, + year = {2022}, + note = {original-date: 2016-11-13T02:20:32Z}, + keywords = {aesthetic-visual-analysis, ava, computer-vision, dataset, python}, +} + +@misc{noauthor_image_2022, + title = {Image {Quality} {Assessment}}, + copyright = {Apache-2.0}, + url = {https://github.com/idealo/image-quality-assessment}, + abstract = {Convolutional Neural Networks to predict the aesthetic and technical quality of images.}, + urldate = {2022-02-11}, + publisher = {idealo}, + month = feb, + year = {2022}, + note = {original-date: 2018-06-12T14:46:09Z}, + keywords = {computer-vision, aws, convolutional-neural-networks, deep-learning, e-commerce, idealo, image-quality-assessment, keras, machine-learning, mobilenet, neural-network, nima, tensorflow}, +} + +@misc{tensorflow, + title = {{TensorFlow}.org}, + url = {https://www.tensorflow.org/}, + urldate = {2022-02-11}, + author = {{Google Brain Team}}, +} + +@misc{noauthor_most_nodate, + title = {Most used social media 2021}, + url = {https://www.statista.com/statistics/272014/global-social-networks-ranked-by-number-of-users/}, + abstract = {Facebook, YouTube, and WhatsApp are the most popular social networks worldwide, each with at least two billion active users.}, + language = {en}, + urldate = {2022-04-26}, + journal = {Statista}, + file = {Snapshot:/home/noble/Zotero/storage/WQGJ88E7/global-social-networks-ranked-by-number-of-users.html:text/html}, +} + +@misc{trophy_camera, + title = {Trophy {Camera}, 2017-2022}, + url = {https://driesdepoorter.be/trophy-camera/}, + abstract = {‘Trophy Camera’ is a photo camera that can only make award winning pictures. Just take your photo and check if the camera sees your picture as award winning. This A.I. powered camera has been trained by all previous winning World Press Photo’s of the year. Based on the identification of labeled patterns, the camera is…}, + language = {en-US}, + urldate = {2022-04-26}, + journal = {Dries Depoorter}, + author = {Depoorter, Dries and Pinckers, Max}, + file = {Snapshot:/home/noble/Zotero/storage/PV8ZQT4J/trophy-camera.html:text/html}, +} + +@misc{trophy_camera_site, + title = {"trophy.camera"}, + url = {https://trophy.camera/}, + urldate = {2022-04-27}, + author = {Depoorter, Dries and Pinckers, Max}, + file = {"trophy.camera":/home/noble/Zotero/storage/7PYMYIDB/trophy.camera.html:text/html}, +} + +@misc{wpp, + title = {Home {\textbar} {World} {Press} {Photo}}, + url = {https://www.worldpressphoto.org/}, + urldate = {2022-04-27}, + file = {Home | World Press Photo:/home/noble/Zotero/storage/B8EU43WT/www.worldpressphoto.org.html:text/html}, +} + +@misc{pyis_laplace, + title = {Blur detection with {OpenCV}}, + url = {https://www.pyimagesearch.com/2015/09/07/blur-detection-with-opencv/}, + abstract = {In this tutorial, I will teach you how to detect the amount of blur in an image using OpenCV and Python. Perform blur detection using the OpenCV library.}, + language = {en-US}, + urldate = {2022-04-27}, + journal = {PyImageSearch}, + month = sep, + year = {2015}, + file = {Snapshot:/home/noble/Zotero/storage/KI46W39W/blur-detection-with-opencv.html:text/html}, +} + +@misc{pyis_fft, + title = {{OpenCV} {Fast} {Fourier} {Transform} ({FFT}) for blur detection in images and video streams}, + url = {https://www.pyimagesearch.com/2020/06/15/opencv-fast-fourier-transform-fft-for-blur-detection-in-images-and-video-streams/}, + abstract = {In this tutorial, you will learn how to use OpenCV and the Fast Fourier Transform (FFT) to perform blur detection in images and real-time video streams.}, + language = {en-US}, + urldate = {2022-04-27}, + journal = {PyImageSearch}, + month = jun, + year = {2020}, +} + +@misc{python, + title = {Python.org}, + url = {https://www.python.org/}, + abstract = {The official home of the Python Programming Language}, + language = {en}, + urldate = {2022-04-27}, + journal = {Python.org}, + file = {Snapshot:/home/noble/Zotero/storage/PXIQFZZL/www.python.org.html:text/html}, +} + +@misc{keras, + title = {Keras: the {Python} deep learning {API}}, + url = {https://keras.io/}, + urldate = {2022-04-27}, + file = {Keras\: the Python deep learning API:/home/noble/Zotero/storage/98IXDCT3/keras.io.html:text/html}, +} + +@misc{google_photos, + title = {Updating {Google} {Photos}’ storage policy to build for the future}, + url = {https://blog.google/products/photos/storage-changes/}, + abstract = {In order to welcome even more of your memories and build Google Photos for the future, we are changing our unlimited High quality storage policy.}, + language = {en-us}, + urldate = {2022-05-02}, + journal = {Google}, + month = nov, + year = {2020}, + file = {Snapshot:/home/noble/Zotero/storage/PBDLGX6I/storage-changes.html:text/html}, +} + +@misc{google_workspace, + title = {G {Suite}'s unlimited {Google} {Drive} storage will be discontinued with {Workspace}}, + url = {https://9to5google.com/2020/10/08/google-workspace-drive-storage-limits/}, + abstract = {While G Suite offered it to businesses, Google Workspace has completely dropped the option to have unlimited storage on Google Drive.}, + language = {en-US}, + urldate = {2022-05-02}, + journal = {9to5Google}, + author = {Schoon, Ben}, + month = oct, + year = {2020}, + file = {Snapshot:/home/noble/Zotero/storage/RCM4U3V4/google-workspace-drive-storage-limits.html:text/html}, +} + +@misc{instagram_aesthetic, + title = {Why {Your} {Instagram} {Profile} is the {New} {Home} {Page}}, + url = {https://later.com/blog/instagram-profile-home-page/}, + abstract = {It's time to treat your Instagram profile as seriously as the home page of your website. Learn how to optimize your Instagram profile to convert visitors into followers!}, + language = {en}, + urldate = {2022-05-02}, + file = {Snapshot:/home/noble/Zotero/storage/HEUXGVXA/instagram-profile-home-page.html:text/html}, +} + +@misc{instagram_planner, + title = {{PREVIEW} - {Plan} your {Instagram} – {Apps} on {Google} {Play}}, + url = {https://play.google.com/store/apps/details?id=com.sensio.instapreview&hl=en_GB&gl=GB}, + abstract = {ALL-IN-ONE Instagram tool: Presets, themes, plan, analytics, schedule \& repost.}, + language = {en}, + urldate = {2022-05-02}, + file = {Snapshot:/home/noble/Zotero/storage/8KHZSN73/details.html:text/html}, +} + +@misc{unum, + title = {{UNUM} — {World}'s easiest marketing tool}, + url = {https://www.unum.la/}, + abstract = {Save 7 hours every week with UNUM — your all-in-one design, planning, and marketing platform for your most important channels. Loved by millions of creators, small businesses, agencies, and marketing teams worldwide.}, + urldate = {2022-05-02}, + file = {Snapshot:/home/noble/Zotero/storage/SK45SUA4/www.unum.la.html:text/html}, +} + +@misc{golden_ratio, + title = {Golden ratio: {A} beginner's guide {\textbar} {Adobe}}, + shorttitle = {Golden ratio}, + url = {https://www.adobe.com/creativecloud/design/discover/golden-ratio.html}, + abstract = {The golden ration is one of the most famous ratios in mathematics and design. Learn more about the golden ratio and its role in art and design.}, + language = {en-US}, + urldate = {2022-05-02}, + file = {Snapshot:/home/noble/Zotero/storage/6CMQQJM8/golden-ratio.html:text/html}, +} + +@misc{symmetry, + title = {Symmetry in {Photography}: {The} {Ultimate} {Guide} to {Using} {Symmetry} in {Your} {Photos}}, + shorttitle = {Symmetry in {Photography}}, + url = {https://www.photoworkout.com/symmetry-in-photography/}, + abstract = {Symmetry in photography makes for bold, in-your-face compositions. Discover how to use symmetry for the best results!}, + language = {en-US}, + urldate = {2022-05-02}, + journal = {PhotoWorkout}, + month = sep, + year = {2020}, + file = {Snapshot:/home/noble/Zotero/storage/5KV5F7K8/symmetry-in-photography.html:text/html}, +} + +@misc{rule-of-thirds, + title = {What is the {Rule} of {Thirds} and {How} to {Use} it to {Improve} {Your} {Photos}}, + url = {https://photographylife.com/the-rule-of-thirds}, + abstract = {Read this detailed article to understand how the rule of thirds works, when to and when not to use it when composing images.}, + language = {en-US}, + urldate = {2022-05-02}, + journal = {Photography Life}, + month = mar, + year = {2018}, + file = {Snapshot:/home/noble/Zotero/storage/GKPUDLZK/the-rule-of-thirds.html:text/html}, +} + +@misc{dof, + title = {Understanding shallow depth of field photography {\textbar} {Adobe}}, + url = {https://www.adobe.com/creativecloud/photography/discover/shallow-depth-of-field.html}, + abstract = {Shallow depth of field is achieved by shooting photographs with a low f-number to let in more light. Learn more about shallow depth of field today.}, + language = {en-US}, + urldate = {2022-05-02}, + file = {Snapshot:/home/noble/Zotero/storage/LKK7R2RN/shallow-depth-of-field.html:text/html}, +} + +@misc{flickr, + title = {Flickr}, + url = {https://www.flickr.com}, + urldate = {2022-05-02}, + file = {2007 Spencer Platt WY | World Press Photo:/home/noble/Zotero/storage/I8L8PC7M/1.html:text/html}, +} + +@misc{aqa-on-ava, + title = {Papers with {Code} - {AVA} {Benchmark} ({Aesthetics} {Quality} {Assessment})}, + url = {https://paperswithcode.com/sota/aesthetics-quality-assessment-on-ava}, + abstract = {The current state-of-the-art on AVA is MP\_adam. See a full comparison of 9 papers with code.}, + language = {en}, + urldate = {2022-05-03}, + file = {Snapshot:/home/noble/Zotero/storage/LMRI5CPK/aesthetics-quality-assessment-on-ava.html:text/html}, +} + +@misc{archillect, + title = {Archillect}, + url = {https://archillect.com/}, + abstract = {The Ocular Engine}, + language = {en}, + urldate = {2022-05-03}, + file = {Snapshot:/home/noble/Zotero/storage/Q8V5TTS5/archillect.com.html:text/html}, +} + +@misc{noauthor_theres_nodate, + title = {There’s a way to pick the absolute best images for your content: {Apply} {AI} {\textbar} {TechCrunch}}, + url = {https://techcrunch.com/2020/10/01/theres-a-way-to-pick-the-absolute-best-images-for-your-content-apply-ai/?guccounter=1}, + urldate = {2022-05-03}, + file = {There’s a way to pick the absolute best images for your content\: Apply AI | TechCrunch:/home/noble/Zotero/storage/TKV3EA5U/theres-a-way-to-pick-the-absolute-best-images-for-your-content-apply-ai.html:text/html}, +} + +@article{intrinsic_image_popularity, + title = {Intrinsic {Image} {Popularity} {Assessment}}, + url = {http://arxiv.org/abs/1907.01985}, + doi = {10.1145/3343031.3351007}, + abstract = {The goal of research in automatic image popularity assessment (IPA) is to develop computational models that can accurately predict the potential of a social image to go viral on the Internet. Here, we aim to single out the contribution of visual content to image popularity, i.e., intrinsic image popularity. Specifically, we first describe a probabilistic method to generate massive popularity-discriminable image pairs, based on which the first large-scale image database for intrinsic IPA (I2PA) is established. We then develop computational models for I2PA based on deep neural networks, optimizing for ranking consistency with millions of popularity-discriminable image pairs. Experiments on Instagram and other social platforms demonstrate that the optimized model performs favorably against existing methods, exhibits reasonable generalizability on different databases, and even surpasses human-level performance on Instagram. In addition, we conduct a psychophysical experiment to analyze various aspects of human behavior in I2PA.}, + language = {en}, + urldate = {2022-05-03}, + journal = {Proceedings of the 27th ACM International Conference on Multimedia}, + author = {Ding, Keyan and Ma, Kede and Wang, Shiqi}, + month = oct, + year = {2019}, + note = {arXiv: 1907.01985}, + keywords = {Computer Science - Computer Vision and Pattern Recognition, Computer Science - Multimedia}, + pages = {1979--1987}, + file = {Ding et al. - 2019 - Intrinsic Image Popularity Assessment.pdf:/home/noble/Zotero/storage/69F498QV/Ding et al. - 2019 - Intrinsic Image Popularity Assessment.pdf:application/pdf}, +} + +@misc{pytorch-rocm, + title = {{PyTorch} for {AMD} {ROCm}™ {Platform} now available as {Python} package}, + url = {https://pytorch.org/blog/pytorch-for-amd-rocm-platform-now-available-as-python-package/}, + abstract = {An open source machine learning framework that accelerates the path from research prototyping to production deployment.}, + language = {en}, + urldate = {2022-05-03}, + file = {Snapshot:/home/noble/Zotero/storage/K88CKU33/pytorch-for-amd-rocm-platform-now-available-as-python-package.html:text/html}, +} + +@misc{gcp-gpu, + title = {Create a {VM} with attached {GPUs} {\textbar} {Compute} {Engine} {Documentation} {\textbar} {Google} {Cloud}}, + url = {https://cloud.google.com/compute/docs/gpus/create-vm-with-gpus}, + language = {en}, + urldate = {2022-05-03}, + file = {Snapshot:/home/noble/Zotero/storage/EIDYTHME/create-vm-with-gpus.html:text/html}, +} + +@misc{slurm, + title = {Slurm {Workload} {Manager} - {Overview}}, + url = {https://slurm.schedmd.com/overview.html}, + urldate = {2022-05-03}, + file = {Slurm Workload Manager - Overview:/home/noble/Zotero/storage/53EBVW79/overview.html:text/html}, +} + +@misc{anaconda, + title = {Anaconda {\textbar} {The} {World}'s {Most} {Popular} {Data} {Science} {Platform}}, + url = {https://www.anaconda.com/}, + abstract = {Anaconda is the birthplace of Python data science. We are a movement of data scientists, data-driven enterprises, and open source communities.