| license: other | |
| task_categories: | |
| - image-classification | |
| - zero-shot-image-classification | |
| - text-to-image | |
| language: | |
| - en | |
| tags: | |
| - art | |
| - anime | |
| - not-for-all-audiences | |
| size_categories: | |
| - 1M<n<10M | |
| annotations_creators: | |
| - no-annotation | |
| source_datasets: | |
| - zerochan | |
| # Zerochan Newest 4M Re-encoded Dataset | |
| This is the re-encoded dataset of [deepghs/zerochan_full](https://huggingface.co/datasets/deepghs/zerochan_full). And all the resized images are maintained here. | |
| There are 4072945 images in total. The maximum ID of these images is 4587464. Last updated at `2025-09-18 14:36:41 JST`. | |
| # How to Painlessly Use This | |
| Use [cheesechaser](https://github.com/deepghs/cheesechaser) to quickly get images from this repository. | |
| Before using this code, you have to **grant the access from this gated repository**. And then **set your personal HuggingFace token into `HF_TOKEN` environment variable** to give the code authorization for this repository. | |
| ```python | |
| from cheesechaser.datapool import ZerochanWebpDataPool | |
| pool = ZerochanWebpDataPool() | |
| pool.batch_download_to_directory( | |
| # download images #3000000-3000100, any ranges or id lists are okay | |
| resource_ids=range(3000000, 3000100), | |
| # save to directory /data/zerochan_webp | |
| dst_dir='/data/zerochan_webp', | |
| ) | |
| ``` | |