From f084a1aad573fbdd53255b57a95d0bbd7a3b8139 Mon Sep 17 00:00:00 2001
From: Sefik Ilkin Serengil <serengil@gmail.com>
Date: Mon, 10 Mar 2025 15:09:39 +0000
Subject: [PATCH] Update README.md

---
 README.md | 12 ++++--------
 1 file changed, 4 insertions(+), 8 deletions(-)

diff --git a/README.md b/README.md
index 6fdc14e..9318b86 100644
--- a/README.md
+++ b/README.md
@@ -381,24 +381,20 @@ Even though vector embeddings are not reversible to original images, they still
 ```python
 from lightphe import LightPHE
 
+# define a plain vectors for source and target
+alpha = DeepFace.represent("img1.jpg")[0]["embedding"]
+beta = DeepFace.represent("target.jpg")[0]["embedding"]
+
 # build an additively homomorphic cryptosystem (e.g. Paillier) on-prem
 cs = LightPHE(algorithm_name = "Paillier", precision = 19)
-
-# export keys
 cs.export_keys("public.txt", public=True)
 
-# define a plain vector for source (user tower)
-alpha = DeepFace.represent("img1.jpg")[0]["embedding"]
-
 # encrypt source embedding
 encrypted_alpha = cs.encrypt(alpha)
 
 # restore the cryptosystem in cloud with only public key
 cloud_cs = LightPHE(algorithm_name = "Paillier", precision = 19, key_file = "public.txt")
 
-# define a plain vector for target (item tower)
-beta = DeepFace.represent("target.jpg")[0]["embedding"]
-
 # dot product of encrypted and plain embedding pair in cloud
 encrypted_cosine_similarity = encrypted_alpha @ beta