# cvdfoundation/open-images-dataset

Open Images is a dataset of ~9 million images that have been annotated with image-level labels and bounding boxes spanning thousands of classes.

Repository: https://github.com/cvdfoundation/open-images-dataset
Canonical: https://ross.abutalabs.com/products/open-images-dataset
Homepage: https://github.com/openimages/dataset
License Family: other
Last push: 2020-05-04T12:43:19+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3215, "days_push": 2312, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1128, forks 170 (observed 2026-08-28T04:03:41.613407+00:00)

## What it is
Open Images is a large-scale dataset of ~9 million images annotated with image-level labels and bounding boxes spanning over 6000 categories, hosted by CVDF on AWS S3. The repository provides download instructions, mirrors, and tooling for retrieving the dataset's train, validation, and test splits.

## Use cases
- train an object detection model on a large labeled image dataset
- download millions of annotated images with bounding boxes
- benchmark computer vision models across thousands of classes
- get training data for image classification
- find a large-scale dataset for instance segmentation research

## When to choose
- you need a massive, freely available image dataset with bounding box annotations
- you want thousands of object categories for detection or classification
- you need standard train/validation/test splits for benchmarking

## When to avoid
- you need a small curated dataset for a quick prototype
- you cannot store hundreds of gigabytes of images
- you need pixel-perfect segmentation masks for all images

## Facets
- artifact type: dataset
- maturity: maintenance
- function: machine-learning, computer-vision, image-processing
- domain: computer-vision, machine-learning, image-processing, deep-learning
- platform: cloud, cross-platform
- tags: image-dataset, object-detection, bounding-boxes, image-classification, computer-vision-dataset, open-images

## Member repositories
- cvdfoundation/open-images-dataset (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:41.613407+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:38:32.700581+00:00, confidence not recorded.
  - readme: https://github.com/cvdfoundation/open-images-dataset (fetched 2026-08-28T04:03:41.613407+00:00, sha 33d95b1769c0)
  - homepage: https://github.com/openimages/dataset (fetched 2026-08-29T12:43:22.092064+00:00, sha 08cc2c9abbaa)
- Data as of 2026-08-30T08:39:29.467469+00:00.