Keras: Visualizing image summaries from intermediate layers using Tensorboard

Created on 24 May 2016  路  1Comment  路  Source: keras-team/keras

Is there a way to use keras to visualize image summaries using tensorboard? The tensorboard callback currently doesn't seem to support them. If there is no existing functionality, can someone give an example of implementing a separate callback for this (or any other suitable way to achieve this)?

stale

Most helpful comment

Recently ran across this issue.

The TensorBoard callback creates a self.merged layer with nodes comprised of the histograms and images, but it only attempts to write this summary info if model.validation_data is defined. If you are using fit_generator with a generator for the validation data, validation_data is set to None, and therefore the images and histograms are never written.

In addition, the code that generates the merged layer looks like it needs to be updated... I'm getting all kinds of invalid size errors related to the image nodes.

At a minimum this should be documented, and certainly the class could use some improvements.

>All comments

Recently ran across this issue.

The TensorBoard callback creates a self.merged layer with nodes comprised of the histograms and images, but it only attempts to write this summary info if model.validation_data is defined. If you are using fit_generator with a generator for the validation data, validation_data is set to None, and therefore the images and histograms are never written.

In addition, the code that generates the merged layer looks like it needs to be updated... I'm getting all kinds of invalid size errors related to the image nodes.

At a minimum this should be documented, and certainly the class could use some improvements.

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