cv2.dnn.readNetFromTorch(pretrained_model_path) throws error

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please be so kind and replace any screenshots of code & errors with a TEXT version, so we can try your code, and lookup the errors, thank you !

opencv version ? do you think, we can do anything without seing your model / training code ?

opencv-python==4.1.0.25 I used the Github open source project to train from https://github.com/davidtvs/PyTorch-ENet

ok, reproduced with a similar pretrained model

i guess, it needs some pre/postprocessing. also note, that the existing ENet from opencv's model zoo was saved from c++ torch, not from pytorch.

could you add your saving code to the question ?

https://github.com/opencv/opencv/issu...

can it be, that what you saved there is a plain pickle of the network weights, like a saved checkpoint ?

(the other one is, and not usable for opencv)

((readNetFromTorch() expects a serialized .t7 file from c++/lua Torch, not a python pickle, entirely different api))

imho, what you have to do is:

• in pytorch, extract the state_dict (and discard the optimizer, miou and such parts)
• put that into your model
• model.eval()
• then save it somehow (that's the current problem..)
  

i tried with onnx.export(), but fail with KeyError: 'max_unpool2d'

see: https://github.com/pytorch/pytorch/is...

Thank you for your answers. Instead of using onnx or using openCV can I just use the model which was saved using PyTorch and just pass an image to the model for inference/predict the semantic segmentation results.

I get the exact same error with every model from here: https://upscale.wiki/wiki/Model_Database

Which were trained with ESRGAN

And I can confirm the models work running them through PyTorch itself.

Is the ultimate answer to my issue "PyTorch models aren't supported?" I can try conversion, but being new to this whole ecosystem, the distinction between Torch/PyTorch support seems rather confusing,

@AlphaAtlas your're getting which error ? do you fail to import the result from torch.save() or fail to onnx.export() ?

please rather ask a new question specific to your problem.

Thanks for the response!

It's the same error from the first post: "error:(-213: The function/feature is not implemented) Unsupported Lua type in function 'cv::dnn::*::TorchImporter::readObject"

Repro steps are exactly the same too: try to load a .pth file with dnn.readNetFromTorch() or nn.readNet(). I haven't created the script for onnx.export() yet, but I'd rather not have to do that for every model I try. I'm away from a CUDA device atm, so I suspect the conversion will be painfully slow, and that also means inference though PyTorch isn't an option.

I'd be happy to open a second thread if necessary, but it appears I'm having the exact same issue as berak, so I figured I'd keep my issue in this thread.