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May 7, 2021 19:38
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Creates a video from sequential training progress images. Skips more and more frames as iterations increase.
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| from glob import glob | |
| # Creates a video from a folder containing images of training progress | |
| # Allows sampling the image less often as iterations increase | |
| # (Requires images be sortable by filename for now. Could use modification date too) | |
| def render_video(output_path="/content/taming-transformers/output.mp4", src_path="/content/taming-transformers/", file_glob="*.png", step_increase_every=100): | |
| tmp_path = "/tmp/latentvisions_tmp" | |
| files = glob(src_path+file_glob) | |
| files.sort() | |
| if len(files) == 0: | |
| print(f"No files found in '{src_path}{file_glob}'. Returning...") | |
| return | |
| !rm -rf $tmp_path | |
| !mkdir -p $tmp_path | |
| for i, filepath in enumerate(files): | |
| # this is a bit hacky. we should be adding a float to get | |
| # smooth increase in steps. | |
| save_step = i % (i//step_increase_every + 1) == 0 | |
| if save_step: | |
| !cp -v $filepath $tmp_path | |
| else: | |
| !mv $filepath /tmp | |
| !ffmpeg -y -r 20 -pattern_type glob -i "{tmp_path+"/"+file_glob}" -vcodec libx264 -crf 15 -pix_fmt yuv420p {output_path} -hide_banner -loglevel error | |
| render_video() |
Author
I updated it to make it render an mp4 that is understood by more players... I didn't test it for a while so let me know if there are any bugs
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Thanks for this. On stylegan2 skipping steps traversing the latent where loss worsened or went the wrong direction seemed to help smooth a lot of the animation for me, but this is great for quick experiments while i'm reimplementing my VQGAN related implementation. I need to run metrics on each frame generation and record the hyperparameters as I think that basic heuristic and secondary ones for momentum can be extended into something better if I analyze or find some more pointers on how people are trying to smooth and create coherent latent animations now.