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Commit to enable true fully convolutional application of network #684
The original implementation of VGG models has fully connected layers implemented as convolution.
It gives predictable results when the network is used for classification.
It is also possible to apply the network in a fully convolutional manner like it is described in the paper
You can see that in the second picture the image was downsampled by 32 while on the first one
I suggest to add one more argument to the definition of models to be able to switch between those two
referenced this pull request
Jan 2, 2017
Hi! I`m a beginner of Python and tensorflow.When I run you programs with these change, however, I met a problem like that:
Caused by op 'SoftmaxCrossEntropyWithLogits', defined at:
InvalidArgumentError (see above for traceback): logits and labels must be same size: logits_size=[168960,2] labels_size=[183000,2]
I am afraid that I need your help.Thank you!