github/deepface
1
1
Fork 0
mirror of https://github.com/serengil/deepface.git synced 2025-06-06 11:35:21 +00:00
Code Issues Packages Projects Releases Wiki Activity

Update README.md

Browse Source 
phe snippet updated
This commit is contained in:
Sefik Ilkin Serengil 2025-03-05 12:41:42 +00:00 committed by GitHub
parent 53085ac5a1
commit d16e2f083e
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
1 changed files with 5 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

12
README.md
View File

@ -414,7 +414,7 @@ def on_prem():
onprem_cs.export_keys("secret.txt") onprem_cs.export_keys("secret.txt")
onprem_cs.export_keys("public.txt", public=True) onprem_cs.export_keys("public.txt", public=True)
# find l2 normalized vector embeddings - VGG-Face already does # find l2 normalized and all positive vector embeddings - VGG-Face already does
source_embedding = DeepFace.represent("img1.jpg")[0]["embedding"] source_embedding = DeepFace.represent("img1.jpg")[0]["embedding"]
# encrypt source embedding # encrypt source embedding
@ -422,10 +422,10 @@ def on_prem():
return encrypted_source_embedding return encrypted_source_embedding
def cloud(encrypted_source_embedding): def cloud(encrypted_source_embedding):
# build the cryptosystem in cloud with only public key # restore the built cryptosystem in cloud with only public key
cloud_cs = LightPHE(algorithm_name = "Paillier", precision = 19, key_file = "public.txt") cloud_cs = LightPHE(algorithm_name = "Paillier", precision = 19, key_file = "public.txt")
# find l2 normalized vector embeddings - VGG-Face already does # find l2 normalized and all positive vector embeddings - VGG-Face already does
target_embedding = DeepFace.represent("target.jpg")[0]["embedding"] target_embedding = DeepFace.represent("target.jpg")[0]["embedding"]
# find dot product of encrypted embedding and plain embedding # find dot product of encrypted embedding and plain embedding
@ -434,16 +434,14 @@ def cloud(encrypted_source_embedding):
# confirm that cloud cannot decrypt it even though it is calculated by cloud # confirm that cloud cannot decrypt it even though it is calculated by cloud
with pytest.raises(ValueError, match="must have private key"): with pytest.raises(ValueError, match="must have private key"):
cloud_cs.decrypt(encrypted_cosine_similarity) cloud_cs.decrypt(encrypted_cosine_similarity)
return encrypted_cosine_similarity return encrypted_cosine_similarity
def proof_of_work(encrypted_cosine_similarity, threshold = 0.68): def verify(encrypted_cosine_similarity, threshold = 0.68):
# build the cryptosystem on-prem with secret key # restore the built cryptosystem on-prem with secret key
cloud_cs = LightPHE(algorithm_name = "Paillier", precision = 19, key_file = "secret.txt") cloud_cs = LightPHE(algorithm_name = "Paillier", precision = 19, key_file = "secret.txt")
# restore cosine similarity # restore cosine similarity
cosine_similarity = onprem_cs.decrypt(encrypted_cosine_similarity)[0] cosine_similarity = onprem_cs.decrypt(encrypted_cosine_similarity)[0]
print("same person" if cosine_similarity >= 1 - threshold else "different persons") print("same person" if cosine_similarity >= 1 - threshold else "different persons")
``` ```