Detectron2
Detection and segmentation, boxed up as the field's default toolkit
Latest: Detectron2 (actively maintained on GitHub)
FAIR's modular PyTorch platform for object detection, instance segmentation, keypoints, and panoptic segmentation — the successor to the original Caffe2-based Detectron (2018). For years the default research and industry toolkit for detection, it implements Mask R-CNN, RetinaNet, DensePose, and dozens of successors.
Why it matters
Detectron2 boxed up detection, instance and panoptic segmentation and keypoints as the field's default PyTorch toolkit: Mask R-CNN, RetinaNet, DensePose and dozens of successors in one modular codebase with about 35,000 GitHub stars. It underpinned countless CVPR papers, spawned Detectron2Go for mobile, and remains actively maintained.
Facts
- One of GitHub's most-starred computer-vision libraries with tens of thousands of stars; spawned major derivatives like Detectron2Go for mobile deployment and underpinned countless CVPR papers.
Try it yourself
Official Colab tutorial ↗ Documentation ↗ Code on GitHub ↗