This video provides an introduction to Detectron2 in python using pre-trained models for instance and panoptic segmentation.

Code generated in the video can be downloaded from here: https://github.com/bnsreenu/python_for_microscopists/blob/master/329_Detectron2_intro.ipynb

All other code:
https://github.com/bnsreenu/python_for_microscopists

Detectron2 repo: https://github.com/facebookresearch/detectron2​

What is Detectron2?
An open-source object detection and segmentation framework developed by Facebook AI Research.​

Built on top of PyTorch and provides a unified API for a variety of tasks, including object detection, instance segmentation, and panoptic segmentation.​

Designed to be flexible and easy-to-use, it puts a focus on enabling rapid research.​

It includes high-quality implementations of state-of-the-art algorithms like Mask R-CNN, RetinaNet, and DensePose.​

It includes a Model Zoo with models for object detection, instance segmentation, and more. ​

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