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metadata
dataset_info:
  - config_name: photos
    features:
      - name: id
        dtype: string
      - name: provider
        dtype: string
      - name: source_id
        dtype: string
      - name: query
        dtype: string
      - name: title
        dtype: string
      - name: author
        dtype: string
      - name: license
        dtype: string
      - name: license_url
        dtype: string
      - name: source_page
        dtype: string
      - name: original_url
        dtype: string
      - name: input_path
        dtype: string
      - name: target_path
        dtype: string
      - name: sha256
        dtype: string
      - name: input
        dtype: image
      - name: target
        dtype: image
    splits:
      - name: train
        num_bytes: 2235579871
        num_examples: 82651
      - name: test
        num_bytes: 42450997
        num_examples: 1639
    download_size: 2123870018
    dataset_size: 2278030868
  - config_name: scenes
    features:
      - name: id
        dtype: string
      - name: split
        dtype: string
      - name: kind
        dtype: string
      - name: caption
        dtype: string
      - name: style
        dtype: string
      - name: background
        dtype: string
      - name: objects
        dtype: string
      - name: slots
        dtype: string
      - name: sprites
        dtype: string
      - name: background_path
        dtype: string
      - name: path
        dtype: string
      - name: image
        dtype: image
    splits:
      - name: train
        num_bytes: 37273165
        num_examples: 50000
      - name: test
        num_bytes: 1491562
        num_examples: 2000
    download_size: 27078810
    dataset_size: 38764727
  - config_name: sprites
    features:
      - name: path
        dtype: string
      - name: pack
        dtype: string
      - name: creator
        dtype: string
      - name: license
        dtype: string
      - name: source_url
        dtype: string
      - name: width
        dtype: string
      - name: height
        dtype: string
      - name: label
        dtype: string
      - name: label_source
        dtype: string
      - name: image
        dtype: image
    splits:
      - name: train
        num_bytes: 1853104
        num_examples: 5144
      - name: test
        num_bytes: 191701
        num_examples: 541
    download_size: 1324918
    dataset_size: 2044805
configs:
  - config_name: photos
    data_files:
      - split: train
        path: photos/train-*
      - split: test
        path: photos/test-*
  - config_name: scenes
    data_files:
      - split: train
        path: scenes/train-*
      - split: test
        path: scenes/test-*
  - config_name: sprites
    data_files:
      - split: train
        path: sprites/train-*
      - split: test
        path: sprites/test-*
license:
  - cc0-1.0
  - cc-by-2.0
  - cc-by-2.5
  - cc-by-3.0
  - cc-by-4.0
size_categories:
  - 100K<n<1M
task_categories:
  - text-to-image
pretty_name: pixl-data
tags:
  - pixel-art
  - sprites

pixl-data

Training data for pixl, a small text-to-pixel-art model trained from scratch.

Config Rows What it holds
photos ~84k Photo pairs: a 256×256 photo (input), a 32×32, 24-colour version of it (target), and a caption (query)
sprites ~5.7k CC0 game sprites (image) with a short label (label)
scenes 52k 32×32 scenes built from the sprites (image), with a caption written from the placement (caption)

Load

from datasets import load_dataset

photos = load_dataset("ocdbytes/pixl-data", "photos")    # {"train": ..., "test": ...}
sprites = load_dataset("ocdbytes/pixl-data", "sprites")
scenes = load_dataset("ocdbytes/pixl-data", "scenes")

train = load_dataset("ocdbytes/pixl-data", "photos", split="train")  # one split only

Splits

Config train test Kept together in one split
photos ~82.7k ~1.6k (2% of source photos) All crops of one source photo (same sha256)
sprites ~5.1k ~540 (10% of groups) The colour variants of one tile, and the frames of one animation
scenes 50,000 2,000 Set by the generator: test scenes use test sprites, or object pairs never seen in train scenes

Near-copies never appear in both splits, so test scores are not inflated by images the model has already seen. A group is in test when the first 8 hex digits of the SHA-256 of its key, as a fraction of 16⁸, are below 0.02 (photos) or 0.1 (sprites). The split is fixed: new data never moves existing rows.

photos

Source Caption
Open Images V7 A box label or a relationship between two boxes drawn by people, e.g. "dog", "man riding horse", "wooden table". The photo is cropped around the box.
Wikimedia Commons, Openverse The search query that found the photo, e.g. "arcade cabinet".

Photos were filtered before upload. A photo was removed when:

  • CLIP matched it more closely to prompts for nudity or graphic content (gore, dead bodies, injuries) than to neutral prompts;
  • it came from a web search and CLIP found it does not show its query;
  • it is CC BY but has no author to credit, or its author field is an email address.

Every photo was changed:

  1. Cropped to a square.
  2. Resized to 256×256: input.
  3. Resized to 32×32 and reduced to 24 colours: target.
Column Meaning
id Pair id
provider openimages, wikimedia or openverse:<provider>
source_id Id of the photo at its source
query Caption
title, author From the photo's source page
license, license_url Licence of the original photo
source_page, original_url Where the original photo is
input_path, target_path File paths in the original folder layout
sha256 SHA-256 of the downloaded original
input, target The two images

sprites

Sprites from CC0 packs by Kenney (1-Bit Pack, Cursor Pixel Pack, Pico-8 City, Tiny Battle, Tiny Farm, Tiny Town), ansimuz (Sunny Land), GrafxKid (Mini Pixel Pack 3) and Buch (A Platformer in the Forest). label_source says where each label comes from: checked by eye (claude-visual), a file name (filename) or a sprite-sheet atlas (atlas).

Column Meaning
path File path in the original pack layout
pack, creator, source_url Which pack the sprite comes from
license CC0 1.0
width, height Size in pixels
label, label_source Label and where it comes from
image The sprite (PNG, with transparency)

scenes

Synthetic 32×32 scenes, each made from one sprite style: a background tile repeated in every 16 px slot (8 px for Pico-8 City) and one or two objects, each centred in its own slot. Sprites are never scaled. The caption is written from the placement, so it is always right: "a green pine tree left of a wooden barrel on grass", "a yellow bus at the top right on pavement".

Kind (kind) Split Scenes Objects from
train train 50,000 Train-split sprites
new sprites test 1,000 Test-split sprites only
new pair test 1,000 Train-split sprites in label pairs that never appear together in train scenes
Column Meaning
caption The scene's caption
kind See above
style Sprite pack (or 1-Bit Pack colour family) the scene is made from
background, background_path Background tile label and path in the sprites config; empty for a transparent scene
objects, sprites, slots Each object's label, path and row,column slot, |-separated
image The scene (PNG, transparent where there is no background)

Licences

Every row has its own licence in license (and license_url for photos):

  • Sprites: CC0 1.0.
  • Scenes: CC0 1.0, as they are made only from the sprites.
  • Photos: CC0, public domain, or CC BY 1.0–4.0. All Open Images photos are listed as CC BY 2.0.
  • Open Images annotations (the boxes and labels behind the crops and captions): CC BY 4.0, by Google.

To reuse a CC BY photo, credit it with the row's author, title, source_page and license, and say that it was changed (cropped, resized, colours reduced).

Google lists Open Images photos as CC BY 2.0 but does not guarantee each licence. Wikimedia and Openverse licences come from their providers' metadata. Check a row's source page before relying on its licence.

Known issues

  • Web captions are still somewhat noisy: in a sample of 30 web photos that passed the CLIP check, 4 did not show their query.
  • The nudity and graphic-content filter is automatic and can miss photos. Please report any you find.
  • Many photos show real people. Some show brand logos or photographers' watermarks.