I have set up Tensorboard with Keras as a callback, like so:
callback_tb = keras.callbacks.TensorBoard(log_dir=tb_dir, histogram_freq=2,write_graph=True,write_images=True)
callbacks_list = [callback_save,callack_view, callback_tb]
model.fit(x_train,y_train,
batch_size=batch_size,
epochs=epochs,
callbacks=callbacks_list,
verbose=1,
validation_data=(x_test,y_test),
shuffle='batch')
This works fine and I can see loss and accuracy graphs on Tensorboard. I am generating and saving model predictions in another file, but I want to know if it is possible to view these images on Tensorboard with Keras?
I have found the tf.summary.image
function on https://github.com/tensorflow/tensorboard
But I don't understand how this relates to Keras.
Any help would be appreciated.