}, + language = {en}, + urldate = {2022-05-03}, + journal = {Anaconda}, + file = {Snapshot:/home/noble/Zotero/storage/QI8YM43G/www.anaconda.com.html:text/html}, +} + +@misc{rocm-ml, + title = {{ROCm}™: {Machine} {Learning}}, + shorttitle = {{ROCm}™}, + url = {https://www.amd.com/en/graphics/servers-solutions-rocm-ml}, + language = {en}, + urldate = {2022-05-03}, + file = {Snapshot:/home/noble/Zotero/storage/FP6GHSEP/servers-solutions-rocm-ml.html:text/html}, +} + +@misc{pyis-cnn, + title = {{PyTorch}: {Training} your first {Convolutional} {Neural} {Network} ({CNN})}, + shorttitle = {{PyTorch}}, + url = {https://www.pyimagesearch.com/2021/07/19/pytorch-training-your-first-convolutional-neural-network-cnn/}, + abstract = {In this tutorial, you will receive a gentle introduction to training your first Convolutional Neural Network (CNN) using the PyTorch deep learning library.}, + language = {en-US}, + urldate = {2022-05-04}, + journal = {PyImageSearch}, + month = jul, + year = {2021}, + file = {Snapshot:/home/noble/Zotero/storage/A79TLMS6/pytorch-training-your-first-convolutional-neural-network-cnn.html:text/html}, +} + +@misc{dpchallenge, + title = {{DPChallenge} - {A} {Digital} {Photography} {Contest}}, + url = {https://www.dpchallenge.com/}, + urldate = {2022-05-04}, + file = {DPChallenge - A Digital Photography Contest:/home/noble/Zotero/storage/8HYS69YJ/www.dpchallenge.com.html:text/html}, +} + +@misc{wpp-spencer, + title = {2007 {Spencer} {Platt} {WY} {\textbar} {World} {Press} {Photo}}, + url = {https://www.worldpressphoto.org/collection/photo-contest/2007/spencer-platt/1}, + urldate = {2022-05-02}, +} + +@article{aadb_paper, + title = {Photo {Aesthetics} {Ranking} {Network} with {Attributes} and {Content} {Adaptation}}, + url = {http://arxiv.org/abs/1606.01621}, + abstract = {Real-world applications could benefit from the ability to automatically generate a fine-grained ranking of photo aesthetics. However, previous methods for image aesthetics analysis have primarily focused on the coarse, binary categorization of images into high- or low-aesthetic categories. In this work, we propose to learn a deep convolutional neural network to rank photo aesthetics in which the relative ranking of photo aesthetics are directly modeled in the loss function. Our model incorporates joint learning of meaningful photographic attributes and image content information which can help regularize the complicated photo aesthetics rating problem.}, + language = {en}, + urldate = {2022-05-04}, + journal = {arXiv:1606.01621 [cs]}, + author = {Kong, Shu and Shen, Xiaohui and Lin, Zhe and Mech, Radomir and Fowlkes, Charless}, + month = jul, + year = {2016}, + note = {arXiv: 1606.01621}, + keywords = {Computer Science - Computer Vision and Pattern Recognition, Computer Science - Multimedia, Computer Science - Information Retrieval}, + file = {Kong et al. - 2016 - Photo Aesthetics Ranking Network with Attributes a.pdf:/home/noble/Zotero/storage/EXJXBA6X/Kong et al. - 2016 - Photo Aesthetics Ranking Network with Attributes a.pdf:application/pdf}, +} + +@misc{ml-module, + title = {Current {Modules} by {Department} : {Modules} , {Aberystwyth} {University}}, + shorttitle = {Current {Modules} by {Department}}, + url = {https://www.aber.ac.uk/en/modules/deptcurrent/CS36220/}, + abstract = {Information about current modules offered available at Aberystwyth University, listed by department.}, + language = {en}, + urldate = {2022-05-04}, + author = {Team, Aberystwyth University Web}, + note = {Last Modified: 2022-05-04}, + file = {Snapshot:/home/noble/Zotero/storage/YEJGV5C2/CS36220.html:text/html}, +} + +@misc{stanford_dl, + title = {Lecture 8 {\textbar} {Deep} {Learning} {Software}}, + url = {https://www.youtube.com/watch?v=6SlgtELqOWc}, + abstract = {In Lecture 8 we discuss the use of different software packages for deep learning, focusing on TensorFlow and PyTorch. We also discuss some differences between CPUs and GPUs. + +Keywords: CPU vs GPU, TensorFlow, Keras, Theano, Torch, PyTorch, Caffe, Caffe2, dynamic vs static computational graphs + +Slides: http://cs231n.stanford.edu/slides/201... + +-------------------------------------------------------------------------------------- + +Convolutional Neural Networks for Visual Recognition + +Instructors: +Fei-Fei Li: http://vision.stanford.edu/feifeili/ +Justin Johnson: http://cs.stanford.edu/people/jcjohns/ +Serena Yeung: http://ai.stanford.edu/{\textasciitilde}syyeung/ + +Computer Vision has become ubiquitous in our society, with applications in search, image understanding, apps, mapping, medicine, drones, and self-driving cars. Core to many of these applications are visual recognition tasks such as image classification, localization and detection. Recent developments in neural network (aka “deep learning”) approaches have greatly advanced the performance of these state-of-the-art visual recognition systems. This lecture collection is a deep dive into details of the deep learning architectures with a focus on learning end-to-end models for these tasks, particularly image classification. From this lecture collection, students will learn to implement, train and debug their own neural networks and gain a detailed understanding of cutting-edge research in computer vision. + +Website: +http://cs231n.stanford.edu/ + +For additional learning opportunities please visit: +http://online.stanford.edu/}, + urldate = {2022-05-04}, + author = {{Stanford University School of Engineering}}, + month = aug, + year = {2017}, +} + +@misc{stanford_cnn, + title = {Lecture 9 {\textbar} {CNN} {Architectures}}, + url = {https://www.youtube.com/watch?v=DAOcjicFr1Y}, + abstract = {In Lecture 9 we discuss some common architectures for convolutional neural networks. We discuss architectures which performed well in the ImageNet challenges, including AlexNet, VGGNet, GoogLeNet, and ResNet, as well as other interesting models. + +Keywords: AlexNet, VGGNet, GoogLeNet, ResNet, Network in Network, Wide ResNet, ResNeXT, Stochastic Depth, DenseNet, FractalNet, SqueezeNet + +Slides: http://cs231n.stanford.edu/slides/201... + +-------------------------------------------------------------------------------------- + +Convolutional Neural Networks for Visual Recognition + +Instructors: +Fei-Fei Li: http://vision.stanford.edu/feifeili/ +Justin Johnson: http://cs.stanford.edu/people/jcjohns/ +Serena Yeung: http://ai.stanford.edu/{\textasciitilde}syyeung/ + +Computer Vision has become ubiquitous in our society, with applications in search, image understanding, apps, mapping, medicine, drones, and self-driving cars. Core to many of these applications are visual recognition tasks such as image classification, localization and detection. Recent developments in neural network (aka “deep learning”) approaches have greatly advanced the performance of these state-of-the-art visual recognition systems. This lecture collection is a deep dive into details of the deep learning architectures with a focus on learning end-to-end models for these tasks, particularly image classification. From this lecture collection, students will learn to implement, train and debug their own neural networks and gain a detailed understanding of cutting-edge research in computer vision. + +Website: +http://cs231n.stanford.edu/ + +For additional learning opportunities please visit: +http://online.stanford.edu/}, + urldate = {2022-05-04}, + author = {{Stanford University School of Engineering}}, + month = aug, + year = {2017}, +} + +@misc{pytorch-training, + title = {Training with {PyTorch} — {PyTorch} {Tutorials} 1.11.0+cu102 documentation}, + url = {https://pytorch.org/tutorials/beginner/introyt/trainingyt.html}, + urldate = {2022-05-04}, + file = {Training with PyTorch — PyTorch Tutorials 1.11.0+cu102 documentation:/home/noble/Zotero/storage/ZPY5XLIN/trainingyt.html:text/html}, +} + +@misc{imagenet, + title = {{ImageNet}}, + url = {https://www.image-net.org/index.php}, + urldate = {2022-05-04}, + file = {ImageNet:/home/noble/Zotero/storage/AZR8PDKP/index.html:text/html}, +} + +@misc{skimage, + title = {skimage — skimage v0.19.2 docs}, + url = {https://scikit-image.org/docs/stable/api/skimage.html}, + urldate = {2022-05-04}, + file = {skimage — skimage v0.19.2 docs:/home/noble/Zotero/storage/K8SAES3B/skimage.html:text/html}, +} + +@misc{unsplash, + title = {Photo by {ZHENYU} {LUO} on {Unsplash}}, + url = {https://unsplash.com/photos/mhvL46eQis0}, + abstract = {Download this photo by ZHENYU LUO on Unsplash}, + language = {en}, + urldate = {2022-05-05}, + author = {Unsplash}, + file = {Snapshot:/home/noble/Zotero/storage/EBF2RRHE/mhvL46eQis0.html:text/html}, +} + +@misc{gimp, + title = {{GIMP}}, + url = {https://www.gimp.org/}, + abstract = {GIMP - The GNU Image Manipulation Program: The Free and Open Source Image Editor}, + language = {en}, + urldate = {2022-05-05}, + journal = {GIMP}, + file = {Snapshot:/home/noble/Zotero/storage/KNSWAL4N/www.gimp.org.html:text/html}, +} + +@misc{pyis_contrast, + title = {Detecting low contrast images with {OpenCV}, scikit-image, and {Python}}, + url = {https://www.pyimagesearch.com/2021/01/25/detecting-low-contrast-images-with-opencv-scikit-image-and-python/}, + abstract = {In this tutorial you will learn how to detect low contrast images using OpenCV and scikit-image.}, + language = {en-US}, + urldate = {2022-05-06}, + journal = {PyImageSearch}, + month = jan, + year = {2021}, + file = {Snapshot:/home/noble/Zotero/storage/WNHWPBW8/detecting-low-contrast-images-with-opencv-scikit-image-and-python.html:text/html}, +} + +@misc{pyis_keras, + title = {Regression with {Keras}}, + url = {https://www.pyimagesearch.com/2019/01/21/regression-with-keras/}, + abstract = {In this tutorial you will learn how to perform regression using Keras. You will learn how to train a Keras neural network for regression and continuous value prediction, specifically in the context of house price prediction.}, + language = {en-US}, + urldate = {2022-05-06}, + journal = {PyImageSearch}, + month = jan, + year = {2019}, + file = {Snapshot:/home/noble/Zotero/storage/DBW7BKZV/regression-with-keras.html:text/html}, +} + +@misc{pyis_keras_cnn, + title = {Keras, {Regression}, and {CNNs}}, + url = {https://www.pyimagesearch.com/2019/01/28/keras-regression-and-cnns/}, + abstract = {In this tutorial you will learn how to train a Convolutional Neural Network (CNN) for regression prediction with Keras and deep learning.}, + language = {en-US}, + urldate = {2022-05-06}, + journal = {PyImageSearch}, + month = jan, + year = {2019}, + file = {Snapshot:/home/noble/Zotero/storage/8CWZPFAB/keras-regression-and-cnns.html:text/html}, +} + +@misc{house_dataset, + title = {House {Prices} - {Advanced} {Regression} {Techniques}}, + url = {https://kaggle.com/competitions/house-prices-advanced-regression-techniques}, + abstract = {Predict sales prices and practice feature engineering, RFs, and gradient boosting}, + language = {en}, + urldate = {2022-05-06}, + file = {Snapshot:/home/noble/Zotero/storage/IYF6ZKAL/data.html:text/html}, +} + +@misc{pytorch-resnet, + title = {{PyTorch}: {ResNet}}, + url = {https://pytorch.org/hub/pytorch_vision_resnet/}, + abstract = {An open source machine learning framework that accelerates the path from research prototyping to production deployment.