Comments (5)
We haven't used our models for feature extraction. Ideally, it should be possible to do. You can write a script similar to validate.lua. You can extract the features from fully connected layers after forward
ing the data through the model.
You can access the layer outputs in the normal way as any other torch nngraph
model.
model = torch.load('<model.net>')
model:forward(data)
features = model.modules[FC_LAYER_INDEX].output:clone()
from first-impressions.
Thank you very much. I will surely try along these lines.
from first-impressions.
Hi Arul,
Your answer is well appreciated.
But I feel difficult to run these codes for my data. I am not sure where to start with.
How to place my mp4 data in proper directories, as the data given in the link is not downloadable?
It would be very helpful if there are commands for feature extraction alone (for our data).
I request you to please share your thoughts.
from first-impressions.
Please go through the files data/preprocessing_videofeats.py
, data/preprocessing_audiofeats.py
to know the commands for feature extraction.
The extracted features shall be placed in the below folders (automatically done by these scripts).
"data/trainaudiofeat" - training audio features
"data/trainframes" - training video features
"data/validationaudiofeat" - validation audio features
"data/validationframes" - validation video features
Also, the original data from the competition is downloadable from organizer's website.
from first-impressions.
Closing the issue assuming that the issue was resolved, please reopen/create a new issue if there is any help/clarification needed. Thanks!
from first-impressions.
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