Having worked with YOLO, I really recommend this intro: https://blog.paperspace.com/how-to-implement-a-yolo-object-detector-in-pytorch/ https://blog.paperspace.

Having worked with YOLO, I really recommend this intro: https://blog.paperspace.com/how-to-implement-a-yolo-object-detector-in-pytorch/ https://blog.paperspace.com/how-to-implement-a-yolo-object-d.... And in general, YOLO is performant and at the same time, it has a simpler architecture than the Fast(er) R-CNN family. And in general, due to its head, it is WAY more readable in PyTorch than in TensorFlow; to the point, I use it as an example in Keras vs PyTorch example https://deepsense.ai/keras-or-pytorch/ https://deepsense.ai/keras-or-pytorch/ (was here at some point).