Pictograph Research
Dataset

COCO-164k

Pictograph Research · Updated 2mo ago · CC-BY-4.0

Dataset Card

COCO-164k

A public computer-vision dataset of 163,957 images with 885,976 annotations across 80 classes, annotated as polygon and bounding box.

Pictograph Research · CC-BY-4.0 · Public · Updated 2026-08-08

Overview

This dataset holds 163,957 images annotated as polygon and bounding box across 80 classes. The most common auto-detected tags are playing, eating, person, eye-level view, top-down view, zoo. It is ready to fork, export in a dozen formats, or train a model from.

At a glance

Metric Value
Images163,957
Annotations885,976
Classes80
Annotation typespolygon, bounding box
Folders3
StorageStandard
VisibilityPublic

What's in these images

Tags auto-detected across the dataset, most common first.

Tag Category Images
playingAttributes22,448
eatingAttributes17,689
personObjects16,034
eye-level viewAttributes12,679
top-down viewAttributes10,642
zooScenes8,089
walkingAttributes7,380
drivingAttributes7,018
childObjects6,740
signObjects6,474
cookingAttributes6,465
bathroomScenes6,319
skiObjects6,274
skiingAttributes6,248
jumpingAttributes6,024

Use this dataset

from pictograph import Client, Dataset

client = Client()  # reads PICTOGRAPH_API_KEY
dataset: Dataset = client.datasets.get("COCO-164k")
print(dataset.image_count, dataset.annotation_count)
  • Fork it into your own workspace with one click from its page.
  • Pull it with the Pictograph SDK (shown above) or the CLI.
  • Export to COCO, YOLO, Darwin V7, Pascal VOC, and more.
  • Train a model directly from an export.

License

Released under CC-BY-4.0.

163,957 images
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Creative Commons Attribution 4.0 Data / content

Allows any use, including commercial, as long as appropriate credit is given. A common choice for datasets.

Read the full Creative Commons Attribution 4.0 →

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