Play with different face recognition techniques and observe the result.
# Download training dataset
$ mkdir -p download/train
$ wget -O download/train/CASIA-WebFace.tar.gz https://www.dropbox.com/s/6x03igvbvfwx24w/CASIA-WebFace.tar.gz?dl=1
# Download testing dataset
$ mkdir -p download/test
$ wget -O download/test/CFP_FP.tar.gz https://www.dropbox.com/s/e3u7804yk54yqoj/CFP_FP.tar.gz?dl=1
$ wget -O download/test/LFW.tar.gz https://www.dropbox.com/s/d1y5o66dn8vcpvv/LFW.tar.gz?dl=1
# Untar them by yourself
# Train face recognition model with softmax
$ python3 main.py --config config/example.yml
# Train face recognition model with triplet loss
$ python3 main.py --config config/facenet.yml
Face Verification Accuracy | Pretrained Model | |
---|---|---|
Softmax Loss | 0.87 | Link |
Triplet Loss | 0.90 | Link |