pictograph/ade-20k

View on Pictograph · Pictograph Research · Custom (ADE20K dual license)

About

ADE-20K is a computer-vision dataset curated and annotated on Pictograph. The most common detected objects are building, sidewalk, bed, house, road, tower. On Pictograph you can browse every annotated image, fork it into your own workspace in one click, export it in a dozen formats, or train a model on it directly.

At a glance

Metric	Value
Images	22,207
Annotations	396,285
Classes	150
Annotation types	polygon
Splits	train

Quick start

Load it in one line with the datasets library, then read each record's boxes and class names:

from datasets import load_dataset
from PIL import ImageDraw

ds = load_dataset("pictograph/ade-20k", split="train")
example = ds[0]
image = example["image"]            # a PIL image
objects = example["objects"]        # {bbox, categories, category_names}

# draw every bounding box with its class name
draw = ImageDraw.Draw(image)
for (x, y, w, h), name in zip(objects["bbox"], objects["category_names"]):
    draw.rectangle([x, y, x + w, y + h], outline="red", width=3)
    draw.text((x, y - 12), name, fill="red")

# polygon masks live under example["segmentation"]:
#   [{"label": name, "category": idx, "points": [[x, y], ...]}, ...]
image.show()

Prefer a full annotation editor, one-click fork, multi-format export, and one-click training? Open this dataset on Pictograph.

Dataset structure

This dataset uses the Hugging Face imagefolder layout: each split directory holds the images plus a metadata.jsonl that links every image to its annotations by file_name.

Field	Description
file_name	Path to the image within the split directory.
objects.bbox	Bounding boxes as [x, y, width, height] (pixels).
objects.categories	Integer class index per box (matches the class list below).
objects.category_names	Human class name per box.
segmentation	List of {label, category, points}; points is a polygon ring [[x, y], ...].

Data instance

One record (bounding boxes are [x, y, width, height] in pixels; the class index maps into the class list below):

{
  "image": <PIL.Image (RGB)>,
  "objects": {
    "bbox": [[172.0, 192.0, 249.4, 152.7]],
    "categories": [0],
    "category_names": ["wall"]
  },
  "segmentation": [
    {"label": "wall", "category": 0, "points": [[176.9, 207.2], [259.0, 274.1], ...]}
  ]
}

Classes

Class index matches objects.categories in metadata.jsonl.

All 150 classes, in index order: wall, building, sky, floor, tree, ceiling, road, bed, windowpane, grass, cabinet, sidewalk, person, earth, door, table, mountain, plant, curtain, chair, car, water, painting, sofa, shelf, house, sea, mirror, rug, field, armchair, seat, fence, desk, rock, wardrobe, lamp, bathtub, railing, cushion, base, box, column, signboard, chest_of_drawers, counter, sand, sink, skyscraper, fireplace, refrigerator, grandstand, path, stairs, runway, case, pool_table, pillow, screen_door, stairway, river, bridge, bookcase, blind, coffee_table, toilet, flower, book, hill, bench, countertop, stove, palm, kitchen_island, computer, swivel_chair, boat, bar, arcade_machine, hovel, bus, towel, light, truck, tower, chandelier, awning, streetlight, booth, television_receiver, airplane, dirt_track, apparel, pole, land, bannister, escalator, ottoman, bottle, buffet, poster, stage, van, ship, fountain, conveyer_belt, canopy, washer, plaything, swimming_pool, stool, barrel, basket, waterfall, tent, bag, minibike, cradle, oven, ball, food, step, tank, trade_name, microwave, pot, animal, bicycle, lake, dishwasher, screen, blanket, sculpture, hood, sconce, vase, traffic_light, tray, ashcan, fan, pier, crt_screen, plate, monitor, bulletin_board, shower, radiator, glass, clock, flag.

License

ADE20K uses a dual license. Images: non-commercial research and educational use only (bespoke MIT CSAIL agreement; access via request form; MIT does not hold image copyright; commercial use requires permission from MIT CSAIL). Annotations, software, and website: BSD-3-Clause, Copyright 2019 MIT, CSAIL.

Source and attribution

This dataset is derived from ADE20K, created by Zhou et al., MIT CSAIL. We are grateful to the original authors. If you use this data, please cite the original source above.

Citation

@inproceedings{zhou2017scene,
  title={Scene Parsing through ADE20K Dataset},
  author={Zhou, Bolei and Zhao, Hang and Puig, Xavier and Fidler, Sanja and Barriuso, Adela and Torralba, Antonio},
  booktitle={CVPR},
  year={2017}
}

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