Introduction
Detectron2 is Facebook AI Research’s next-generation library for object detection and segmentation. It includes modern capabilities such as panoptic segmentation, DensePose, Cascade R-CNN, PointRend, ViTDet, and more, and is designed to support both research projects and production deployments.
Key Features
- Modular and extensible codebase for building research projects and custom modules.
- Rich model zoo and baselines with pre-trained weights and evaluation scripts.
- Exportable to TorchScript and other production formats for deployment and acceleration.
Use Cases
- Computer vision research: reproduce experiments and compare detection/segmentation methods.
- Production deployment: integrate high-performance detection/segmentation models into products.
- Teaching and benchmarking: tutorials, labs, and competitive evaluations.
Technical Highlights
- Support for modern detection and segmentation techniques (ViTDet, PointRend, Mask R-CNN extensions).
- Optimized training and inference pipelines with distributed training and acceleration backends.
- Comprehensive documentation (ReadTheDocs), active community, and an extensive Model Zoo.