https://github.com/robvanvolt/DALLE-datasets

This is a summary of easily available datasets for generalized DALLE-pytorch training.
https://github.com/robvanvolt/DALLE-datasets

Last synced: about 2 months ago
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This is a summary of easily available datasets for generalized DALLE-pytorch training.

• Host: GitHub
• URL: https://github.com/robvanvolt/DALLE-datasets
• Owner: robvanvolt
• License: mit
• Created: 2021-05-01T22:53:22.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2022-04-19T20:27:34.000Z (over 2 years ago)
• Last Synced: 2024-08-04T03:12:02.070Z (5 months ago)
• Language: Python
• Size: 497 KB
• Stars: 127
• Watchers: 3
• Forks: 16
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
## DALLE-datasets

This is a summary of easily available, high-quality datasets consisiting of captioned image files for generalized DALLE-pytorch training (https://github.com/lucidrains/DALLE-pytorch).

The scripts help you download and resize the files from the given sources.

* general datasets

  * Conceptual Images 12m

  * Wikipedia

  * Filtered yfcc100m

  * Open Images

* specific datasets

  * None yet

## Helper scripts

All helper scripts can be found in the utilities folder now:

* TFrecords to WebDataset converter

* Image-Text-Folder to WebDataset converter

* Dataset sanitycheck for image-text-files

* Example reader for WebDataset files

### Sanitycheck for downloaded datasets

The following command will look for image-text-pairs (.jpg / .png / .bmp) and return a csv table with incomplete data.

When you add the optional argument -DEL, the incomplete files get deleted. The python scripts checks one folder and the first subdirectories.

```python sanity_check.py --dataset_folder my-dataset-folder```

## Pretrained models

If you want to continue training on pretrained models or even upload your own Dall-E model, head over to https://github.com/robvanvolt/DALLE-models

## Credits

Special thanks go to Romaine, who improved the download scripts and made the great WebDataset format more accessible with his continuous coding efforts! 🙏 

A lot of inspiration was taken from https://github.com/yashbonde/dall-e-baby - unfortunately that repo does not get updated anymore...

Also, the shard creator was inspired by https://github.com/tmbdev-archive/webdataset-examples/blob/master/makeshards.py.

The custom tokenizer was inspired by afiaka87, who showed a simple way to generate custom tokenizers with youtokentome.