}, + language = {en}, + urldate = {2022-05-06}, + file = {Snapshot:/home/noble/Zotero/storage/ZRCB5F9V/pytorch_vision_resnet.html:text/html}, +} + +@misc{pyis_pytorch_transferlearning, + title = {{PyTorch}: {Transfer} {Learning} and {Image} {Classification} - {PyImageSearch}}, + url = {https://pyimagesearch.com/2021/10/11/pytorch-transfer-learning-and-image-classification/}, + urldate = {2022-05-06}, + file = {PyTorch\: Transfer Learning and 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\ No newline at end of file diff --git a/docs/report/img/diagrams/filter_brightness.pdf b/docs/report/img/diagrams/filter_brightness.pdf new file mode 100644 index 0000000..3b3b7a7 --- /dev/null +++ b/docs/report/img/diagrams/filter_brightness.pdf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b0b86af3bf9576bc229b7973f3255c3f0ddaa9819e5536bcf78d8f32d6fedd89 +size 41265 diff --git a/docs/report/img/diagrams/filter_brightness.uml b/docs/report/img/diagrams/filter_brightness.uml new file mode 100644 index 0000000..6a6a184 --- /dev/null +++ b/docs/report/img/diagrams/filter_brightness.uml @@ -0,0 +1,16 @@ +@startuml +start +:Input: list of paths; +if (Does the list only have one item which is also a directory?) then (yes) + :List files inside the directory; + :Overwrite the original list with those new files; +else (no) +endif +if (Ignore video files?) then (yes) + :Add each file that ends in an image file extension to a new list; +else (no) + : Add each file that ends in an image or a video file extension to a new list; +endif +:Output: list of filtered paths; +stop +@enduml diff --git a/docs/report/img/diagrams/filter_paths.pdf b/docs/report/img/diagrams/filter_paths.pdf new file mode 100644 index 0000000..164991a --- /dev/null +++ b/docs/report/img/diagrams/filter_paths.pdf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:349a3f9595276e1d3bb95562628ccab22065550b263570d0c782dc993e8189c0 +size 35668 diff --git a/docs/report/img/diagrams/filter_paths.svg b/docs/report/img/diagrams/filter_paths.svg new file mode 100644 index 0000000..77618fa --- /dev/null +++ b/docs/report/img/diagrams/filter_paths.svg @@ -0,0 +1,28 @@ +Input: list of pathsList files inside the directoryOverwrite the original list with those new filesyesDoes the list only have one item which is also a directory?noIgnore video files?yesnoAdd each file that ends in an image file extension to a new listAdd each file that ends in an image or a video file extension to a new listOutput: list of filtered paths \ No newline at end of file diff --git a/docs/report/img/diagrams/filter_paths.uml b/docs/report/img/diagrams/filter_paths.uml new file mode 100644 index 0000000..6a6a184 --- /dev/null +++ b/docs/report/img/diagrams/filter_paths.uml @@ -0,0 +1,16 @@ +@startuml +start +:Input: list of paths; +if (Does the list only have one item which is also a directory?) then (yes) + :List files inside the directory; + :Overwrite the original list with those new files; +else (no) +endif +if (Ignore video files?) then (yes) + :Add each file that ends in an image file extension to a new list; +else (no) + : Add each file that ends in an image or a video file extension to a new list; +endif +:Output: list of filtered paths; +stop +@enduml diff --git a/docs/report/img/diagrams/load_config.pdf b/docs/report/img/diagrams/load_config.pdf new file mode 100644 index 0000000..dd17ff8 --- /dev/null +++ b/docs/report/img/diagrams/load_config.pdf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5e6f6eeb6821a3023c3b0d5ba77d489288ae5947816c4a0332a8811b54fe6824 +size 30434 diff --git a/docs/report/img/diagrams/load_config.svg b/docs/report/img/diagrams/load_config.svg new file mode 100644 index 0000000..3d9f782 --- /dev/null +++ b/docs/report/img/diagrams/load_config.svg @@ -0,0 +1,29 @@ +Input: path to a config fileDoes the path exist?yesnoDoes the path end with .yml or .yaml?yesnoAttempt to read the fileOutput: dictionary of file contentsError: File is not a YAML fileError: File doesn't exist \ No newline at end of file diff --git a/docs/report/img/diagrams/load_config.uml b/docs/report/img/diagrams/load_config.uml new file mode 100644 index 0000000..fe24b83 --- /dev/null +++ b/docs/report/img/diagrams/load_config.uml @@ -0,0 +1,17 @@ +@startuml +start +:Input: path to a config file; +if (Does the path exist?) then (yes) + if (Does the path end with .yml or .yaml?) then (yes) + :Attempt to read the file; + :Output: dictionary of file contents; + stop + else (no) + #pink:Error: File is not a YAML file; + kill + endif +else (no) + #pink:Error: File doesn't exist; + kill +endif +@enduml diff --git a/docs/report/img/diagrams/load_video.svg b/docs/report/img/diagrams/load_video.svg new file mode 100644 index 0000000..e69de29 diff --git a/docs/report/img/diagrams/load_video.uml b/docs/report/img/diagrams/load_video.uml new file mode 100644 index 0000000..e69de29 diff --git a/docs/report/img/diagrams/umlToPdf.sh b/docs/report/img/diagrams/umlToPdf.sh new file mode 100644 index 0000000..6f80983 --- /dev/null +++ b/docs/report/img/diagrams/umlToPdf.sh @@ -0,0 +1,9 @@ +dir=$(cd -P -- "$(dirname -- "$0")" && pwd -P) +echo $dir +for path in $dir/*.uml; do + echo $path + filename=$(basename -- "$path") + filename_noext="${filename%.*}" + cat "$dir/$filename" | docker run --rm -i think/plantuml > $filename_noext.svg +done +inkscape -C $dir/*.svg --export-type=pdf diff --git a/docs/report/img/dof.jpg 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https://git-lfs.github.com/spec/v1 +oid sha256:7383a214ab931c231766b13e8cfbe077eda8b500af0acceeafc712bbaf6b6842 +size 19710363 diff --git a/docs/report/osp1-mmp-report.tex b/docs/report/osp1-mmp-report.tex new file mode 100755 index 0000000..0cb5bb5 --- /dev/null +++ b/docs/report/osp1-mmp-report.tex @@ -0,0 +1,212 @@ +\documentclass[11pt,a4paper]{report} + +% Aberstwyth MMP Project Report Template for LaTeX +% +% Authors: Neil Taylor (nst@aber.ac.uk) and Dr. Hannah Dee (hmd1@aber.ac.uk) +% +% This has been adapted from the Leeds Thesis template and the +% Group Project template for Computer Science in Aberystywth University. +% +% All comments and suggestions welcome. +% +% Template designed to be used with pdflatex: it may need alteration to +% run with a different LaTeX engine. +% +% Note - this is offered as a starting point for your work. You are not +% required to use this template and can choose to create your own document +% without it. + +% This template is suitable for students with an engineering-style project, +% which will be most students in the department. If your project is a research-oriented +% project, look at the alternative template. + +% To build document on the unix command line, run four commands: + +% pdflatex mmp-report +% bibtex mmp-report +% pdflatex mmp-report +% pdflatex mmp-report + +% you will end up with mmp-report.pdf. Before submitting, add your user ID as a prefix, +% e.g. abc01-mmp-report.pdf +\usepackage{StylesAndReferences/mmp-report} + +% the following packages are used for citations - You only need to include one. +% +% Use the cite package if you are using the numeric style (e.g. IEEEannot). +% Use the natbib package if you are using the author-date style (e.g. authordate2annot). +% Only use one of these and comment out or remove the other one. +\usepackage{cite} +%\usepackage{natbib} + +% Use en-GB locale formatting for dates +\usepackage[en-GB]{datetime2} +\DTMlangsetup[en-GB]{ord=raise} + +% plantuml +\usepackage{plantuml} + +% load images path +\graphicspath{ {./img} } +%%%% Title and Section Colours %%%% +% Modify these values to change the colours used for title, sections and subsections. +% Each value is a range of 0-255 in RGB colourspace. +% Idea courtesy of discussion at +% https://www.overleaf.com/learn/latex/Using_colours_in_LaTeX +% and +% https://tex.stackexchange.com/questions/75667/change-colour-on-chapter-section-headings-lyx +% +% If you prefer to have black headers, then comment out the following lines +\definecolor{mmpTitle}{RGB}{10, 85, 145} +\definecolor{mmpSection}{RGB}{10,85,155} +\definecolor{mmpSubsection}{RGB}{79,129,189} + +\chapterfont{\color{mmpTitle}} % sets colour of chapters +\sectionfont{\color{mmpSection}} % sets colour of sections +\subsectionfont{\color{mmpSubsection}} % sets colour subsections +\subsubsectionfont{\color{mmpSubsection}} % sets colour subsections + +%%%% end of Title and Section Colours %%%% + + +%%%% Report Type %%%% +%% comment/uncomment depending on the type of report you want to generate +%\reporttype{Engineering} +\reporttype{Research} +%%%% end of Report Type %%%% + + +\begin{document} + +%TC:ignore + +% all of the include directives below refer to tex files +% so \include{cover} includes cover.tex - to change the content, +% edit the tex file + +\raggedright +\pagenumbering{roman} + +% This is the front page +\include{FrontMatter/cover} + +% Set up page numbering +\pagestyle{empty} + +% declarations of originality +\include{FrontMatter/declaration} + +\include{FrontMatter/acknowledgements} % Acknowledgements + +\include{FrontMatter/abstract} % Abstract + +\pagenumbering{roman} +\pagestyle{fancy} +\fancyhead{} +\fancyfoot[C]{\thepage} +\renewcommand{\headrulewidth}{0 pt} +\renewcommand{\chaptermark}[1]{\markboth{#1}{}} + +\tableofcontents +\newpage +\listoffigures % comment out this line if you don't have any figures / graphics +\newpage +\listoftables % comment out this line if you don't have any tables +\newpage + +% Set up page numbering +\pagenumbering{arabic} + +\setchapterheaderfooter + +%TC:endignore + +% Problem Analysis 15% +% Technical Work 35% +% Critical Evaluation and Insight 10% +% Dissertation Presentation Quality 10% + +% Word count break down: +% Problem Analysis 25% 2727 words +% Technical Work 58.3..% 6400 words +% Critical Evaluation and Insight 16.6..% 1818 words + +% include the chapters +\include{Chapters_\showreporttype/background-and-objectives} +\include{Chapters_\showreporttype/experiment-methods} +\include{Chapters_\showreporttype/software-design-implementation-testing} +\include{Chapters_\showreporttype/results-and-conclusions} +\include{Chapters_\showreporttype/evaluation} +% add any additional chapters here + +%TC:ignore +\setemptyheader + +\nocite{*} % include everything from the bibliography, irrespective of whether it has been referenced. + +% the following line is included so that the bibliography is also shown in the table of contents. There is the possibility that this is added to the previous page for the bibliography. To address this, a newline is added so that it appears on the first page for the bibliography. +\addcontentsline{toc}{chapter}{References} % Adds References to contents page + +% +% example of including an bibliography. The current style uses IEEE. If you want to change, comment out the line and uncomment the previous line. You should also modify the packages included at the top (see the notes earlier in the file) and then trash your aux files and re-run. +%\bibliographystyle{StylesAndReferences/authordate2annot} +\bibliographystyle{StylesAndReferences/IEEEannotU} +\renewcommand{\bibname}{References} + +\bibliography{StylesAndReferences/references} % References file + + +\setemptyheader + +\addcontentsline{toc}{chapter}{Appendices} +\chapter*{Appendices} +%The appendices are for additional content that is useful to support the discussion in the report. It is material that is not necessarily needed in the body of the report, but its inclusion in the appendices makes it easy to access. +% +%If you have used any 3rd party code, i.e. code that you have not written yourself such as libraries, then you must include Appendix A. In that appendix, you will provide details of the 3rd party code that you have used. +% +%For most other items, it would be better to include them in your technical submission instead of including them as an appendix. For example: +% +%\begin{itemize} +% \item If you have developed a Design Specification document as part of a plan-driven approach for the project, then it would be appropriate to include that document in the technical work. In this report, you would highlight the most interesting aspects of the design, referring your reader to the full specification for further detail. +% \item If you have taken an agile approach to developing the project, then you may be less likely to have developed a full requirements specification at the start of the project. Perhaps you used stories to keep track of the functionality and the ‘future conversations.’ If it isn’t relevant to include all those stories in the body of your report, you could detail those stores in a document in the technical work. +% \item If you have used manual testing, then include a document in the technical work that records the tests that have been done. In this report, you would talk about the use of those tests. +%\end{itemize} +% +%Documents included in the technical work or in the appendices are supporting evidence of the work done. Where you include documents, this report should refer to the documents. You should not be relying on detailed study of those documents in order to understand what is written in this report. +% +%Speak to your supervisor or the module coordinator if you have questions about this. + +%\pagebreak + +% start the appendix - sets up different numbering +\fancypagestyle{plain}{% +%\fancyhf{} % clear all header and footer fields +\fancyhead[L]{Appendix\ \thechapter} +\fancyhead[R]{\leftmark}} + +\appendix +\fancyhead[L]{Appendix\ \thechapter} +\fancyhead[R]{\leftmark} +\fancyhead[C]{} +\fancyfoot[C]{\thepage} +\renewcommand{\headrulewidth}{0.4pt} +\renewcommand{\chaptermark}[1]{\markboth{#1}{}} + +\fancyhead[L]{Appendix\ \thechapter} +\fancyhead[R]{\leftmark} +\fancyfoot[C]{{\thepage} of \pageref{LastPage}} + +% include any appendices here +\include{Appendices/appendixA} +\include{Appendices/appendixB} + +\fancypagestyle{plain}{% + \fancyhead{} %[C]{Annotated Bibliography} + \fancyfoot[C]{{\thepage} of \pageref{LastPage}} % except the center + \renewcommand{\headrulewidth}{0pt} + \renewcommand{\footrulewidth}{0pt} +} + +%TC:endignore + +\end{document} diff --git a/environment.yml b/environment.yml index 4e0f912..5e9d4b5 100644 --- a/environment.yml +++ b/environment.yml @@ -1,5 +1,9 @@ name: autophotographer dependencies: - - numpy - - pandas - - python=3.8 \ No newline at end of file + - python=3.8 + - opencv-python=4.5.5.64 + - matplotlib=3.5.1 + - pandas=1.4.2 + - PyYAML=6.0 + - scikit-image=0.19.2 + - tqdm=4.64.0 \ No newline at end of file diff --git a/src/autophotographer/autophotographer_main.py b/src/autophotographer/autophotographer_main.py index 3745809..602628e 100644 --- a/src/autophotographer/autophotographer_main.py +++ b/src/autophotographer/autophotographer_main.py @@ -11,6 +11,8 @@ from skimage.exposure import is_low_contrast from tqdm import tqdm import autophotographer.filters.brightness.brightness as brightness import autophotographer.filters.focusdetection.focusdetection as focusdetection +from autophotographer.cnn.predict import predict +import sys # GLOBAL VARIABLES # accepted image formats @@ -20,22 +22,18 @@ image_formats = (".jpg", ".jpeg", ".png") video_formats = (".mp4", ".mov", ".avi", ".flv", ".mkv") # default options +filters = ['filesize', 'brightness', 'contrast', 'focus'] +modelPath = os.path.abspath(os.path.join(os.path.dirname(__file__), "../", "output/22-03-2022/model.pth")) brightness_thresh = 0.35 focus_thresh = 0.35 filesize_thresh = 0.35 contrast_thresh = 0.35 ignore_video = False +cnnRank = False # FUNCTIONS # load config file def load_config(path=os.path.join(os.path.dirname(__file__), "./config.yml")): - """ - The load_config function loads a YAML configuration file from the specified path. - - :param path=os.path.join(os.path.dirname(__file__): Used to Specify the path of the config. - :param "./config.yml"): Used to Specify the path to the config file. - :return: A dictionary of the config file. - """ abs_path = os.path.abspath(path) # check if file exists @@ -52,25 +50,7 @@ def load_config(path=os.path.join(os.path.dirname(__file__), "./config.yml")): raise FileNotFoundError("[ERRO] Path does not exist") # load the correct filter function from filter name -def filter_to_function(imagefilter: str, paths: list) -> list: - """ - The filter_to_function function filters a list of image paths based on the filter type. - - Args: - imagefilter (str): The type of filter to apply. Can be "brightness", "contrast", or "focus". - - paths (list): A list of filepaths to images that will be filtered. - - brightness_thresh (int, optional): The threshold for filtering out images with low brightness levels. Defaults to 100 if not specified by user in config file or command line arguments. - - contrast_thresh (float, optional): The threshold for filtering out images with low contrast levels. Defaults to 1 if not specified by user in config file or command line arguments.. - - focus_thresh (float, optional): The threshold for filtering out blurry images based on the variance in blurriness across all pixels within an image's bounding box as determined using OpenCV's Laplacian method and Gaussian Blur method respectively . Defaults to 0 if not specified by user in config file or command line arguments.. - - :param imagefilter:str: Used to Determine which filter to apply. - :param paths:list: Used to Store the paths of all images that have been filtered. - :return: The filtered list of paths. - """ +def filter_to_function(imageFilter: str, paths: list) -> list: if imageFilter == "brightness": paths = filter_brightness(paths, brightness_thresh) print("[INFO] Filtering based on brightness...") @@ -306,42 +286,16 @@ def display_images(paths, location): plt.savefig(location) -# parse command line arguments -if __name__ == "__main__": - parser = argparse.ArgumentParser() - parser.add_argument("-i", "--input", type=os.path.abspath, required=True, nargs="+", - help="path to video or image folder") - parser.add_argument("-c", "--config", type=os.path.abspath, help="path to config file") - args = vars(parser.parse_args()) - - # load in config file - if args["config"] is not None: - autophotoConf = load_config(args["config"]) - else: - autophotoConf = load_config() - - # Load values for options - if autophotoConf["brightness_options"]["threshold"] is not None: - brightness_thresh = autophotoConf["brightness_options"]["threshold"] - if autophotoConf["focus_options"]["threshold"] is not None: - focus_thresh = autophotoConf["focus_options"]["threshold"] - if autophotoConf["contrast_options"]["threshold"] is not None: - contrast_thresh = autophotoConf["contrast_options"]["threshold"] - if autophotoConf["filesize_options"]["threshold"] is not None: - filesize_thresh = autophotoConf["filesize_options"]["threshold"] - if autophotoConf["ignore_video"] is not None: - ignore_video = autophotoConf["ignore_video"] - - paths = filter_paths(args["input"]) +def main(paths, filters=None): print("[INFO] Loaded {} objects.".format(len(paths))) prior_paths = [] path_diff = [] # Order and selection of operations from config file - if autophotoConf["filters"] is not None: + if filters is not None: # iterate over all chosen filters - for imageFilter in autophotoConf["filters"]: + for imageFilter in filters: prior_paths = paths # run given filter @@ -359,5 +313,41 @@ if __name__ == "__main__": print("[INFO] Filtered {}/{} images via {} filtering.".format( len(paths), len(prior_paths), imageFilter)) - if autophotoConf["CNNrank"]: - print("[INFO] Running CNN ranking...") \ No newline at end of file + if cnnRank: + print("[INFO] Running CNN ranking...") + predictions = predict(paths, modelPath) + return predictions + + return paths + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("-i", "--input", type=os.path.abspath, required=True, nargs="+", + help="path to video or image folder") + parser.add_argument("-c", "--config", type=os.path.abspath, help="path to config file") + args = vars(parser.parse_args()) + + # load in config file + if args["config"] is not None: + autophotoConf = load_config(args["config"]) + else: + autophotoConf = load_config() + + # Load values for options + if autophotoConf["filters"] is not None: + filters = autophotoConf["filters"] + if autophotoConf["brightness_options"]["threshold"] is not None: + brightness_thresh = autophotoConf["brightness_options"]["threshold"] + if autophotoConf["focus_options"]["threshold"] is not None: + focus_thresh = autophotoConf["focus_options"]["threshold"] + if autophotoConf["contrast_options"]["threshold"] is not None: + contrast_thresh = autophotoConf["contrast_options"]["threshold"] + if autophotoConf["filesize_options"]["threshold"] is not None: + filesize_thresh = autophotoConf["filesize_options"]["threshold"] + if autophotoConf["ignore_video"] is not None: + ignore_video = autophotoConf["ignore_video"] + if autophotoConf["CNNrank"] is not None: + cnnRank = autophotoConf["CNNrank"] + + paths = filter_paths(args["input"]) + sys.exit(main(paths, filters)) \ No newline at end of file diff --git a/src/autophotographer/cnn/autophotographer.py b/src/autophotographer/cnn/autophotographer.py deleted file mode 100644 index 0e2b4f4..0000000 --- a/src/autophotographer/cnn/autophotographer.py +++ /dev/null @@ -1,58 +0,0 @@ -import argparse -import os -import pathlib -import sys - -import cv2 - - -# Process arguments -def parse_arguments(argv=None): - parser = argparse.ArgumentParser() - parser.add_argument('-i', '--input', dest='inputfile', type=pathlib.Path, help='Specify a video file') - parser.add_argument('-o', '--output', dest='outputfolder', type=pathlib.Path, help='Specify a folder to save frames to') - return parser.parse_args() - -# Convert video to frames -def video_to_frames(): - capture = cv2.VideoCapture(str(inputfile)) - success,image = capture.read() - count = 0 - while success: - outputfile = outputfolder + "/frame%d.jpg" % count - print(outputfile) - cv2.imwrite(outputfile, image) - success,image = capture.read() - count +=1 - -# Shrink set based on filesize -def display_file_sizes(): - filesizes = [] - for filename in os.listdir(outputfolder): - filepath = outputfolder + "/" + filename - filesize = os.path.getsize(filepath) - print(filepath + ": " + str(filesize)) - filesizes.append(filesize) - # work out average - average = sum(filesizes)/len(filesizes) - print ("Average is: " + str(average)) - # delete files below average - count = 0 - for filename in os.listdir(outputfolder): - filepath = outputfolder + "/" + filename - if filesizes[count] < average: - # print(filepath + ": " + str(filesizes[count])) - os.remove(filepath) - count += 1 - -#def remove_similar_frames(): -# sad - -args = parse_arguments() -inputfile = str(args.inputfile.absolute()) -outputfolder = str(args.outputfolder.absolute()) - -# Convert video to frames -video_to_frames() - -display_file_sizes() \ No newline at end of file diff --git a/src/autophotographer/cnn/config.py b/src/autophotographer/cnn/config.py index 60975f3..23d149c 100644 --- a/src/autophotographer/cnn/config.py +++ b/src/autophotographer/cnn/config.py @@ -1,5 +1,4 @@ import os - import torch # https://pytorch.org/hub/pytorch_vision_resnet/ @@ -10,15 +9,12 @@ IMAGE_SIZE = 224 VAL_SPLIT = 0.1 DEVICE = "cuda" if torch.cuda.is_available() else "cpu" -FEATURE_EXTRACTION_BATCH_SIZE = 256 -PRED_BATCH_SIZE = 4 -EPOCHS = 20 +TRAIN_BATCH_SIZE = 256 +PREDICTION_BATCH_SIZE = 4 +EPOCHS = 1 LR = 0.001 IMAGE_SIZE = 32 PRED_BATCH_SIZE = 4 -WARMUP_PLOT = os.path.join("output", "plot.png") -WARMUP_MODEL = os.path.join("output", "plot.pth") - TENSOR_IMAGES_PATH = "tensorImages.pt" TENSOR_RATINGS_PATH = "tensorRatings.pt" \ No newline at end of file diff --git a/src/autophotographer/cnn/dataset.py b/src/autophotographer/cnn/dataset.py index b8a7537..ce0e571 100644 --- a/src/autophotographer/cnn/dataset.py +++ b/src/autophotographer/cnn/dataset.py @@ -16,7 +16,7 @@ from sklearn.preprocessing import MinMaxScaler from torch.utils.data import DataLoader from torchvision import transforms -from . import config +import autophotographer.cnn.config as config ImageFile.LOAD_TRUNCATED_IMAGES = True @@ -85,6 +85,10 @@ def get_random_image_index(): def calculate_image_rating(imageIndex): df = pd.read_csv(filePathInfoAVA, sep=" ", header=None) imageInfo = df.loc[df[1] == imageIndex] + if len(imageInfo.values[0]) > 15: + raise ValueError("Entry is larger than the expected 15 columns.") + elif len(imageInfo.values[0]) < 15: + raise ValueError("Entry is smaller than the expected 15 columns.") styleIndex = 2 numOfRatings = 0 score = 0 @@ -96,9 +100,11 @@ def calculate_image_rating(imageIndex): styleIndex += 1 #print(numOfRatings) #print(score) + if score == 0: + return 0 adjustedScore = score / numOfRatings #print(adjustedScore) - return adjustedScore + return round(adjustedScore, 6) def get_all_image_ratings(): imageRatings = {} @@ -119,7 +125,7 @@ def get_all_image_ratings(): df = pd.DataFrame(list(imageRatings.items())) return df -def load_image_ratings(): +def load_image_ratings(filePathRatings): columns = ["id", "rating"] df = pd.read_csv(filePathRatings, header=None, sep=" ", names=columns) return df @@ -157,11 +163,10 @@ def build_dataframe(df, imgPath): return df #df = build_dataframe(remove_entries_for_missing_images(load_image_ratings(), imgPath), imgPath) -df = pd.read_csv(dataframePath, index_col = 0) def create_tensor_array(): tensorArray = [] - for idx, row in df.iterrows(): + for index, row in df.iterrows(): rating = row['rating'] image = cv2.imread(row['path']) image = cv2.resize(image, (32, 32)) @@ -181,8 +186,8 @@ def load_in_tensors(): def get_dataloader(df, transforms, batchSize, shuffle=True): # Create a dataloader for dataset tensorArray = [] - for idx, row in df.iterrows(): - #load each image path and process the data via transforms + for index, row in df.iterrows(): + # load each image path and process the data via transforms transformedImg = transforms(pil_loader(row['path'])) rating = row['rating'] # form a tuple row with rating and the processed data @@ -195,7 +200,27 @@ def get_dataloader(df, transforms, batchSize, shuffle=True): return (tensorArray, loader) +# https://github.com/python-pillow/Pillow/issues/835#issuecomment-53999355 def pil_loader(path): with open(path, 'rb') as f: - img = Image.open(f) - return img.convert('RGB') \ No newline at end of file + image = Image.open(f) + return image.convert('RGB') + +def load_ratings_df(pathToRatingsFile): + columns = ["id", "rating"] + df = pd.read_csv(pathToRatingsFile, header=None, sep=" ", names=columns) + return df + +def load_images_df(pathToImagesDir, image_formats): + imagePaths = [] + imageIds = [] + for filename in os.listdir(pathToImagesDir): + path = os.path.join(pathToImagesDir, filename) + if path.lower().endswith(image_formats): + imagePaths.append(path) + imageIds.append(int(os.path.splitext(filename)[0])) + df = pd.DataFrame({"id": imageIds, "path": imagePaths}) + return df + +# Read in the dataframe +df = pd.read_csv(dataframePath, index_col = 0) \ No newline at end of file diff --git a/src/autophotographer/cnn/model.py b/src/autophotographer/cnn/model.py index 3440ad4..6bcffc4 100644 --- a/src/autophotographer/cnn/model.py +++ b/src/autophotographer/cnn/model.py @@ -3,7 +3,6 @@ import time from os.path import abspath import config -import dataset import