face similarity

app/Hackathon_setup/face_recognition.py

@@ -94,10 +94,10 @@ def get_similarity(img1, img2):
     print('face1.type', type(face1))
 
     output1,output2 = feature_net(face1,face2)
-    #normalized_face1 = F.normalize(output1, dim=1)
-    #normalized_face2 = F.normalize(output2, dim=1)
-    #euclidean_distance = F.pairwise_distance(normalized_face1, normalized_face2)
-    euclidean_distance = F.pairwise_distance(output1, output2)
+    normalized_face1 = F.normalize(output1, dim=1)
+    normalized_face2 = F.normalize(output2, dim=1)
+    euclidean_distance = F.pairwise_distance(normalized_face1, normalized_face2)
+    #euclidean_distance = F.pairwise_distance(output1, output2)
     #pairwise - more distance means less similarity
     #cosine similarity - more means more similarity btwn 2 arrays
     # Use euclidean similarity to measure the similarity between given two images