2.5 KiB
title | date |
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Week 3 | 2022-02-20T12:46:55Z |
Filming footage
At the start of the week I went into town to film some practise footage to work with later (up until this point I had been experimenting with footage limited by my bedroom walls). I took some basic vertical and horizontal footage of the town - no nature or breach footage yet.
Gaining more useful information
I used the footage I had recorded at the start of the week and revised my "filesize" code. I made a new function order_frames_by_filesize()
which orders the frames by the filesize and prints the name of size of each frame in order.
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def order_frames_by_filesize():
"""Order the frames by filesize and print the filenames and their sizes"""
frames = os.listdir(outputfolder)
# sort the frames by their filesize
frames = sorted(frames,
key = lambda x: os.stat(os.path.join(outputfolder, x)).st_size, reverse = True)
# print every frame and it's size in a human readable format
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))
Analysing datasets
There's been a few datasets that I've previously looked at which could be useful to use for this project. I wasn't sure how they would perform with the data I was expecting to use. AVA1 was trained on data that had been photographed under ideal conditions by profesionals. This won't reflect the frames extracted by the footage in this project's use case. I wasn't sure if this distinction was significant enough to effect the results of a trained model. I had previously found a project2 which had models pretrained using AVA1 I could use to predict an aesthetic value from images I provided.
1:1 Weekly meeting
- We discussed that during week 4 I should be looking at implementing CNNs as training might take a while and therefore should be a priority.
- Look at what other people are doing with aesthetic analysis to get an idea on how the code works.
- Attempt to get a basic CNN working.
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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. ↩︎
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Image Quality Assessment: https://github.com/idealo/image-quality-assessment - Idealo ↩︎