# facebookresearch/detectron2

Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

Repository: https://github.com/facebookresearch/detectron2
Canonical: https://ross.abutalabs.com/products/detectron2
Homepage: https://detectron2.readthedocs.io/en/latest/
Language: Python
License: Apache-2.0
License Family: permissive
Last push: 2026-08-19T05:38:53+00:00

## Health v2 (maintenance only)
Score: 67/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 98, release rhythm 8, longevity 100
- inputs: {"age_days": 2554, "days_push": 14, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 34688, forks 7940 (observed 2026-08-28T04:12:00.666727+00:00)

## What it is
Detectron2 is Facebook AI Research's PyTorch-based library for state-of-the-art object detection, instance/panoptic segmentation, and other visual recognition tasks. It provides a modular platform with pretrained model zoos, training/evaluation tooling, and export to TorchScript or Caffe2 for deployment.

## Use cases
- detect objects in images with pretrained models
- train a custom instance segmentation model
- run panoptic segmentation on photos
- fine-tune a Faster R-CNN on my own dataset
- export detection models to TorchScript for production
- estimate human body pose with Densepose
- benchmark object detection baselines

## When to choose
- you need state-of-the-art detection or segmentation models in PyTorch
- you want a modular research platform to build vision projects on
- you need pretrained baselines and a model zoo
- you need fast training and production export paths

## When to avoid
- you need lightweight real-time detection on edge devices
- you work outside PyTorch (e.g., TensorFlow-only)
- you only need simple image classification
- you want a no-code GUI tool rather than a Python library

## Facets
- artifact type: library
- maturity: stable
- function: machine-learning, computer-vision, image-processing, deep-learning
- domain: computer-vision, machine-learning, deep-learning, image-processing
- platform: python
- tags: object-detection, instance-segmentation, panoptic-segmentation, pytorch, model-zoo, facebook-ai-research, torchscript-export, pose-estimation, linux, macos, gpu

## Member repositories
- facebookresearch/detectron2 (main) score 67

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:12:00.666727+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 2026-08-29T16:27:28.051718+00:00, confidence not recorded.
  - readme: https://github.com/facebookresearch/detectron2 (fetched 2026-08-28T04:12:00.666727+00:00, sha 54df9b531f35)
  - homepage: https://detectron2.readthedocs.io/en/latest/ (fetched 2026-08-29T07:48:10.153138+00:00, sha de25515df2aa)
- Data as of 2026-08-30T08:39:29.467469+00:00.