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Object Detection and Image Segmentation with Detectron2
Export [detectron2](https://github.com/facebookresearch/detectron2) model to [onnx](https://github.com/onnx/onnx) and run inference using [caffe2 onnx backend](https://pytorch.org/tutorials/advanced/super_resolution_with_caffe2.html). This let's you run inference on a raspberry pi with acceptable inference times.
Detectron is Facebook AI Research’s (FAIR) software system that implements state-of-the-art object detection algorithms, including Mask R-CNN. It is written in Python and powered by the Caffe2 deep learning framework. Detectron model is meant to advance object detection by offering speedy training and addressing the issues companies face when making the step from research to production.
poker cards detector using Detectron2
An AI project for identifying zebrafish organs and phenotypes in micrographs, based on Detectron2, 0.4.1.
Detectron2 is a modular, flexible, and scalable object detection framework that is built on top of PyTorch. It provides a number of state-of-the-art object detection algorithms, including Mask R-CNN, Faster R-CNN, and YOLOv4.