Update README.md

README.md

@@ -20,8 +20,9 @@ http://www.cs.jhu.edu/~alanlab/Pubs17/wang2017normface.pdf
 
 # Train
 
-1. The dataset used in this paper is [CASIA-Webface](http://www.cbsr.ia.ac.cn/english/CASIA-WebFace-Database.html). Note that there are 3 identities overlap between CASIA-Webface and LFW. They are `0166921`, `1056413` and `1193098`. For fair evaluation, it is recommended to remove them from CAISA-Webface. 
-2. Align all face images using MTCNN. The script can be found in [my another github repository](https://github.com/happynear/FaceVerification/blob/master/dataset/general_align.m).
+1. The dataset used in this paper is [CASIA-Webface](http://www.cbsr.ia.ac.cn/english/CASIA-WebFace-Database.html). Note that there are 3 identities overlap between CASIA-Webface and LFW. They are `0166921`, `1056413` and `1193098`. For fair evaluation, it is recommended to remove them from CAISA-Webface.
+Update: Actually there are 17 overlap identities, the list is in [my FaceDatasets repository](https://github.com/happynear/FaceDatasets/blob/master/CASIA/webface_lfw_overlap_detail.txt).
+2. Align all face images using MTCNN. The script can be found in [my FaceVerification repository](https://github.com/happynear/FaceVerification/blob/master/dataset/general_align.m).
 3. Replace the final inner-product layer and softmax layer with layers defined in [scaled_cosine_softmax.prototxt](./prototxt/scaled_cosine_softmax.prototxt) or [normalized_Euclidean_contrastive.prototxt](./prototxt/normalized_Euclidean_contrastive.prototxt).
 4. **Fine-tune** the network based on the original model using a small learning rate, say 0.001 or 0.0001.