Extracting features of varying dimensionality from the Inception-V3 model

[sivaramakrishnan-rajaraman]

Thanks for this excellent repository. Comparing with https://github.com/mseitzer/pytorch-fid, I would like to extract features from different pooling layers like the first max pooling features (64), second max pooling features (192), pre-aux classifier features (768), and final average pooling features (2048) and compare FID scores. I believe the default option in your case is extracting the features from the final average pooling layer. Correct me if I am wrong.

from cleanfid import fid
fdir1 = '/content/gdrive/MyDrive/syn'
fdir2 = '/content/gdrive/MyDrive/orig'
score = fid.compute_fid(fdir1, fdir2)
print(score)

Is there an option to modify the function call to extract features from different layers and compare the scores? Thanks in advance.

[GaParmar]

Thank you for interest in this work!
The package does not directly support extracting features from different layers of the inception model.
However, this functionality can be achieved by the custom_feat_extractor option, that allows passing in a custom feature extractor function.

-Gaurav