Hi,

I am trying to extract the 4096 dense activations from the VGG16 model, my current understanding of what I would get is a 4096 characters long string but I can’t really find any info on this. What I tried is this code: https://gist.github.com/GertjanBrouwer/67fcf1747d0860fedf9be2cd563bc688

What I tried is:

- Add the VGG16 weights to the model and use Top=False
- Add the VGG16 weights to the model and use Top=False and add model.layers.pop 2x to the model.
- Add the VGG16 weights to the model and use Top=True and add model.layers.pop 2x to the model.

Which gave these results:

- https://gist.github.com/GertjanBrouwer/6b59939593673dac85e313bf9fc72b34
- https://gist.github.com/GertjanBrouwer/32a840247024d25b366a42b3a4dcaaf0
- https://gist.github.com/GertjanBrouwer/b62ce0436e2aec541169e01835d2224d

The 3rd results looked the best to me because it looks like it 1 long string, but it still has spaces in it which look a lot like the output you would get if you just used VGG16 output as is which I have here: https://gist.github.com/GertjanBrouwer/9f3cc08f09174dee3cb2968350db9d43

Can anyone help me get the correct 4096 feature?

Note: I used 1 image to get these features and it was the same image.

Thank you !