Detectron2 is a computer vision library from Facebook AI Research. It provides a state-of-the-art object detection and segmentation framework. Detectron2 is written in Python and is easy to use.
Detectron2 is based on the popular PyTorch machine learning library. This makes it easy to integrate Detectron2 with other PyTorch-based tools and libraries. Detectron2 also supports distributed training, which allows you to train large models on multiple GPUs or machines.
Detectron2 can be used for a variety of computer vision tasks, including:
Object detection: Identifying and locating objects in images and videos.
Instance segmentation: Identifying and segmenting individual objects in images and videos.
Keypoint detection: Identifying and localizing key points on objects, such as the joints of a person or the corners of a building.
Panoptic segmentation: Identifying and segmenting all objects in an image, including stuff (e.g., sky) and things (e.g., people, cars).
Detectron2 is a powerful and versatile computer vision library that can be used for a wide range of tasks. It is easy to use and supports distributed training, making it a good choice for both beginners and experienced users.
Useful Links to start:
Detectron2 website: https://ai.meta.com/tools/detectron2/
Detectron2 documentation: https://detectron2.readthedocs.io/en/latest/
Detectron2 tutorials: https://detectron2.readthedocs.io/en/latest/tutorials/
Conclusion
Detectron2 is a powerful and versatile computer vision library that can be used for a wide range of tasks. It is easy to use and supports distributed training, making it a good choice for both beginners and experienced users.
