#2121st of 22 in ML frameworks and libraries
detectron2
PyTorch library for object detection and segmentation research
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- Stars
- 34.9k
- License
- Apache-2.0
- Last commit
- Sep 2026
- Last release
- Nov 2021
- Language
- Python
34,067 on 25 Mar 202634,898 on 14 Oct 2026
From GitHub's daily star counts.
Checked on GitHub.
Overview
Detectron2 is Facebook AI Research's PyTorch library for object detection and segmentation, successor to Detectron and maskrcnn-benchmark. It covers panoptic segmentation, DensePose, Cascade R-CNN, rotated boxes, PointRend, DeepLab, ViTDet and MViTv2, and ships a Model Zoo of baselines. Models can be exported to TorchScript or Caffe2.
Who it is for: Computer vision researchers training detection and segmentation models
Strengths
- Wide algorithm coverage: panoptic segmentation, DensePose, PointRend, ViTDet, MViTv2, rotated boxes
- Model Zoo with downloadable baselines and trained weights
- Export to TorchScript or Caffe2 for deployment
- Modular design for building research projects on top; Apache-2.0
Weaknesses
- Last tagged release is 2021-11-15, though commits continue
- Not a model server; no inference API or UI included
- Install steps live in external docs, not the README
- Hardware requirements are not stated in the README
What it needs
- Docker + Compose
- Needs PyTorch
- Models: Mask R-CNN, Cascade R-CNN, Panoptic segmentation, DensePose, PointRend
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