julienr / ipynb_playground Goto Github PK
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Various ipython notebooks
Thanks sir for this awesome work!. Actually I've been looking for something like this for quite long time, so thank you . I have a question if you allow me, If I have a test image and I want to get the model output after activation of the dense layer, so in this case what will be the input of this layer ( K.function(inputs, [convout1.output])) ? the original test image ? or the image after computing the output of all the previous layers? shall I compute them by myself or it will be computed implicitly if the test image fed directly into the dense layer?
Hello @julienr , thank you so much for your contribution on visualisation of the neural network.
I've been following this link which uses the weights from mnist_cnn_weights_v1.hdf, however, I was unable to find the file in your repository. Could you point me to the link or where I can get it?
Thank you :)
This example won't work anymore as keras interface has changed.
Have changes and am willing to send if you'd like.
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