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Single Image Pretraining of Visual Representations

Note: this is an edited version of the code from here, where we've added the video-generation code.

Usage

For generating image-datasets run:

python make_single_img_dataset.py --imgpath images/ameyoko.jpg --targetpath ./out/ameyoko_dataset
# with 1.2M samples, the dataset will be roughly 100Gb large

For generating fake-video datasets from a single image run:

python make_fakevideo_dataset.py --imgpath images/ameyoko.jpg --targetpath ./out/ameyoko_video_dataset
# with 200K samples, the dataset will be roughly 10Gb large 

Reference

If you find this code/idea useful, please consider citing the paper: A critical analysis of self-supervision, or what we can learn from a single image, Asano et al. ICLR 2020

@inproceedings{asano2020a,
title={A critical analysis of self-supervision, or what we can learn from a single image},
author={Asano, Yuki M. and Rupprecht, Christian and Vedaldi, Andrea},
booktitle={International Conference on Learning Representations (ICLR)},
year={2020},
}