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batchsize problem when training with FCN #2

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yoyoleeisstrong opened this issue Jun 14, 2018 · 5 comments
Open

batchsize problem when training with FCN #2

yoyoleeisstrong opened this issue Jun 14, 2018 · 5 comments

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@yoyoleeisstrong
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If I combine FCN with your crfasrnn, there is a problem.
In crf_rnn_layer.py, 44 column, all_ones = np.ones(unaries_shape, dtype=np.float32), because there is no definite batchzie in model defining process, the batchsize of unaries is None. The error is TypeError: index returned non-int (type NoneType.

Can you give some training examples using your crfasrnn? Thanks!

@MiguelMonteiro
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For now this is intended behaviour, I don't know how to deal with undefined shapes in c++.
You can try to force define the shape of the inputs before the crf as rnn layer for it work.
I don't have any training examples, it should be somewhat straight-forward to place it on top of a fully-connected neural network, just note the sensitivity to the theta parameters.

@yoyoleeisstrong
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yoyoleeisstrong commented Jun 15, 2018 via email

@MiguelMonteiro
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It will only work for segmentation.
I think you should read this paper before deciding if this is appropriate for your use-case.

@yoyoleeisstrong
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yoyoleeisstrong commented Jun 15, 2018 via email

@watchmexiang
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Hello, may I ask if you have implemented CRFasRNNLayer in FCN, how is it implemented? Thank you. @yoyoleeisstrong @MiguelMonteiro

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3 participants