Keras Network: Placeholder for 'BilinearUpSampling2D'

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jose daniel hoyos giraldo
jose daniel hoyos giraldo 2022 年 9 月 3 日
Hello, I'm trying to use a keras network for depth estimation from a monocular view.
I'm following this:
The problem is that when I try:
placeholderLayers = findPlaceholderLayers(lgraph)
I got layers of this type:
2 'up1_upsampling2d' PLACEHOLDER LAYER Placeholder for 'BilinearUpSampling2D' Keras layer
which I dont know how to deal with.

回答 (1 件)

Sivylla Paraskevopoulou
Sivylla Paraskevopoulou 2022 年 9 月 6 日
編集済み: Sivylla Paraskevopoulou 2022 年 9 月 6 日
You have a few options:
  1. Instead of the importKerasNetwork function, use the importTensorFlowNetwork function. The importTensorFlowNetwork function is the newest and recommended function. The importTensorFlowNetwork function generates a custom layer when you import a TensorFlow layer that the software cannot convert into an equivalent built-in MATLAB layer. Then, you will have a network that is ready to use. Note, that you must convert your TensorFlow model from .h5 format to SavedModel format to use the importTensorFlowNetwork function. For more information on the differences between importKerasNetwork and importTensorFlowNetwork functions, see Importing Models from TensorFlow, PyTorch, and ONNX.
  2. You can replace the placeholder layer with a resize2dLayer or resize3dLayer.
  3. You can replace the placeholder layer with your own custom layer.
  2 件のコメント
Sivylla Paraskevopoulou
Sivylla Paraskevopoulou 2022 年 9 月 13 日
The assembleNetwork function expects the assembled layers to include input and output layers. You can add layers by using the addLayers function.
Also, it looks like you are replacing the placeholder upsampling layers with gaussian noise layers. I don't think these two types of layers have the same functionality.
I still think it would be easier to convert your model from .h5 to SavedModel using Python and then import it by using the importTensorFlowNetwork function.





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