fixing preprocesing

app.py

@@ -20,10 +20,10 @@ facenet.eval()  # Set the model to evaluation mode
 val_test_transform = transforms.Compose([
     transforms.Resize((160, 160)),  # FaceNet expects 160x160 input
     transforms.ToTensor(),
-    transforms.Normalize(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])
+    transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
 ])
 
-def compare_faces(embedding1, embedding2, threshold=0.5):  # Adjusted threshold
+def compare_faces(embedding1, embedding2, threshold=0.2):  # Adjusted threshold
     dist = np.linalg.norm(embedding1 - embedding2)
     return dist, dist < threshold