I set num_worker = 1 , accurate_landmark = False and test on lfw (using your pre-trained model), then there are four photos the model didn't detect out the faces. There are:
Arsinee_Khanjian_0001.jpg
John_Wayne_0001.jpg
Marilyn_Monroe_0002.jpg
Muhammad_Saeed_al-Sahhaf_0003.jpg
so my question is if there is a way to prove the detect performance a little bit to avoid these four failures? or a practical way to fix(or make up) this problem when it happens during the task of detecting and aligning?
I set num_worker = 1 , accurate_landmark = False and test on lfw (using your pre-trained model), then there are four photos the model didn't detect out the faces. There are:
so my question is if there is a way to prove the detect performance a little bit to avoid these four failures? or a practical way to fix(or make up) this problem when it happens during the task of detecting and aligning?