tportenier
tportenier
I also struggle reproducing the numbers in Table 2 from the paper. If I run your script on the data in user_study/fake_high_variance and user_study/fake_mid_variance I get 1.6010857 and 1.6310933 respectively...
The pictures are already in jpg, this is not the reason.
@joelthchao Thanks for the hint. Inspired by your code, I modified the kaffe.tensorflow.Network.load to take a list of layer names that should be ignored when restoring, either because they are...
Here you go! This is what I used (long time ago): `def load(self, data_path, session, ignore_missing=False, scratch_layers=[]): '''Load network weights. data_path: The path to the numpy-serialized network weights session: The...