Add demo material

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

docs/project-demo/demo-material/helper-functions.py

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+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

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