--- dataset_info: features: - name: source_id dtype: string - name: source dtype: string - name: image dtype: image - name: tags sequence: string - name: url dtype: string - name: text dtype: string - name: selector dtype: string splits: - name: train num_bytes: 53726659168.0 num_examples: 279296 download_size: 53423627875 dataset_size: 53726659168.0 pretty_name: 'E621 Rising V3 Image Dataset' size_categories: - 100K

NSFW

This dataset is not suitable for use by minors. The dataset contains X-rated/NFSW content.

# E621 Rising V3: Curated Image Dataset * **279,296** images (53GB) downloaded from `e621.net` (90% of samples), `gelbooru.com`, `danbooru.com`, and `rule34.xxx` * **6,820** [tags](https://huggingface.co/datasets/hearmeneigh/e621-rising-v3-preliminary-data/blob/main/tag-counts.by-name.json) * Used to train [E621 Rising v3](https://huggingface.co/hearmeneigh/e621-rising-v3) SDXL model This dataset was created with [Dataset Rising](https://github.com/hearmeneigh/dataset-rising) toolchain and a [custom configuration](https://github.com/hearmeneigh/e621-rising-configs). You can use these tools to train your own version! ## Image Processing * Only `jpg` and `png` images were considered * Image width and height have been clamped to `(0, 1024]px`; larger images have been resized to meet the limit * Alpha channels have been removed * All images have been converted to `jpg` format * All images have been converted to TrueColor `RGB` * All images have been verified to load with `Pillow` * Metadata from E621 is [available here](https://huggingface.co/datasets/hearmeneigh/e621-rising-v3-preliminary-data) ## Tags Comprehensive list of 6,820 tags and counts: * [By name](https://huggingface.co/datasets/hearmeneigh/e621-rising-v3-preliminary-data/blob/main/tag-counts.by-name.json) * [By count](https://huggingface.co/datasets/hearmeneigh/e621-rising-v3-preliminary-data/blob/main/tag-counts.by-count.json) ### Additional Tags * `rating_explicit` * `rating_questionable` * `rating_safe` * `rising_masterpiece` * `rising_unpopular` * `favorites_below_X` (25, 50, 100, 250, 500, 1000) * `favorites_above_X` (250, 500, 1000, 2000, 3000, 4000) * `score_below_X` (0, 25, 50, 100, 250, 500) * `score_above_X` (100, 250, 500, 1000, 1500, 2000)