Ultralytics YOLOv5 supports object detection, instance segmentation, classification, training, and export in PyTorch.
Open source
24 alternativesdetectron2
Detectron2 provides computer vision tools for object detection, segmentation, and other visual recognition tasks.
About detectron2
Detectron2 is a library from Facebook AI Research for object detection, segmentation, and other visual recognition tasks. It is the successor to Detectron and maskrcnn-benchmark. The homepage says it supports both computer vision research projects and production applications at Facebook.
The library includes several newer detection and segmentation methods. Trained models can be exported to TorchScript or Caffe2 formats for deployment. The repository provides a Model Zoo with baseline results and trained models for download. The homepage does not state hardware, platform, or dependency requirements. Installation and usage details are in separate documentation.
Key features
- Panoptic segmentation, DensePose, Cascade R-CNN, and rotated bounding boxes
- PointRend, DeepLab, ViTDet, and MViTv2 methods
- Model export to TorchScript or Caffe2 formats for deployment
- Library for building research projects on top of its components
- Model Zoo with baseline results and trained models for download
- Colab notebook for basic usage
Best for: Computer vision researchers and engineers who want a Python library of detection and segmentation methods to build on or deploy.
Good for
- Released under the Apache 2.0 license.
- Provides baseline results and trained models in the Model Zoo.
- The homepage states that it trains much faster.
detectron2 at a glance
- Category
- AI & Machine Learning › AI Data & Analytics
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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detectron2 FAQ
What license is Detectron2 released under?
Detectron2 is released under the Apache 2.0 license.
Can trained models be used outside of Python?
The homepage states that models can be exported to TorchScript format or Caffe2 format for deployment.
Where can I find installation instructions?
The homepage links to installation instructions, and a getting started guide and a Colab notebook cover basic usage.
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