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joyhuang9473 / deepid-implementation

DeepID-implementation is an implementation of paper "Deep Learning Face Representation from Predicting 10,000 Classes"
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[INFO] The process of Xiang Wu's model #5

Open joyhuang9473 opened 8 years ago

joyhuang9473 commented 8 years ago

reference: happynear/FaceVerification

OK, I can tell you something you should be attention to in order to use Xiang Wu's model.

  1. Wu's alignment method is different from mine. He used the five-point landmark detection algorithm provided by CUHK, and he aligned the face image both horizontally and vertically, while in my implementation, only vertical alginment is applied.

  2. Wu's face image size is 128x128, so the aligned image should also be resized to 128x128.

  3. Wu's network was trained without mean file, so there is no need to find it.

  4. The distance between two facial images can be calculated by caffe directly, these configurations are in CASIA_demo.prototxt, including a Normalization layer and a Euclidean layer.

  5. The threshold of same / different person can be got by cross-validation on LFW or your own dataset. Since it is only one number, it is all ok to use whether 1000 samples or 10000 samples.
joyhuang9473 commented 8 years ago

4 AlfredXiangWu