From 160b8372b3fea409cf874a8a63682d7464581267 Mon Sep 17 00:00:00 2001
From: Sefik Ilkin Serengil <serengil@gmail.com>
Date: Fri, 18 Apr 2025 12:48:05 +0100
Subject: [PATCH] Update README.md

encrypt embedding credit resized
---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index c38820c..12d752b 100644
--- a/README.md
+++ b/README.md
@@ -337,7 +337,7 @@ calculated_similarity = cs.decrypt(encrypted_cosine_similarity)[0]
 print("same person" if calculated_similarity >= 1 - threshold else "different persons")
 ```
 
-<p align="center"><img src="https://raw.githubusercontent.com/serengil/deepface/refs/heads/master/icon/encrypt-embeddings.jpg" width="80%" height="80%"></p>
+<p align="center"><img src="https://raw.githubusercontent.com/serengil/deepface/refs/heads/master/icon/encrypt-embeddings.jpg" width="60%" height="60%"></p>
 
 In this scheme, we leverage the computational power of the cloud to compute encrypted cosine similarity. However, the cloud has no knowledge of the actual calculations it performs. That's the **magic** of homomorphic encryption! Only the secret key holder on the on-premises side can decrypt the encrypted cosine similarity and determine whether the pair represents the same person or different individuals. Check out [`LightPHE`](https://github.com/serengil/LightPHE) library to find out more about partially homomorphic encryption.