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hgaiser avatar hgaiser commented on September 27, 2024

I submitted a PR to keras-resnet which is not merged yet, where this repo is depending on (broadinstitute/keras-resnet#27). That would explain the error you are getting. If you want to give it a shot you can try installing this branch of keras-resnet instead.

As for the completeness, in theory everything is present to train the classification part, the bounding box regression is disabled for now (no use if classification is not working :)). I tried to train a very stripped down version of RetinaNet (computing the class predictions directly on res5, no FPN) on a very simple dataset (a single black image with a white square on it) and got varying results over different runs. Sometimes it would optimize nicely and train a correct classifier, other times it would get stuck at some loss level and it would missclassify a lot. I'm guessing there is some initialization that can be improved.

At the time of writing, the state of this repo is that training is not yet working properly. Contributions are of course always welcome :)

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mubastan avatar mubastan commented on September 27, 2024

The RetinaNet paper mentions a new initialization strategy, without which the training does not work, as they say..
There is a PyTorch implementation here https://github.com/kuangliu/pytorch-retinanet, but it is also not complete.

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hgaiser avatar hgaiser commented on September 27, 2024

I tried that initialization but it didn't seem to work for me. It's very well possible that I misinterpreted their paper in some way, but it's difficult to localize where the training is failing.

Btw, the script I'm using to test with is :
https://gist.github.com/hgaiser/c31926937f87ed3a7d5e63aaf130a2b3

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