Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/facebookresearch/detectron2
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
https://github.com/facebookresearch/detectron2
Last synced: 11 days ago
JSON representation
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
- Host: GitHub
- URL: https://github.com/facebookresearch/detectron2
- Owner: facebookresearch
- License: apache-2.0
- Created: 2019-09-05T21:30:20.000Z (about 5 years ago)
- Default Branch: main
- Last Pushed: 2024-10-11T00:51:10.000Z (29 days ago)
- Last Synced: 2024-10-14T20:23:40.724Z (25 days ago)
- Language: Python
- Homepage: https://detectron2.readthedocs.io/en/latest/
- Size: 6.2 MB
- Stars: 30,225
- Watchers: 386
- Forks: 7,436
- Open Issues: 532
-
Metadata Files:
- Readme: README.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE
- Code of conduct: .github/CODE_OF_CONDUCT.md
Awesome Lists containing this project
- awesome-python-machine-learning-resources - GitHub - 7% open · ⏱️ 24.08.2022): (图像数据与CV)
- Awesome-pytorch-list-CNVersion - detectron2
- awesome-starts - facebookresearch/detectron2 - Detectron2 is FAIR's next-generation platform for object detection, segmentation and other visual recognition tasks. (Python)
- AiTreasureBox - facebookresearch/detectron2 - 11-02_30407_1](https://img.shields.io/github/stars/facebookresearch/detectron2.svg)|Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.| (Repos)
- awesome-cv - detectron2 - generation platform for object detection, segmentation and other visual recognition tasks | (Repos / Tags: Object Classification `[ObjCls]`, Object Detection `[ObjDet]`, Object Segmentation `[ObjSeg]`, General Library `[GenLib]`, Text Reading / Object Character Recognition `[OCR]`, Action Recognition `[ActRec]`, Object Tracking `[ObjTrk]`, Data Augmentation `[DatAug]`, Simultaneous Localization and Mapping `[SLAM]`, Outlier/Anomaly/Novelty Detection `[NvlDet]`, Content-based Image Retrieval `[CBIR]`, Image Enhancement `[ImgEnh]`, Aesthetic Assessment `[AesAss]`, Explainable Artificial Intelligence `[XAI]`, Text-to-Image Generation `[TexImg]`, Pose Estimation `[PosEst]`, Video Matting `[VidMat]`, Eye Tracking `[EyeTrk]`)
- awesome-robotic-tooling - detectron2 - is a next-generation research platform for object detection and segmentation. (Sensor Processing / Image Processing)
- awesome-robotic-tooling - detectron2 - A next-generation research platform for object detection and segmentation. (Sensor Processing / Image Processing)
- awesome-list - Detectron2 - A platform for object detection, segmentation and other visual recognition tasks, based on PyTorch. (Computer Vision / Classification & Detection & Tracking)
- Awesome-pytorch-list - detectron2 - generation research platform for object detection and segmentation. (Pytorch & related libraries / CV:)
- awesome-google-colab - Detectron2 - Detectron2 is FAIR's next-generation research platform for object detection and segmentation. (Technologies)
- awesome-aigc - Detectron2
- StarryDivineSky - facebookresearch/detectron2
- awesome-production-machine-learning - Detectron2 - Detectron2 is Facebook AI Research's next generation library that provides state-of-the-art detection and segmentation algorithms. (Industry Strength CV)
README
Detectron2 is Facebook AI Research's next generation library
that provides state-of-the-art detection and segmentation algorithms.
It is the successor of
[Detectron](https://github.com/facebookresearch/Detectron/)
and [maskrcnn-benchmark](https://github.com/facebookresearch/maskrcnn-benchmark/).
It supports a number of computer vision research projects and production applications in Facebook.
## Learn More about Detectron2
Explain Like I’m 5: Detectron2 | Using Machine Learning with Detectron2
:-------------------------:|:-------------------------:
[![Explain Like I’m 5: Detectron2](https://img.youtube.com/vi/1oq1Ye7dFqc/0.jpg)](https://www.youtube.com/watch?v=1oq1Ye7dFqc) | [![Using Machine Learning with Detectron2](https://img.youtube.com/vi/eUSgtfK4ivk/0.jpg)](https://www.youtube.com/watch?v=eUSgtfK4ivk)## What's New
* Includes new capabilities such as panoptic segmentation, Densepose, Cascade R-CNN, rotated bounding boxes, PointRend,
DeepLab, ViTDet, MViTv2 etc.
* Used as a library to support building [research projects](projects/) on top of it.
* Models can be exported to TorchScript format or Caffe2 format for deployment.
* It [trains much faster](https://detectron2.readthedocs.io/notes/benchmarks.html).See our [blog post](https://ai.facebook.com/blog/-detectron2-a-pytorch-based-modular-object-detection-library-/)
to see more demos and learn about detectron2.## Installation
See [installation instructions](https://detectron2.readthedocs.io/tutorials/install.html).
## Getting Started
See [Getting Started with Detectron2](https://detectron2.readthedocs.io/tutorials/getting_started.html),
and the [Colab Notebook](https://colab.research.google.com/drive/16jcaJoc6bCFAQ96jDe2HwtXj7BMD_-m5)
to learn about basic usage.Learn more at our [documentation](https://detectron2.readthedocs.org).
And see [projects/](projects/) for some projects that are built on top of detectron2.## Model Zoo and Baselines
We provide a large set of baseline results and trained models available for download in the [Detectron2 Model Zoo](MODEL_ZOO.md).
## License
Detectron2 is released under the [Apache 2.0 license](LICENSE).
## Citing Detectron2
If you use Detectron2 in your research or wish to refer to the baseline results published in the [Model Zoo](MODEL_ZOO.md), please use the following BibTeX entry.
```BibTeX
@misc{wu2019detectron2,
author = {Yuxin Wu and Alexander Kirillov and Francisco Massa and
Wan-Yen Lo and Ross Girshick},
title = {Detectron2},
howpublished = {\url{https://github.com/facebookresearch/detectron2}},
year = {2019}
}
```