Update app.py

app.py

@@ -5,6 +5,8 @@ from scipy.spatial.distance import cosine
 import cv2
 import os
 
+RECOGNITION_THRESHOLD = 0.5 
+
 # Load the embedding model
 embedding_model = tf.keras.models.load_model('embedding_model.h5')
 
@@ -23,10 +25,21 @@ def generate_embedding(image):
     return embedding_model.predict(preprocessed_image)[0]
 
 # Register new user
-def register_user(image, user_id):
-    embedding = generate_embedding(image)
-    user_embeddings[user_id] = embedding
-    return f"User {user_id} registered successfully."
+def recognize_user(image):
+    new_embedding = generate_embedding(image)
+    min_distance = float('inf')
+    recognized_user_id = "Unknown"
+    
+    for user_id, embedding in user_embeddings.items():
+        distance = cosine(new_embedding, embedding)
+        if distance < min_distance:
+            min_distance = distance
+            recognized_user_id = user_id
+    
+    if min_distance > RECOGNITION_THRESHOLD:
+        return "User not recognized."
+    else:
+        return f"Recognized User: {recognized_user_id}"
 
 # Recognize user
 def recognize_user(image):