extract_features.py produces feature that is all the same for all the videos

[wenjie710]

I am using my own dataset and I have made the database as you said. However when I tried to extract features using extract_features.py, I got confused results. I printed the features and found that the softmax layer gives the same number, like (Pdb) activations array([[0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111], [0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111], [0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111], [0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111, 0.01111111]], dtype=float32) since the number of labels I use is 90, the feature I get seems like an initialization. I am so confused. Could you give me some advice?

[dutran]

@wenjie710 can you try again?