I have successfully trained and validated Theano-AlexNet, where the CNN
achieves 56.6% validation accuracy for the top-1 class labels and 79.7% for
the top-5, which is in very close agreement with results published in the
arXiv in 2015.
At this stage I am exploring the python code in an effort
to extract the top-5 class label information for individual test images.
So, far I have been able to run the validate_performance.py program in the
AlexNet folder, i.e.,
https://github.com/uoguelph-mlrg/theano_alexnet/blob/master/validate_performance.py,
and print out the following items:
1) filenames for each of the 195 validation hkl image mini-batch files.
2) their 256 corresponding validation class labels (i.e., val_labels).
3) the single top_5 error value (i.e., error_top_5) for each of the 195
mini-batches.
I wonder if you could help me find some additional
information from the CNN:
1) the top-5 error rate for each of the 256 images in each of the 195
mini-batches.
2) the for each of the 256 images in each of the 195 mini-batches.
Any comments that you may offer would be greatly
appreciated.
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