matplotlib.pyplot as plt import torch import torch.nn as nn @@ -12,31 +11,35 @@ from torch.utils.data import DataLoader from torchvision import transforms from torchvision.models import resnet50 from tqdm import tqdm +import autophotographer.cnn.dataset as dataset +import autophotographer.cnn.config as config # projectRoot = "/src/" script_directory = os.path.dirname(__file__) -projectRoot = abspath(os.path.join(script_directory, "../..")) +projectRoot = abspath(os.path.join(script_directory, "../../..")) print("Project root: " + projectRoot) INITIAL_PLOT_PATH = os.path.join(projectRoot, "src/output/plot.png") INTIIAL_MODEL_PATH = os.path.join(projectRoot, "src/output/model.pth") valDatasetPath = os.path.join(projectRoot, "src/autophotographer/valDataset.pt") trainDatasetPath = os.path.join(projectRoot, "src/autophotographer/trainDataset.pt") -# Declare transformations +# Declare transformations for train set trainTransform = transforms.Compose([ - transforms.RandomResizedCrop(config.IMAGE_SIZE), transforms.RandomHorizontalFlip(), + transforms.RandomResizedCrop(config.IMAGE_SIZE), transforms.RandomRotation(90), transforms.ToTensor(), transforms.Normalize(mean=config.MEAN, std=config.STD) ]) + +# Declare transformations for val set valTransform = transforms.Compose([ transforms.Resize((config.IMAGE_SIZE, config.IMAGE_SIZE)), transforms.ToTensor(), transforms.Normalize(mean=config.MEAN, std=config.STD) ]) -# Split dataset into val and train +# Load dataset from dataset module and split dataset into val and train valSetLen = int(len(dataset.df) * config.VAL_SPLIT) trainSetLen = len(dataset.df) - valSetLen trainSet = dataset.df[:trainSetLen] @@ -46,20 +49,20 @@ print("Using " + config.DEVICE + "...") # create data loaders print("Getting dataloaders...") -#(trainDataset, trainLoader) = dataset.get_dataloader(trainSet, - #transforms=trainTransform, batchSize=config.FEATURE_EXTRACTION_BATCH_SIZE) +(trainDataset, trainLoader) = dataset.get_dataloader(trainSet, + transforms=trainTransform, batchSize=config.TRAIN_BATCH_SIZE) #torch.save(trainDataset, 'trainDataset.pt') -#(valDataset, valLoader) = dataset.get_dataloader(valSet, - #transforms=valTransform, batchSize=config.FEATURE_EXTRACTION_BATCH_SIZE, shuffle=False) +(valDataset, valLoader) = dataset.get_dataloader(valSet, + transforms=valTransform, batchSize=config.TRAIN_BATCH_SIZE, shuffle=False) #torch.save(valDataset, 'valDataset.pt') # Load datasets tensors from disk -valDataset = torch.load(valDatasetPath) -valLoader = DataLoader(valDataset, batch_size=config.FEATURE_EXTRACTION_BATCH_SIZE, shuffle=False, num_workers=os.cpu_count(), - pin_memory=True if config.DEVICE == "cuda" else False) -trainDataset = torch.load(trainDatasetPath) -trainLoader = DataLoader(trainDataset, batch_size=config.FEATURE_EXTRACTION_BATCH_SIZE, shuffle=True, num_workers=os.cpu_count(), - pin_memory=True if config.DEVICE == "cuda" else False) +#valDataset = torch.load(valDatasetPath) +#valLoader = DataLoader(valDataset, batch_size=config.FEATURE_EXTRACTION_BATCH_SIZE, shuffle=False, num_workers=os.cpu_count(), +# pin_memory=True if config.DEVICE == "cuda" else False) +#trainDataset = torch.load(trainDatasetPath) +#trainLoader = DataLoader(trainDataset, batch_size=config.FEATURE_EXTRACTION_BATCH_SIZE, shuffle=True, num_workers=os.cpu_count(), +# pin_memory=True if config.DEVICE == "cuda" else False) # Load the resnet model model = resnet50(pretrained=True) @@ -71,30 +74,32 @@ for parameter in model.parameters(): # Replace last layer with a FC single output layer modelOutputFeatures = model.fc.in_features model.fc = nn.Linear(modelOutputFeatures, 1) + +# Send model to device model = model.to(config.DEVICE) # Initialize otimizer and loss function optimizer = torch.optim.Adam(model.fc.parameters(), lr=config.LR) lossFunction = nn.L1Loss() # mean absolute error +# Calculate steps required for train and validation +trainSteps = len(trainDataset) // config.TRAIN_BATCH_SIZE +valSteps = len(valDataset) // config.TRAIN_BATCH_SIZE -# Calculate steps for train and validation -trainSteps = len(trainDataset) // config.FEATURE_EXTRACTION_BATCH_SIZE -valSteps = len(valDataset) // config.FEATURE_EXTRACTION_BATCH_SIZE - -# Store training data +# Store training data to print to output dataDict = {"train_loss": [], "val_loss": []} # Loop over epochs print("Training...") startTime = time.time() for epoch in tqdm(range(config.EPOCHS)): + # put model in training mode model.train() totalTrainLoss = 0 totalValLoss = 0 - + # Loop over training data for (i, (x, y)) in enumerate(trainLoader): (x, y) = (x.to(config.DEVICE), y.to(config.DEVICE)) pred = model(x) @@ -109,7 +114,8 @@ for epoch in tqdm(range(config.EPOCHS)): optimizer.zero_grad() totalTrainLoss += loss - + + # Evaluate performance with validation set with torch.no_grad(): model.eval() diff --git a/src/autophotographer/cnn/predict.py b/src/autophotographer/cnn/predict.py new file mode 100644 index 0000000..34bfb68 --- /dev/null +++ b/src/autophotographer/cnn/predict.py @@ -0,0 +1,49 @@ +import argparse +import datetime +import os +from os.path import abspath + +import matplotlib.pyplot as plt +import torch +from torch import nn +from torchvision import transforms +from PIL import Image +from tqdm import tqdm + +def predict(paths, model): + device = torch.device("cuda" if torch.cuda.is_available() else "cpu") + model = torch.load(model, map_location=torch.device('cpu')) + model = model.to(device) + model.eval() + # https://pytorch.org/hub/pytorch_vision_resnet/ + configImageSize = 224 + configMean = [0.485, 0.456, 0.406] + configStd = [0.229, 0.224, 0.225] + + # Declare transforms + imageTransforms = transforms.Compose([ + transforms.Resize((configImageSize, configImageSize)), + transforms.ToTensor(), + transforms.Normalize(mean=configMean, std=configStd) + ]) + + # # Calulate the inverse std and inverse mean for denormalisation + # invMean = [-m/s for (m, s) in zip(configMean, configStd)] + # invStd = [1/s for s in configStd] + + # # define denormalisation transform + # deNormalize = transforms.Normalize(mean=invMean, std=invStd) + + predictions = {} + for path in tqdm(paths, desc="Predicting aesthetic quality"): + img = Image.open(path) + img = img.convert("RGB") + trImg = imageTransforms(img) + trImg = trImg.unsqueeze(0) + trImg = trImg.to(device) + with torch.no_grad(): + # Make a prediction on the images + imagePrediction = model(trImg) + imagePrediction = imagePrediction[0].numpy()[0] + predictions[path] = imagePrediction + return predictions \ No newline at end of file diff --git a/src/autophotographer/predict.py b/src/autophotographer/predict.py index 178629f..7319408 100644 --- a/src/autophotographer/predict.py +++ b/src/autophotographer/predict.py @@ -12,9 +12,9 @@ from cnn import config, dataset # set project root for fetching files using relative file paths script_directory = os.path.dirname(__file__) -projectRoot = abspath(os.path.join(script_directory, "../")) +projectRoot = abspath(os.path.join(script_directory, "../../")) print(projectRoot) -PLOT_PATH = os.path.join(projectRoot, "src/output/") +plotPath = os.path.join(projectRoot, "src/output/") # parse arguments for image to predict and model to use parser = argparse.ArgumentParser() @@ -48,7 +48,7 @@ valSetLen = int(len(dataset.df) * config.VAL_SPLIT) trainSetLen = len(dataset.df) - valSetLen valSet = dataset.df[trainSetLen:] (valDataset, valLoader) = dataset.get_dataloader(valSet, - transforms=valTransform, batchSize=config.PRED_BATCH_SIZE, + transforms=valTransform, batchSize=config.PREDICTION_BATCH_SIZE, shuffle=True) if torch.cuda.is_available(): @@ -79,9 +79,9 @@ with torch.no_grad(): preds = model(images) # Loop over each element in the batch - for i in range(0, config.PRED_BATCH_SIZE): + for i in range(0, config.PREDICTION_BATCH_SIZE): # Initalize a subplot - ax = plt.subplot(config.PRED_BATCH_SIZE, 1, i + 1) + ax = plt.subplot(config.PREDICTION_BATCH_SIZE, 1, i + 1) # De-normalize image, scale the pixel range to 255 image = images[i] @@ -109,5 +109,5 @@ with torch.no_grad(): plt.tight_layout() date = datetime.datetime.now() dateString = str(date.year) + "-" + str(date.month) + "-" + str(date.day) + "_" + str(date.hour) + "-" + str(date.minute) + "-" + str(date.second) - PLOT_PATH = os.path.join(PLOT_PATH, "predict-plot-" + dateString + ".png") - plt.savefig(PLOT_PATH) \ No newline at end of file + plotPath = os.path.join(plotPath, "predict-plot-" + dateString + ".png") + plt.savefig(plotPath) \ No newline at end of file diff --git a/src/experiments/data/artificial-blurry.png b/src/experiments/data/artificial-blurry.png new file mode 100644 index 0000000..71b726d --- /dev/null +++ b/src/experiments/data/artificial-blurry.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:56e354fb8e86c9d85e40f22c770b9bac679e442d5855c1fc887559c75a127263 +size 381315 diff --git a/src/experiments/data/artificial-high-exposure.png b/src/experiments/data/artificial-high-exposure.png new file mode 100644 index 0000000..99e17bd --- /dev/null +++ b/src/experiments/data/artificial-high-exposure.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:82c1bdf1c0efcdcf92a5a395dedb85bc09b8c41a1f00074488bf54332c864780 +size 731485 diff --git a/src/experiments/data/artificial-low-contrast.png b/src/experiments/data/artificial-low-contrast.png new file mode 100644 index 0000000..d4dff59 --- /dev/null +++ b/src/experiments/data/artificial-low-contrast.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b9ed77dc9e4ccc4aff2ccd459afc403b1fc63f771b5aa988faa7930dda732b7c +size 738413 diff --git a/src/experiments/data/artificial-normal.png b/src/experiments/data/artificial-normal.png new file mode 100644 index 0000000..b9080f1 --- /dev/null +++ b/src/experiments/data/artificial-normal.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5794a5ce7006213100436d7e99bac7fddf72899a71ee737a15c16e7c1235d8c9 +size 1184720 diff --git a/src/experiments/experiment-1.py b/src/experiments/experiment-1.py new file mode 100644 index 0000000..c7fc749 --- /dev/null +++ b/src/experiments/experiment-1.py @@ -0,0 +1,56 @@ +import pandas as pd +import os +from autophotographer.cnn.dataset import load_ratings_df +from autophotographer.cnn.dataset import load_images_df +from autophotographer import autophotographer_main +import matplotlib.pyplot as plt +import datetime +import numpy as np + +imagesDir = "/datasets/AVA/images/images" +scriptDir = os.path.dirname(__file__) +ratingsPath = os.path.abspath(os.path.join(scriptDir, "../../", "data/ratings.txt")) +image_formats = (".jpg", ".jpeg", ".png") +numSamples = 50 +filters = ['filesize', 'brightness', 'contrast', 'focus'] + +# load ava images and ratings +imagesDf = load_images_df(imagesDir, image_formats) +ratingsDf = load_ratings_df(ratingsPath) + +datasetDf = imagesDf.merge(ratingsDf, on='id', how='left') + +ratingDiffs = [] +for run in range(1, 20): + print("RUN {}".format(run)) + # get a random sample + dfSample = datasetDf.sample(numSamples) + sampleAvgRating = float(dfSample.mean()["rating"]) + + filtered_paths = autophotographer_main.main(dfSample["path"], filters) + + # collected filtered ratings + filtered_ratings=[] + for path in filtered_paths: + row = (dfSample.index[dfSample["path"] == path])[0] + filtered_ratings.append(float(dfSample.at[row, "rating"])) + filteredAvgRating = float(pd.DataFrame(filtered_ratings).mean()) + + ratingDiff = sampleAvgRating - filteredAvgRating + ratingDiffs.append(ratingDiff) + if filteredAvgRating > sampleAvgRating: + print("Rating improved - Sample: {}, Filtered: {}".format(sampleAvgRating, filteredAvgRating)) + else: + print("Rating did not improve - Sample: {}, Filtered: {}".format(sampleAvgRating, filteredAvgRating)) + +x = np.array(range(1, 20)) +y = np.array(ratingDiffs) + + +plt.plot(x,y) +plt.xlabel("run") +plt.ylabel("rating diff") +outputDir = os.path.join(os.path.dirname(__file__), "output") +fileName = datetime.datetime.now().strftime("%G-%m-%dT%H%M%S") + "_" + "experiment-1" + ".png" +filePath = os.path.join(outputDir, fileName) +plt.savefig(filePath) \ No newline at end of file diff --git a/src/experiments/experiment-2.py b/src/experiments/experiment-2.py new file mode 100644 index 0000000..42e746f --- /dev/null +++ b/src/experiments/experiment-2.py @@ -0,0 +1,40 @@ +# check if filter order makes a difference +from autophotographer.cnn.dataset import load_ratings_df +from autophotographer.cnn.dataset import load_images_df +from autophotographer import autophotographer_main +import os +import matplotlib.pyplot as plt +import numpy as np +import datetime +imagesDir = "/datasets/AVA/images/images" +scriptDir = os.path.dirname(__file__) +ratingsPath = os.path.abspath(os.path.join(scriptDir, "../../", "data/ratings.txt")) +image_formats = (".jpg", ".jpeg", ".png") +numSamples = 50 +imagesDf = load_images_df(imagesDir, image_formats) +ratingsDf = load_ratings_df(ratingsPath) +datasetDf = imagesDf.merge(ratingsDf, on='id', how='left') +dfSample = datasetDf.sample(numSamples, random_state=5050) +print(__file__) + +filters = ['focus'] +focus_reduced = len(autophotographer_main.main(dfSample["path"], filters)) + +filters = ['filesize'] +filesize_reduced = len(autophotographer_main.main(dfSample["path"], filters)) + +filters = ['brightness'] +brighness_reduced = len(autophotographer_main.main(dfSample["path"], filters)) + +filters = ['contrast'] +contast_reduced = len(autophotographer_main.main(dfSample["path"], filters)) + + +x = np.array(["focus", "filesize", "brighness", "contrast"]) +y = np.array([focus_reduced, filesize_reduced, brighness_reduced, contast_reduced]) + +plt.bar(x,y) +outputDir = os.path.join(os.path.dirname(__file__), "output") +fileName = datetime.datetime.now().strftime("%G-%m-%dT%H%M%S") + "_" + "experiment-2" + ".png" +filePath = os.path.join(outputDir, fileName) +plt.savefig(filePath) \ No newline at end of file diff --git a/src/experiments/experiment-3.py b/src/experiments/experiment-3.py new file mode 100644 index 0000000..9404b63 --- /dev/null +++ b/src/experiments/experiment-3.py @@ -0,0 +1,93 @@ +from autophotographer.cnn.predict import predict +import os +import pandas as pd +import cv2 +import datetime +from tqdm import tqdm +import matplotlib.pyplot as plt + +scriptDir = os.path.dirname(__file__) +datasetsPath = "/datasets" +modelPath = os.path.abspath(os.path.join(scriptDir, "../", "output/22-03-2022/model.pth")) +videoDirPath = os.path.abspath(os.path.join(datasetsPath, "Hannah/" )) +filenames = os.listdir(videoDirPath) +image_formats = (".jpg", ".jpeg", ".png") + +# iterate over each of the "journey" directories +for directory in [ + "overcastjuly/melindwr1", + "overcastjuly/melindwr2", + "sunnyaugust/camels hump", + "sunnyaugust/diggers end", + "sunnyaugust/drunken druid", + "sunnyaugust/hippety hop", + "sunnyaugust/melindwr1", + "sunnyaugust/melindwr2", + "sunnyaugust/spaghetti junction"]: + videoDirPath = os.path.abspath(os.path.join(datasetsPath, "Hannah/", directory)) + # list all file names + filenames = os.listdir(videoDirPath) + paths = [] + # only retrieve the images + for filename in filenames: + if filename.lower().endswith(image_formats): + path = os.path.join(videoDirPath, filename) + paths.append(path) + + # make predictions on the images + predictions = predict(paths, modelPath) + df = pd.DataFrame(list(predictions.items()), columns = ["path", "prediction"]) + df = df.sort_values(by=["prediction"]) + + # retrieve the 5 highest ranking and 5 lowest ranking predictions + fiveHighest = df.tail(5) + fiveLowest = df.head(5) + + + # plot the images + row = 2 + column = 5 + width = 250 + size = width * row + outputDir = os.path.join(os.path.dirname(__file__), "output") + fileName = datetime.datetime.now().strftime("%G-%m-%dT%H%M%S") + "_" + "experiment-3" + directory.replace("/", "-") + ".png" + filePath = os.path.join(outputDir, fileName) + + fig = plt.figure(figsize=(15, 6)) + + # Plot the 5 highest on the first row + plotIndex = 1 + for index in tqdm(fiveHighest.index): + path = fiveHighest["path"][index] + rating = fiveHighest["prediction"][index] + image = cv2.imread(path) + image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) + height = int(image.shape[0] * (width / image.shape[0])) + image = cv2.resize(image, (width, height)) + fig.add_subplot(row, column, plotIndex) + plt.imshow(image) + plt.axis('off') + plt.title(rating) + plt.tight_layout() + plotIndex += 1 + + # Plot the 5 lowest on the second row + for index in tqdm(fiveLowest.index): + path = fiveLowest["path"][index] + rating = fiveLowest["prediction"][index] + image = cv2.imread(path) + image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) + height = int(image.shape[0] * (width / image.shape[0])) + image = cv2.resize(image, (width, height)) + fig.add_subplot(row, column, plotIndex) + plt.imshow(image) + plt.axis('off') + plt.title(rating) + plt.tight_layout() + plotIndex += 1 + + fig.tight_layout() + plt.savefig(filePath) + + + diff --git a/src/experiments/experiment-4.py b/src/experiments/experiment-4.py new file mode 100644 index 0000000..cf3a5f5 --- /dev/null +++ b/src/experiments/experiment-4.py @@ -0,0 +1,59 @@ +from autophotographer.cnn.predict import predict +import os +import pandas as pd +import cv2 +import datetime +from tqdm import tqdm +import matplotlib.pyplot as plt + +scriptDir = os.path.dirname(__file__) +modelPath = os.path.abspath(os.path.join(scriptDir, "../", "output/22-03-2022/model.pth")) +experimentDataPath = os.path.join(scriptDir, "data/") +image_formats = (".jpg", ".jpeg", ".png") + +# list all file names +filenames = os.listdir(experimentDataPath) +paths = [] +# only retrieve the images +for filename in filenames: + if filename.lower().endswith(image_formats): + path = os.path.join(experimentDataPath, filename) + paths.append(path) + +# make predictions on the images +predictions = predict(paths, modelPath) +df = pd.DataFrame(list(predictions.items()), columns = ["path", "prediction"]) +df = df.sort_values(by=["prediction"]) + +# plot the images +row = 1 +column = 4 +width = 250 +size = width * row +outputDir = os.path.join(os.path.dirname(__file__), "output") +fileName = datetime.datetime.now().strftime("%G-%m-%dT%H%M%S") + "_" + "experiment-4" + ".png" +filePath = os.path.join(outputDir, fileName) + +fig = plt.figure(figsize=(15, 6)) + +# Plot the 5 highest on the first row +plotIndex = 1 +for index in tqdm(df.index): + path = df["path"][index] + rating = df["prediction"][index] + image = cv2.imread(path) + image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) + height = int(image.shape[0] * (width / image.shape[0])) + image = cv2.resize(image, (width, height)) + fig.add_subplot(row, column, plotIndex) + plt.imshow(image) + plt.axis('off') + plt.title(rating) + plt.tight_layout() + plotIndex += 1 + +fig.tight_layout() +plt.savefig(filePath) + + + diff --git a/src/experiments/output/2022-05-01T200015_experiment-2.png b/src/experiments/output/2022-05-01T200015_experiment-2.png new file mode 100644 index 0000000..69e3b8f --- /dev/null +++ b/src/experiments/output/2022-05-01T200015_experiment-2.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1f4d2364e69e5104f829a02de1680dd68afe4ff6e9d1d6599fa13fd8c99df1ed +size 9859 diff --git a/src/experiments/output/2022-05-01T202118_experiment-1.png b/src/experiments/output/2022-05-01T202118_experiment-1.png new file mode 100644 index 0000000..96d3b34 --- /dev/null +++ b/src/experiments/output/2022-05-01T202118_experiment-1.png @@ -0,0 +1,3 @@ +version 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https://git-lfs.github.com/spec/v1 +oid sha256:099ef022e948d13817c164a34818e4cdb5ee61e6e0330351c1403debfe7436e6 +size 59375 diff --git a/src/output/predict-plot-2022-5-5_8-15-13.png b/src/output/predict-plot-2022-5-5_8-15-13.png new file mode 100644 index 0000000..95d0930 --- /dev/null +++ b/src/output/predict-plot-2022-5-5_8-15-13.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:31b798ad7ff16886cef0b02cf489ad634a313ef7336e43315314d454db9b6bd7 +size 60484 diff --git a/test/unit/test_dataset.py b/test/unit/test_dataset.py index e69de29..6ad4b2b 100644 --- a/test/unit/test_dataset.py +++ b/test/unit/test_dataset.py @@ -0,0 +1,35 @@ +from autophotographer.cnn import dataset +from unittest import mock +import pytest +import pandas as pd + +@mock.patch("pandas.read_csv") +def test_calculate_image_rating_with_no_ratings(mock_read_csv): + testEntry = "1 1 0 0 0 0 0 0 0 0 0 0 -1 -1 -1" + testEntry = testEntry.split() + testEntry = list(map(int, testEntry)) + df = pd.DataFrame([testEntry]) + mock_read_csv.return_value = df + index = 1 + assert dataset.calculate_image_rating(index) == 0 + +@mock.patch("pandas.read_csv") +def test_calculate_image_rating_multiple_ratings(mock_read_csv): + testEntry = "1 1 1 2 3 4 5 6 7 8 9 10 -1 -1 -1" + testEntry = testEntry.split() + testEntry = list(map(int, testEntry)) + df = pd.DataFrame([testEntry]) + mock_read_csv.return_value = df + index = 1 + assert dataset.calculate_image_rating(index) == 7 + +@mock.patch("pandas.read_csv") +def test_calculate_image_rating_incorrect_number_of_columns(mock_read_csv): + with pytest.raises(ValueError): + testEntry = "1 1 1 2 3 4 5 6 7 8 9 10 -1 -1 -1 9 9 9" + testEntry = testEntry.split() + testEntry = list(map(int, testEntry)) + df = pd.DataFrame([testEntry]) + mock_read_csv.return_value = df + index = 1 + assert dataset.calculate_image_rating(index) \ No newline at end of file From 9e8ed73cf47f7e0218d12326bf8bf07dda364882 Mon Sep 17 00:00:00 2001 From: oscarpocock Date: Mon, 16 May 2022 09:59:53 +0100 Subject: [PATCH 32/36] Added project demo slides with architecture --- docs/project-demo/latex/.gitignore | 303 ++++++++++++++++++ .../project-demo/latex/img/architecture-1.pdf | 3 + .../project-demo/latex/img/architecture-2.pdf | 3 + docs/project-demo/latex/presentation.pdf | 3 + docs/project-demo/latex/presentation.tex | 261 +++++++++++++++ 5 files changed, 573 insertions(+) create mode 100644 docs/project-demo/latex/.gitignore create mode 100644 docs/project-demo/latex/img/architecture-1.pdf create mode 100644 docs/project-demo/latex/img/architecture-2.pdf create mode 100644 docs/project-demo/latex/presentation.pdf create mode 100644 docs/project-demo/latex/presentation.tex diff --git a/docs/project-demo/latex/.gitignore b/docs/project-demo/latex/.gitignore new file mode 100644 index 0000000..360474b --- /dev/null +++ b/docs/project-demo/latex/.gitignore @@ -0,0 +1,303 @@ +## Core latex/pdflatex auxiliary files: +*.aux +*.lof +*.log +*.lot +*.fls +*.out +*.toc +*.fmt +*.fot +*.cb +*.cb2 +.*.lb + +## Intermediate documents: +*.dvi +*.xdv +*-converted-to.* +# these rules might exclude image files for figures etc. +# *.ps +# *.eps +# *.pdf + +## Generated if empty string is given at "Please type another file name for output:" +.pdf + +## Bibliography auxiliary files (bibtex/biblatex/biber): +*.bbl +*.bcf +*.blg +*-blx.aux +*-blx.bib +*.run.xml + +## Build tool auxiliary files: +*.fdb_latexmk +*.synctex +*.synctex(busy) +*.synctex.gz +*.synctex.gz(busy) +*.pdfsync + +## Build tool directories for auxiliary files +# latexrun +latex.out/ + +## Auxiliary and intermediate files from other packages: +# algorithms +*.alg +*.loa + +# achemso +acs-*.bib + +# amsthm +*.thm + +# beamer +*.nav +*.pre +*.snm +*.vrb + +# changes +*.soc + +# comment +*.cut + +# cprotect +*.cpt + +# elsarticle (documentclass of Elsevier journals) +*.spl + +# endnotes +*.ent + +# fixme +*.lox + +# feynmf/feynmp +*.mf +*.mp +*.t[1-9] +*.t[1-9][0-9] +*.tfm + +#(r)(e)ledmac/(r)(e)ledpar +*.end +*.?end +*.[1-9] +*.[1-9][0-9] +*.[1-9][0-9][0-9] +*.[1-9]R +*.[1-9][0-9]R +*.[1-9][0-9][0-9]R +*.eledsec[1-9] +*.eledsec[1-9]R +*.eledsec[1-9][0-9] +*.eledsec[1-9][0-9]R +*.eledsec[1-9][0-9][0-9] +*.eledsec[1-9][0-9][0-9]R + +# glossaries +*.acn +*.acr +*.glg +*.glo +*.gls +*.glsdefs +*.lzo +*.lzs +*.slg +*.slo +*.sls + +# uncomment this for glossaries-extra (will ignore makeindex's style files!) +# *.ist + +# gnuplot +*.gnuplot +*.table + +# gnuplottex +*-gnuplottex-* + +# gregoriotex +*.gaux +*.glog +*.gtex + +# htlatex +*.4ct +*.4tc +*.idv +*.lg +*.trc +*.xref + +# hyperref +*.brf + +# knitr +*-concordance.tex +# TODO Uncomment the next line if you use knitr and want to ignore its generated tikz files +# *.tikz +*-tikzDictionary + +# listings +*.lol + +# luatexja-ruby +*.ltjruby + +# makeidx +*.idx +*.ilg +*.ind + +# minitoc +*.maf +*.mlf +*.mlt +*.mtc[0-9]* +*.slf[0-9]* +*.slt[0-9]* +*.stc[0-9]* + +# minted +_minted* +*.pyg + +# morewrites +*.mw + +# newpax +*.newpax + +# nomencl +*.nlg +*.nlo +*.nls + +# pax +*.pax + +# pdfpcnotes +*.pdfpc + +# sagetex +*.sagetex.sage +*.sagetex.py +*.sagetex.scmd + +# scrwfile +*.wrt + +# svg +svg-inkscape/ + +# sympy +*.sout +*.sympy +sympy-plots-for-*.tex/ + +# pdfcomment +*.upa +*.upb + +# pythontex +*.pytxcode +pythontex-files-*/ + +# tcolorbox +*.listing + +# thmtools +*.loe + +# TikZ & PGF +*.dpth +*.md5 +*.auxlock + +# titletoc +*.ptc + +# todonotes +*.tdo + +# vhistory +*.hst +*.ver + +# easy-todo +*.lod + +# xcolor +*.xcp + +# xmpincl +*.xmpi + +# xindy +*.xdy + +# xypic precompiled matrices and outlines +*.xyc +*.xyd + +# endfloat +*.ttt +*.fff + +# Latexian +TSWLatexianTemp* + +## Editors: +# WinEdt +*.bak +*.sav + +# Texpad +.texpadtmp + +# LyX +*.lyx~ + +# Kile +*.backup + +# gummi +.