--- pretty_name: 32x32 Pixel Icon Dataset (Z-Image-Turbo) tags: - image - pixel-art - synthetic - diffusion task_categories: - unconditional-image-generation - text-to-image size_categories: - 1K add noise -> train -> predict noise -> sample). > **License**: TODO -- set before publishing. Check the license of the > generating model (Tongyi-MAI/Z-Image-Turbo) and this repo's own terms for any > restrictions that apply to the generated images before choosing a license here. ## Generation Images were rendered at 512px and downsampled to 32px with a progressive Lanczos pipeline (halving each step, never more than 2x per call) followed by a light unsharp mask (sharpen=0.6) to recover edge definition. Quality filtering: - **degenerate filter**: drops flat/blank/over- or under-exposed outputs (min_colors=10, min_lum_std=10) - **perceptual dedup**: dhash (dhash_8x9, distance<4) within each (subject, style) group removes near-duplicates ## Stats - prompt combos: 232 - attempted: 1160 - kept: 1059 - filtered (degenerate): 1 - filtered (duplicate): 100 - generation failures: 0 Categories: - **animal**: 12 subjects - **vehicle**: 8 subjects - **object**: 10 subjects - **food**: 7 subjects - **nature**: 8 subjects - **building**: 5 subjects - **character**: 8 subjects ## Structure Standard HuggingFace `imagefolder` layout -- images and `metadata.jsonl` share this directory, keyed by `file_name`: ``` .png metadata.jsonl # file_name, prompt, category, subject, style, seed, gen_size, dhash, metrics manifest.json # dataset-level generation params (not read by the loader) ``` Load with: ```python from datasets import load_dataset ds = load_dataset("imagefolder", data_dir=".") ``` Each `metadata.jsonl` record also carries per-image `metrics` (colors, luminance std, edge density) captured at generation time.