Struggling in Evaluation on MegaFace!

Hi, @happynear

Thanks for sharing the detection and alignment procedure for MegaFace dataset.

I have followed your steps to preprocess both FaceScrub and MegaFace roughly. ( I don't use the cpp MTCNN but matlab MTCNN, however, the logic should be similar as yours) I can only get a result of Rank 1: 0.471718 for 1000000 distractors (with released model sphereface-20).

I use this command to get the result without modifying run_experiment.py:
python run_experiment.py -p ../templatelists/facescrub_uncropped_features_list.json ~/mat-MegaFace-feature/FlickrFinal2 ~/mat-FaceScrub-feature _cnn.bin ../../MegaFace/Mat-result -s 1000000

Is there anything wrong with my test command? I notice that there is a default model jb_identity.bin for scoring, and why should we use it for scoring since we may use a normalized l2 as the metric.

If it is correct with the test command, I may wonder, in your logic, what the face score is if using Matlab MTCNN? And I found that there are lots of images whose detection bbox is accurate, however, the alignment points are really really bad.