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YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
* Apart from VGG-SSD (Source code https://pytorch.org/vision/main/_modules/torchvision/models/detection/ssd.html), there are other models available there. And also the one I tried my self (yolov7 https://github.com/WongKinYiu/yolov)
* Most of the time I find Roboflow extremely handy, I used it to merge datasets, augmentate, read tutorials and that kind of thing. Basically you just create your dataset with roboflow and focus on other aspects.
* Why doesnt Pytorch have YOLO! https://github.com/pytorch/vision/issues/6341
* Nice implemention of Yolo that is BSD license (not GPL) https://github.com/Megvii-BaseDetection/YOLOX
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