Update app.py

app.py

@@ -68,9 +68,6 @@ def extract_hog_features(img):
     return hog_features
 
 def get_face(img):
-    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
-    img = img.astype(np.float32) / 255.0
-    
     detector = MTCNN()
     faces = detector.detect_faces(img)
     if faces:
@@ -86,16 +83,21 @@ def verify(image, model, person):
         temp_image.write(image.read())
         temp_image_path = temp_image.name
 
-        if model == "Siamese":
-            siamese = SiameseNetwork()
-            siamese.load_state_dict(torch.load(f'siamese_{person.lower()}.pth'))
-            siamese.eval()
-
-            image = Image.open(temp_image_path)
+        image = cv2.imread(temp_image_path)
+            
+        face = get_face(image)
 
-            face = get_face(image)
+        temp_face_path = tempfile.mktemp(suffix=".jpg")
+        cv2.imwrite(temp_face_path, face)
+        
+        if face is not None:
+            if model == "Siamese":
+                siamese = SiameseNetwork()
+                siamese.load_state_dict(torch.load(f'siamese_{person.lower()}.pth'))
+                siamese.eval()
 
-            if face is not None:
+                face = Image.load(temp_face_path)
+    
                 face = preprocess_image_siamese(face)
             
                 with torch.no_grad():
@@ -107,20 +109,15 @@ def verify(image, model, person):
                     st.write("Match")
                 else:
                     st.write("Not Match")
-            else:
-                st.write("Face not detected")
-        
-        elif model == "HOG-SVM":
-            with open(f'./svm_{person.lower()}.pkl', 'rb') as f:
-                svm = joblib.load(f)
-            with open(f'./pca_{person.lower()}.pkl', 'rb') as f:
-                pca = joblib.load(f)
-
-            image = cv2.imread(temp_image_path)
-        
-            face = get_face(image)
-
-            if face is not None:
+    
+            elif model == "HOG-SVM":
+                with open(f'./svm_{person.lower()}.pkl', 'rb') as f:
+                    svm = joblib.load(f)
+                with open(f'./pca_{person.lower()}.pkl', 'rb') as f:
+                    pca = joblib.load(f)
+
+                face = cv2.imread(temp_face_path)
+                
                 face = preprocess_image_svm(face)
     
                 hog = extract_hog_features(face)
@@ -133,8 +130,6 @@ def verify(image, model, person):
                     st.write("Match")
                 else:
                     st.write("Not Match")
-            else:
-                st.write("Face not detected")
 
 def main():
     st.title("Face Verification")