*.swp + +# KBibTeX +*~[0-9]* + +# TeXnicCenter +*.tps + +# auto folder when using emacs and auctex +./auto/* +*.el + +# expex forward references with \gathertags +*-tags.tex + +# standalone packages +*.sta + +# Makeindex log files +*.lpz + +# xwatermark package +*.xwm + +# REVTeX puts footnotes in the bibliography by default, unless the nofootinbib +# option is specified. Footnotes are the stored in a file with suffix Notes.bib. +# Uncomment the next line to have this generated file ignored. +#*Notes.bib + +.sync_* \ No newline at end of file diff --git a/docs/project-demo/latex/img/architecture-1.pdf b/docs/project-demo/latex/img/architecture-1.pdf new file mode 100644 index 0000000..29b2357 --- /dev/null +++ b/docs/project-demo/latex/img/architecture-1.pdf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:12b19f4d94499c9366747e9a1a8169b32ab7d74f516175ae197df1875ab0b478 +size 58492 diff --git a/docs/project-demo/latex/img/architecture-2.pdf b/docs/project-demo/latex/img/architecture-2.pdf new file mode 100644 index 0000000..848c889 --- /dev/null +++ b/docs/project-demo/latex/img/architecture-2.pdf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7a67eee57641c24ae5ac6f2b77f8842a4baf1513e04dde754bb486cd0d46b7f4 +size 66110 diff --git a/docs/project-demo/latex/presentation.pdf b/docs/project-demo/latex/presentation.pdf new file mode 100644 index 0000000..6bbadf5 --- /dev/null +++ b/docs/project-demo/latex/presentation.pdf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:47dfa7488a24b1e52bab5f335d61c2aa5ccd52df030d840320fe143cba3d1143 +size 112968 diff --git a/docs/project-demo/latex/presentation.tex b/docs/project-demo/latex/presentation.tex new file mode 100644 index 0000000..0657c03 --- /dev/null +++ b/docs/project-demo/latex/presentation.tex @@ -0,0 +1,261 @@ +% xelatex +\documentclass[aspectratio=169]{beamer} +\usepackage{graphicx} +\graphicspath{ {./img/} } +\usetheme{CambridgeUS} + +\title{Autophotographer} +\subtitle{Project Demo} +\author{Oscar Pocock} +\date{May 16, 2022} + +\begin{document} +\begin{frame} + \titlepage +\end{frame} + +\begin{frame} +\begin{figure} +\centering +\includegraphics[height=0.95\textheight]{architecture-1}\\ +\end{figure} +\end{frame} + +\begin{frame} +\begin{figure} +\centering +\includegraphics[width=\textwidth]{architecture-2}\\ +\end{figure} +\end{frame} + + +%\begin{frame} +% \tableofcontents +%\end{frame} +% +%\section{What is Open Source?} +% +%\begin{frame} +%\frametitle{Simple Analogy} +%\begin{columns} +%\column{.5\textwidth} +%\centering \textbf{Proprietary}\\ +%\includegraphics[width=0.5\textwidth]{cake} +%\column{.5\textwidth} +%\centering \textbf{Open Source}\\ +%\includegraphics[height=0.5\textwidth]{cake-and-recipe} +%\end{columns} +%\end{frame} +% +%\begin{frame} +%\begin{figure} +%\centering +%\includegraphics[height=0.75\textheight]{tweet}\\ +%\tiny{\href{https://twitter.com/bbotezatu/status/768756952528723969}{https://twitter.com/bbotezatu/status/768756952528723969}} +%\end{figure} +%\end{frame} +% +%\begin{frame} +%\frametitle{Why care?} +%Open Source software gives certain freedoms to users. +%\begin{columns} +%\column{.5\textwidth} +%It allows indviduals to: +%\begin{itemize} +%\item use the software +%\item study the code and make changes +%\item share the software +%\item improve the software and share the improvements +%\end{itemize} +%\column{.5\textwidth} +%Following our cake analogy +%\begin{itemize} +%\item eat the cake! +%\item study the recipe +%\item share the recipe with others +%\item improve or change the recipe and share that with others +%\end{itemize} +%\end{columns} +%\end{frame} +% +%\begin{frame} +%\frametitle{Popular open source projects} +%\begin{columns} +%\column{.5\textwidth} +%\begin{itemize} +%\item Linux +%\item Wordpress +%\item Firefox +%\item GIMP +%\item Python +%\end{itemize} +%\column{.5\textwidth} +%\centering +%\includegraphics[height=0.80\textheight]{OS-Software} +%\end{columns} +%\end{frame} +% +%\begin{frame} +%\frametitle{How popular is Open Source?}\pause +%\begin{itemize} +%\item Android - most successful operating system with over 2 billion devices\pause +%\item Cloud - 9/10 of the top cloud providers run Linux\pause +%\item Over 60\% of the web use Open Source web servers\pause +%\item The top 500 super computers run Linux\% of the web use Open Source web servers\pause +%\item Car entertainment systems, routers, rockets + space, smart home applicances, TVs... +%\end{itemize} +%\end{frame} +% +% +%\begin{frame} +%\frametitle{Why care?}\pause +%\begin{itemize} +%\item Security\pause +%\item Cost\pause +%\item Support\pause +%\item Avoid-lock in +%\end{itemize} +%\end{frame} +% +% +% +%\section{What is Open Source Firmware?} +%\begin{frame} +%\frametitle{Stack} +%\begin{overprint} +%\onslide<1> +%\onslide<2>\centering\includegraphics[height=0.85\textheight]{Hardware} +%\onslide<3>\centering\includegraphics[height=0.85\textheight]{Firmware} +%\onslide<4>\centering\includegraphics[height=0.85\textheight]{Kernel} +%\onslide<5>\centering\includegraphics[height=0.85\textheight]{OS} +%\onslide<6>\centering\includegraphics[height=0.85\textheight]{Software} +%\onslide<7->\centering\includegraphics[height=0.85\textheight]{Firmware-highlighted} +%\end{overprint} +%\end{frame} +% +%\section{Why is Open Source Firmware important?} +%\begin{frame} +%\frametitle{Why care? An example}\pause +%\begin{columns} +%\column{.5\textwidth} +%Intel ME: +%\begin{itemize} +%\item Inside all Intel CPUs since 2008\pause +%\item 32 bit CPU that runs Minix\pause +%\item Has it's own IP and MAC address\pause +%\item No official documentation on how to disable it\pause +%\item Used for remote management\pause +%\end{itemize} +%\column{.5\textwidth} +%What it can do: +%\begin{itemize} +%\item Format or reimage your computer without needing to be on +%\item Connect to the internet and send packets regardless of OS firewall +%\item Full access to system memory +%\item Full access to TCP/IP stack +%\item With Intel ME 7.1, it can also run Java applets +%\end{itemize} +%\end{columns} +%\vspace{1em}\pause +%AMD's equivalent called PSP in all AMD CPUs since 2014 +%\end{frame} +% +%\begin{frame} +%\centering\includegraphics[height=0.85\textheight]{intel-me-report}\\ +%\tiny{\href{https://www.wired.com/story/intel-management-engine-vulnerabilities-pcs-servers-iot/}{https://www.wired.com/story/intel-management-engine-vulnerabilities-pcs-servers-iot/}} +%\end{frame} +% +%\begin{frame} +%\frametitle{Alright, but who cares?}\pause +%\centering\includegraphics[height=0.75\textheight]{mullvad}\\ +%\tiny{\href{https://mullvad.net/en/blog/2019/8/7/open-source-firmware-future/}{https://mullvad.net/en/blog/2019/8/7/open-source-firmware-future/}} +%\end{frame} +% +%\begin{frame} +%\frametitle{Alright, but who really cares?}\pause +%\centering\includegraphics[height=0.75\textheight]{facebook}\\ +%\tiny{\href{https://www.phoronix.com/scan.php?page=news\_item\&px=Facebook-Loves-OSS-Firmware}{https://www.phoronix.com/scan.php?page=news\_item\&px=Facebook-Loves-OSS-Firmware}} +%\end{frame} +% +%\begin{frame} +%\frametitle{What does Open Source Firmware run on?}\pause +%\begin{columns} +%\column{.5\textwidth} +%\centering +%\includegraphics[height=0.35\textheight]{coreboot-flash}\\ +%\tiny{\href{https://ch1p.io/coreboot-mbp101-flashing/}{https://ch1p.io/coreboot-mbp101-flashing/}}\\\pause +%\includegraphics[height=0.35\textheight]{chromebook}\\ +%\tiny{\href{https://www.google.com/intl/en\_uk/chromebook/device/asus-chromebook-flip-c436-512gb/}{https://www.google.com/intl/en\_uk/chromebook/device/asus-chromebook-flip-c436-512gb/}}\pause +%\column{.5\textwidth} +%\centering +%\includegraphics[height=0.35\textheight]{tesla}\\ +%\tiny{\href{https://www.phoronix.com/scan.php?page=news\_item\&px=Tesla-Uses-Coreboot}{https://www.phoronix.com/scan.php?page=news\_item\&px=Tesla-Uses-Coreboot}}\pause\\ +%\includegraphics[height=0.35\textheight]{pine64} +%\end{columns} +%\end{frame} +% +% +%\begin{frame} +%\frametitle{Open Source Firmware Projects} +%\centering\includegraphics[height=0.75\textheight]{opensourcefirmware}\\ +%\tiny{\href{https://www.osfc.io/}{https://www.osfc.io/}} +%\end{frame} +% +%\begin{frame} +%\frametitle{Open Source Firmware Conference} +%\centering +%\includegraphics[height=0.75\textheight]{conference}\\ +%\tiny{\href{https://www.osfc.io/}{https://www.osfc.io/}} +%\end{frame} +% +% +%\begin{frame} +%\frametitle{Where are we now?} +%\begin{itemize} +%\item Chromebook's have free firmware +%\item A selection old laptops pre-2014 if you enjoy taking apart computers +%\item Very few specialised devices +%\end{itemize} +%\end{frame} +% +%\begin{frame} +%\frametitle{Future of proprietary chips and firmware} +%\centering\includegraphics[height=0.75\textheight]{pluton}\\ +%\tiny{\href{https://www.microsoft.com/security/blog/2020/11/17/meet-the-microsoft-pluton-processor-the-security-chip-designed-for-the-future-of-windows-pcs/}{https://www.microsoft.com/security/blog/2020/11/17/meet-the-microsoft-pluton-processor-the-security-chip-designed-for-the-future-of-windows-pcs/}} +%\end{frame} +% +%\begin{frame} +%\frametitle{What else is there?}\pause +%\begin{columns} +%\column{.5\textwidth} +%\centering\includegraphics[height=0.85\textheight]{Breakdown}\pause +%\column{.5\textwidth} +%\begin{itemize} +%\item IBM's OpenPOWER Foundation - open firmware and software\pause +%\item RISC-V, open instruction set (Alternative to x86 and ARM)\pause +%\item Pine64 devices - open firmware and software\pause +% +%\end{itemize} +%\end{columns} +%\end{frame} +% +%\section{Summary} +%\begin{frame} +%\begin{itemize} +%\item Open Source Firmware exists but on very few devices +%\begin{itemize} +%\item coreboot +%\item open-bmc +%\end{itemize} +%\item What's next? +%\begin{itemize} +%\item RISC-V +%\item OpenPOWER +%\item Open Source firmware for consumer level platforms (mainline AMD and Intel) +%\end{itemize} +%\item Microsoft Pluton +%\end{itemize} +%\frametitle{Summary} +%\end{frame} + +\end{document} From 9949125a5db6ea887e911914d9aa2b2f933c1b98 Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Mon, 16 May 2022 14:02:40 +0100 Subject: [PATCH 33/36] Add demo material --- data/VID_20220214_101740.mp4 | 3 + docs/project-demo/demo-material/demo.md | 43 ++++++++++ .../demo-material/helper-functions.py | 82 +++++++++++++++++++ .../latex/img/HL-Diagram-CNN-Simplified.pdf | 3 + .../project-demo/latex/img/HL-Diagram-CNN.pdf | 3 + docs/project-demo/latex/presentation.pdf | 4 +- docs/project-demo/latex/presentation.tex | 12 +++ 7 files changed, 148 insertions(+), 2 deletions(-) create mode 100644 data/VID_20220214_101740.mp4 create mode 100644 docs/project-demo/demo-material/demo.md create mode 100644 docs/project-demo/demo-material/helper-functions.py create mode 100644 docs/project-demo/latex/img/HL-Diagram-CNN-Simplified.pdf create mode 100644 docs/project-demo/latex/img/HL-Diagram-CNN.pdf diff --git a/data/VID_20220214_101740.mp4 b/data/VID_20220214_101740.mp4 new file mode 100644 index 0000000..1d5e8fa --- /dev/null +++ b/data/VID_20220214_101740.mp4 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d26f3e9eca643ad04a001d9ac6d33afcff20b6411a32e8a30c643a8647724b84 +size 164545500 diff --git a/docs/project-demo/demo-material/demo.md b/docs/project-demo/demo-material/demo.md new file mode 100644 index 0000000..a0728f9 --- /dev/null +++ b/docs/project-demo/demo-material/demo.md @@ -0,0 +1,43 @@ +1. Show Docker stuff +Explain: docker compose build +Run: docker compose run autophotographer +Run: cd /mmp-osp1 +Run: pip install -e . + +2. Explain missing function load_files() +Run: python src/autophotographer/autophotographer_main.py -i /datasets/Hannah/overcastjuly/melindwr1/output.avi +Explain: load_files() is never called +Explain: No logic for working with 0 compatible files +Edit: config file to disable ingore_video +Run: python src/autophotographer/autophotographer_main.py -i /datasets/Hannah/overcastjuly/melindwr1/output.avi +Explain: Tuple of file formats aren't a comprehensive method +Explain: Tries to load videos directly as images +Edit: config file to enable ingore_video +Explain: why frames are exported seperate to images + +3. Show a successful run +Run: python src/autophotographer/autophotographer_main.py -i /datasets/Hannah/overcastjuly/melindwr1/* +Explain: ouput from command + +4. Discuss filters +- Brightness (Upper and lower bounds) +- Contrast (Upper and lower bounds) +- Filesize (Lower bounds) +- Focus (Lower bounds) + - Laplacian + - Fast Fourier Transform + +5. Discuss how contrast would be calculated (difference in luminance / min+max) + +6. Automatic threshold calculation +Explain: Calculating thresholds from percentiles + +7. CNN Performance +7.1 Run: A couple of images through +7.2 Run: Experiment 3 +7.3 Run: Experiment 4 +7.4 Discuss: Why ratings are exclusively between 5-7 + +8. + +If there's time discuss Terraform diff --git a/docs/project-demo/demo-material/helper-functions.py b/docs/project-demo/demo-material/helper-functions.py new file mode 100644 index 0000000..55fecdf --- /dev/null +++ b/docs/project-demo/demo-material/helper-functions.py @@ -0,0 +1,82 @@ +import cv2 +import os +from os.path import abspath +import datetime +import matplotlib.pyplot as plt +from tqdm import tqdm +import random + +# Export's video frames +def video_to_frames(path): + print("[INFO] Loading video...") + basename = os.path.splitext(os.path.split(path)[1])[0] + output_dir_name = basename + "_frames" + output_dir = os.path.join(os.path.split(path)[0], output_dir_name) + if not os.path.exists(output_dir): + os.makedirs(output_dir) + else: + print("[INFO] Outut folder \"{}\" already exists".format(output_dir)) + return + stream = cv2.VideoCapture(path) + count = 0 + print("[INFO] Reading and saving frames...") + while True: + (retrieved, frame) = stream.read() + if not retrieved: + break + count += 1 + filename = "frame-{}.jpg".format(count) + path = os.path.abspath(os.path.join(output_dir, filename)) + cv2.imwrite(path, frame) + print("[INFO] Frames saved to \"{}\"".format(output_dir)) + +# Plot images +def plot_images(paths): + # plot the images + number_of_images = len(paths) + if number_of_images % 5 == 0: + row = number_of_images // 5 + else: + row = (number_of_images // 5) + 1 + column = 5 + width = 250 + size = width * row + outputDir = os.path.join(os.path.dirname(__name__), "output") + fileName = datetime.datetime.now().strftime("%G-%m-%dT%H%M%S") + ".png" + filePath = os.path.join(outputDir, fileName) + + if not os.path.exists(outputDir): + os.makedirs(outputDir) + + heightOfFig = 6 * row + fig = plt.figure(figsize=(15, heightOfFig)) + + # Plot the 5 highest on the first row + plotIndex = 1 + for path in tqdm(paths): + image = cv2.imread(path) + image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) + height = int(image.shape[0] * (width / image.shape[0])) + image = cv2.resize(image, (width, height)) + fig.add_subplot(row, column, plotIndex) + plt.imshow(image) + plt.axis('off') + plt.title(os.path.split(path)[1]) + plt.tight_layout() + plotIndex += 1 + + fig.tight_layout() + plt.savefig(filePath) + +def list_dir_abs(directory): + dirAbsPath = os.path.abspath(directory) + listOfItems = os.listdir(directory) + listOfPaths = [] + for item in listOfItems: + path = os.path.join(dirAbsPath, item) + listOfPaths.append(path) + return listOfPaths + +def pickRandomNum(paths, num): + ranPaths = random.choices(paths, k=num) + return ranPaths \ No newline at end of file diff --git a/docs/project-demo/latex/img/HL-Diagram-CNN-Simplified.pdf b/docs/project-demo/latex/img/HL-Diagram-CNN-Simplified.pdf new file mode 100644 index 0000000..0755762 --- /dev/null +++ b/docs/project-demo/latex/img/HL-Diagram-CNN-Simplified.pdf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:521edd694fb6e5c47cf80862fa2e7ab7066ad7b2bab08703d857130864428219 +size 61504 diff --git a/docs/project-demo/latex/img/HL-Diagram-CNN.pdf b/docs/project-demo/latex/img/HL-Diagram-CNN.pdf new file mode 100644 index 0000000..d64190a --- /dev/null +++ b/docs/project-demo/latex/img/HL-Diagram-CNN.pdf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:685e65e8bc3f249eb1141dc2dc28d8c7abb6f5a380a2e26b9ae5830146af0221 +size 149527 diff --git a/docs/project-demo/latex/presentation.pdf b/docs/project-demo/latex/presentation.pdf index 6bbadf5..d11941b 100644 --- a/docs/project-demo/latex/presentation.pdf +++ b/docs/project-demo/latex/presentation.pdf @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:47dfa7488a24b1e52bab5f335d61c2aa5ccd52df030d840320fe143cba3d1143 -size 112968 +oid sha256:53c6227533c5a2e60b8fd2e2b8f1d67e0a4be5919e1b12dc3dabd7376e8518f3 +size 325928 diff --git a/docs/project-demo/latex/presentation.tex b/docs/project-demo/latex/presentation.tex index 0657c03..867b001 100644 --- a/docs/project-demo/latex/presentation.tex +++ b/docs/project-demo/latex/presentation.tex @@ -27,7 +27,19 @@ \includegraphics[width=\textwidth]{architecture-2}\\ \end{figure} \end{frame} +\begin{frame} +\begin{figure} +\centering +\includegraphics[height=0.95\textheight]{HL-Diagram-CNN}\\ +\end{figure} +\end{frame} +\begin{frame} +\begin{figure} +\centering +\includegraphics[height=0.95\textheight]{HL-Diagram-CNN-Simplified}\\ +\end{figure} +\end{frame} %\begin{frame} % \tableofcontents From b8e260affadd03f3bf27b336184f3a621093f606 Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Wed, 18 May 2022 14:59:31 +0100 Subject: [PATCH 34/36] Added demo config files --- .../demo-material/config-files/CNN-only.yml | 34 +++++++++++++++++++ .../demo-material/config-files/default.yml | 34 +++++++++++++++++++ .../demo-material/config-files/tuned.yml | 34 +++++++++++++++++++ .../output/2022-05-16T112115.png | 3 ++ .../output/2022-05-16T113150.png | 3 ++ .../output/2022-05-16T113215.png | 3 ++ .../output/2022-05-16T113321.png | 3 ++ 7 files changed, 114 insertions(+) create mode 100644 docs/project-demo/demo-material/config-files/CNN-only.yml create mode 100644 docs/project-demo/demo-material/config-files/default.yml create mode 100644 docs/project-demo/demo-material/config-files/tuned.yml create mode 100644 docs/project-demo/demo-material/output/2022-05-16T112115.png create mode 100644 docs/project-demo/demo-material/output/2022-05-16T113150.png create mode 100644 docs/project-demo/demo-material/output/2022-05-16T113215.png create mode 100644 docs/project-demo/demo-material/output/2022-05-16T113321.png diff --git a/docs/project-demo/demo-material/config-files/CNN-only.yml b/docs/project-demo/demo-material/config-files/CNN-only.yml new file mode 100644 index 0000000..7519951 --- /dev/null +++ b/docs/project-demo/demo-material/config-files/CNN-only.yml @@ -0,0 +1,34 @@ +--- +# Configuration file for the autophographer tool + +# List of filters to apply in order +# Note: Possible filters include: brightness, filesize, contrast, focus +filters: + # - brightness + # - filesize + # - contrast + # - focus + +# Whether or not to apply CNN ranking +CNNrank: True + +# Ignore video files and don't bother processing them into frames +# Note: Useful if directory contains original video and indivual frames from video (prevents processing the same frames more than once) +ignore_video: True + +# Options for brightness filter +brightness_options: + threshold: 0.25 + +# Options for filesize filter +filesize_options: + threshold: 0.35 + +# Options for contrast filter +contrast_options: + threshold: 0.35 + +# Options for focus filter +focus_options: + threshold: 0.5 +... \ No newline at end of file diff --git a/docs/project-demo/demo-material/config-files/default.yml b/docs/project-demo/demo-material/config-files/default.yml new file mode 100644 index 0000000..8f8ce19 --- /dev/null +++ b/docs/project-demo/demo-material/config-files/default.yml @@ -0,0 +1,34 @@ +--- +# Configuration file for the autophographer tool + +# List of filters to apply in order +# Note: Possible filters include: brightness, filesize, contrast, focus +filters: + - brightness + - filesize + - contrast + - focus + +# Whether or not to apply CNN ranking +CNNrank: False + +# Ignore video files and don't bother processing them into frames +# Note: Useful if directory contains original video and indivual frames from video (prevents processing the same frames more than once) +ignore_video: True + +# Options for brightness filter +brightness_options: + threshold: 0.25 + +# Options for filesize filter +filesize_options: + threshold: 0.35 + +# Options for contrast filter +contrast_options: + threshold: 0.35 + +# Options for focus filter +focus_options: + threshold: 0.5 +... \ No newline at end of file diff --git a/docs/project-demo/demo-material/config-files/tuned.yml b/docs/project-demo/demo-material/config-files/tuned.yml new file mode 100644 index 0000000..8f8ce19 --- /dev/null +++ b/docs/project-demo/demo-material/config-files/tuned.yml @@ -0,0 +1,34 @@ +--- +# Configuration file for the autophographer tool + +# List of filters to apply in order +# Note: Possible filters include: brightness, filesize, contrast, focus +filters: + - brightness + - filesize + - contrast + - focus + +# Whether or not to apply CNN ranking +CNNrank: False + +# Ignore video files and don't bother processing them into frames +# Note: Useful if directory contains original video and indivual frames from video (prevents processing the same frames more than once) +ignore_video: True + +# Options for brightness filter +brightness_options: + threshold: 0.25 + +# Options for filesize filter +filesize_options: + threshold: 0.35 + +# Options for contrast filter +contrast_options: + threshold: 0.35 + +# Options for focus filter +focus_options: + threshold: 0.5 +... \ No newline at end of file diff --git a/docs/project-demo/demo-material/output/2022-05-16T112115.png b/docs/project-demo/demo-material/output/2022-05-16T112115.png new file mode 100644 index 0000000..99b4ab9 --- /dev/null +++ b/docs/project-demo/demo-material/output/2022-05-16T112115.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:86e9225320395bd23f62316c96990b811b4975af628f0a3e8f8c3f279e481493 +size 655486 diff --git a/docs/project-demo/demo-material/output/2022-05-16T113150.png b/docs/project-demo/demo-material/output/2022-05-16T113150.png new file mode 100644 index 0000000..6b359cb --- /dev/null +++ b/docs/project-demo/demo-material/output/2022-05-16T113150.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:29fca8e3dc1c9b02862b7f3da4f5f79857cdd67d7fd9105137f2a8daf11c85b9 +size 380661 diff --git a/docs/project-demo/demo-material/output/2022-05-16T113215.png b/docs/project-demo/demo-material/output/2022-05-16T113215.png new file mode 100644 index 0000000..7787536 --- /dev/null +++ b/docs/project-demo/demo-material/output/2022-05-16T113215.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1ad6c1b22706d842bce9fb93daac32c18b27add59e7ffacae5836f696225a8d0 +size 480231 diff --git a/docs/project-demo/demo-material/output/2022-05-16T113321.png b/docs/project-demo/demo-material/output/2022-05-16T113321.png new file mode 100644 index 0000000..8d5fd01 --- /dev/null +++ b/docs/project-demo/demo-material/output/2022-05-16T113321.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5b2747e0b88bb3d4993820be92a6957d96753dcbf732b41e0a5f6f5f870cd291 +size 3452432 From a1bd5002cac7afe2e78a562f0ac39d4418106f12 Mon Sep 17 00:00:00 2001 From: oscarpocock Date: Thu, 26 May 2022 16:41:07 +0100 Subject: [PATCH 35/36] Added FFT methods --- .../demo-material/helper-functions.py | 44 ++++++++++++++++++- 1 file changed, 42 insertions(+), 2 deletions(-) diff --git a/docs/project-demo/demo-material/helper-functions.py b/docs/project-demo/demo-material/helper-functions.py index 55fecdf..e67e16e 100644 --- a/docs/project-demo/demo-material/helper-functions.py +++ b/docs/project-demo/demo-material/helper-functions.py @@ -4,7 +4,10 @@ from os.path import abspath import datetime import matplotlib.pyplot as plt from tqdm import tqdm -import random +import numpy as np +import random +from PIL import Image +import requests # Export's video frames def video_to_frames(path): @@ -79,4 +82,41 @@ def list_dir_abs(directory): def pickRandomNum(paths, num): ranPaths = random.choices(paths, k=num) - return ranPaths \ No newline at end of file + return ranPaths + +def showImage(path): + image = cv2.imread(path) + image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) + plt.imshow(image) + plt.show() + +def showDiscreteFFT(image): + fftImage = np.fft.fft2(image) + fftShift = np.fft.fftshift(fftImage) + magnitude = 20 * np.log(np.abs(fftShift)) + + fig = plt.figure(figsize=(15, 6)) + fig.add_subplot(1, 2, 1) + plt.imshow(image, cmap="gray") + fig.add_subplot(1, 2, 2) + plt.imshow(magnitude, cmap="gray") + fig.tight_layout() + plt.show() + +def loadImageFromURL(url): + response = requests.get(url) + image = Image.open(requests.get(url, stream=True).raw) + return image + +def PILToNumpy(image): + image = np.array(image) + return image + +def URL2FFT(url): + image = loadImageFromURL(url) + if image.mode == "RGB": + image = PILToNumpy(image) + image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY) + else: + image = PILToNumpy(image) + showDiscreteFFT(image) \ No newline at end of file From 01e9656e5c26077af4a85e42b94a86aded57b4ce Mon Sep 17 00:00:00 2001 From: Oscar Pocock Date: Sat, 28 May 2022 16:34:46 +0100 Subject: [PATCH 36/36] Final project demo files --- docs/project-demo/demo-material/demo.md | 2 +- docs/project-demo/demo-material/helper-functions.py | 9 ++++++++- 2 files changed, 9 insertions(+), 2 deletions(-) diff --git a/docs/project-demo/demo-material/demo.md b/docs/project-demo/demo-material/demo.md index a0728f9..a0cb9d0 100644 --- a/docs/project-demo/demo-material/demo.md +++ b/docs/project-demo/demo-material/demo.md @@ -17,7 +17,7 @@ Explain: why frames are exported seperate to images 3. Show a successful run Run: python src/autophotographer/autophotographer_main.py -i /datasets/Hannah/overcastjuly/melindwr1/* -Explain: ouput from command +Explain: output from command 4. Discuss filters - Brightness (Upper and lower bounds) diff --git a/docs/project-demo/demo-material/helper-functions.py b/docs/project-demo/demo-material/helper-functions.py index e67e16e..f37c90f 100644 --- a/docs/project-demo/demo-material/helper-functions.py +++ b/docs/project-demo/demo-material/helper-functions.py @@ -8,6 +8,7 @@ import numpy as np import random from PIL import Image import requests +import json # Export's video frames def video_to_frames(path): @@ -119,4 +120,10 @@ def URL2FFT(url): image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY) else: image = PILToNumpy(image) - showDiscreteFFT(image) \ No newline at end of file + showDiscreteFFT(image) + +def fileToList(path): + with open(path) as f: + contents = f.read().rstrip() + paths = contents.strip('][').replace("'", "").split(', ') + return paths \ No newline at end of file