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Merge pull request #20935 from crywang:dnn_face

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Fix problems in tutorial and python sample of dnn_face.

* Update dnn_face.markdown

* Update face_match.py
This commit is contained in:
Chengrui Wang
2021-10-27 20:23:42 +08:00
committed by GitHub
parent 60f949e36f
commit 244ba1a61a
2 changed files with 8 additions and 8 deletions
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samples/dnn/face_match.py
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@@ -38,20 +38,20 @@ face1_align = recognizer.alignCrop(img1, face1[1][0])
face2_align = recognizer.alignCrop(img2, face2[1][0])
# Extract features
face1_feature = recognizer.faceFeature(face1_align)
face2_feature = recognizer.faceFeature(face2_align)
face1_feature = recognizer.feature(face1_align)
face2_feature = recognizer.feature(face2_align)
# Calculate distance (0: cosine, 1: L2)
cosine_similarity_threshold = 0.363
cosine_score = recognizer.faceMatch(face1_feature, face2_feature, 0)
cosine_score = recognizer.match(face1_feature, face2_feature, 0)
msg = 'different identities'
if cosine_score >= cosine_similarity_threshold:
msg = 'the same identity'
print('They have {}. Cosine Similarity: {}, threshold: {} (higher value means higher similarity, max 1.0).'.format(msg, cosine_score, cosine_similarity_threshold))
l2_similarity_threshold = 1.128
l2_score = recognizer.faceMatch(face1_feature, face2_feature, 1)
l2_score = recognizer.match(face1_feature, face2_feature, 1)
msg = 'different identities'
if l2_score <= l2_similarity_threshold:
msg = 'the same identity'
print('They have {}. NormL2 Distance: {}, threshold: {} (lower value means higher similarity, min 0.0).'.format(msg, l2_score, l2_similarity_threshold))
print('They have {}. NormL2 Distance: {}, threshold: {} (lower value means higher similarity, min 0.0).'.format(msg, l2_score, l2_similarity_threshold))