- https://www.mathworks.com/help/releases/R2022a/vision/ug/getting-started-with-r-cnn-fast-r-cnn-and-faster-r-cnn.html
- https://www.mathworks.com/help/releases/R2022a/vision/ug/object-detection-using-deep-learning.html
- https://www.mathworks.com/help/releases/R2022a/vision/ug/object-detection-using-faster-r-cnn-deep-learning.html
Export Mask R-CNN to ONNX format
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Karl Mueller
el 9 de Mayo de 2023
Comentada: Karl Mueller
el 18 de Mayo de 2023
I am considering using MATLAB to train a Mask R-CNN network but the trained network must be able to be exported to ONNX format afterwards so I can import and use it in my application.
I took a look at the exportONNXFormat function and exporting a roiAlignLayer doesn't seem to be listed. Can anyone confirm whether this kind of layer is compatible with the ONNX export?
Otherwise I can probably use a Fast or Faster R-CNN for my application, and the roiMaxPooling2D layer is explicitly mentioned in the function documentation as being supported.
Thank you
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Sourabh
el 16 de Mayo de 2023
Hey Karl,
As you have mentioned, the roiAlignLayer is not supported by the exportONNXNetwork function currently. I have attached a few relevant links which might help get you started with your approach using a Fast or Faster R-CNN network:
All the best!
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