There is a pytorch port from Ultralytics (https://github.com/ultralytics/yolov3 https://github.com/ultralytics/yolov3). Nobody seems to have figured out how to

There is a pytorch port from Ultralytics (https://github.com/ultralytics/yolov3 https://github.com/ultralytics/yolov3). Nobody seems to have figured out how to achieve the training performance of darknet though, which is entirely uncommented C. The source is all there, but the loss function changed between v2 and v3, and its not documented in the paper. I think it's been fixed in that pytorch port now though. The only frustrating thing is that every commit in the repo is called update... Alternatively... you can train in darknet and then run inference in another framework of choice. Also shameless plug: I wrote an annotation tool which is designed to output darknet formatted labels: https://github.com/jveitchmichaelis/deeplabel https://github.com/jveitchmichaelis/deeplabel