AsafShul/PoDD
Official PyTorch Implementation for the "Distilling Datasets Into Less Than One Image" paper.
This project helps machine learning researchers compress vast image datasets into highly efficient 'posters' – single images that represent entire classes of data. By condensing many images into significantly fewer pixels, it allows for faster model training with comparable accuracy. Data scientists and AI researchers working with large image classification tasks would find this valuable.
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Use this if you need to drastically reduce the size of your image training datasets to speed up model development and iteration, especially for image classification.
Not ideal if your primary goal is interpretability of individual images in the distilled dataset rather than overall model performance on the compressed data.
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Python
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Last pushed
Jun 06, 2024
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