Update app.py

app.py

@@ -16,62 +16,50 @@ sys.excepthook = custom_excepthook
 def list_overlay_images(directory):
     return [f for f in os.listdir(directory) if f.endswith('.png')]
 
-def process_frame(frame, overlay, LEFT_EYE, RIGHT_EYE, LEFT_IRIS, RIGHT_IRIS, 
-                  min_detection_confidence, min_tracking_confidence, alpha):
-    try:
-        mp_face_mesh = mp.solutions.face_mesh
-        with mp_face_mesh.FaceMesh(
-            max_num_faces=1,
-            refine_landmarks=True,
-            min_detection_confidence=min_detection_confidence,
-            min_tracking_confidence=min_tracking_confidence
-        ) as face_mesh:
-            rgb_frame = cv.cvtColor(frame, cv.COLOR_BGR2RGB)
-            rgba_frame = cv.cvtColor(frame, cv.COLOR_BGR2RGBA)
-            height, width = rgba_frame.shape[:2]
-            results = face_mesh.process(rgb_frame)
-            if results.multi_face_landmarks:
-                zero_overlay = np.zeros_like(rgba_frame)
-                mesh_points = np.array([np.multiply([p.x, p.y],
-                        [width, height]).astype(int) for p in results.multi_face_landmarks[0].landmark])
-                iris_mask_left = np.zeros(rgba_frame.shape, dtype=np.uint8)
-                iris_mask_right = np.zeros(rgba_frame.shape, dtype=np.uint8)
-                _, re_ratio, le_ratio = blinkRatio(rgb_frame, mesh_points, RIGHT_EYE, LEFT_EYE)
-                (l_cx, l_cy), l_radius = cv.minEnclosingCircle(mesh_points[LEFT_IRIS])
-                (r_cx, r_cy), r_radius = cv.minEnclosingCircle(mesh_points[RIGHT_IRIS])
-                center_left = (int(l_cx), int(l_cy))
-                center_right = (int(r_cx), int(r_cy))
-                cv.circle(iris_mask_left, center_left, int(l_radius), (255, 0, 0, 255), -1, cv.LINE_AA)
-                cv.circle(iris_mask_right, center_right, int(r_radius), (255, 0, 0, 255), -1, cv.LINE_AA)
-                bbx_size_l = int((l_radius * 2) / 2)
-                bbx_size_r = int((r_radius * 2) / 2)
-                resized_overlay_l = cv.resize(overlay, (bbx_size_l * 2, bbx_size_l * 2), interpolation=cv.INTER_CUBIC)
-                resized_overlay_r = cv.resize(overlay, (bbx_size_r * 2, bbx_size_r * 2), interpolation=cv.INTER_CUBIC)
-                y1_r = center_right[1] - bbx_size_r
-                y2_r = center_right[1] + bbx_size_r
-                x1_r = center_right[0] - bbx_size_r
-                x2_r = center_right[0] + bbx_size_r
-                y1_l = center_left[1] - bbx_size_l
-                y2_l = center_left[1] + bbx_size_l
-                x1_l = center_left[0] - bbx_size_l
-                x2_l = center_left[0] + bbx_size_l
-                if (resized_overlay_l.shape == zero_overlay[y1_l:y2_l, x1_l:x2_l].shape) & (le_ratio < 5.0) & (le_ratio > 2.0):
-                    zero_overlay[y1_l:y2_l, x1_l:x2_l] = resized_overlay_l
-                if (resized_overlay_r.shape == zero_overlay[y1_r:y2_r, x1_r:x2_r].shape) & (re_ratio < 5.0) & (re_ratio > 2.0):
-                    zero_overlay[y1_r:y2_r, x1_r:x2_r] = resized_overlay_r
-                eye_mask_left = np.zeros(rgba_frame.shape, dtype=np.uint8)
-                eye_mask_right = np.zeros(rgba_frame.shape, dtype=np.uint8)
-                cv.fillPoly(eye_mask_left, [mesh_points[LEFT_EYE]], (255, 0, 0, 255))
-                cv.fillPoly(eye_mask_right, [mesh_points[RIGHT_EYE]], (255, 0, 0, 255))
-                zero_overlay[np.where((iris_mask_left[:, :, 3] > 0) & (eye_mask_left[:, :, 3] == 0))] = 0
-                zero_overlay[np.where((iris_mask_right[:, :, 3] > 0) & (eye_mask_right[:, :, 3] == 0))] = 0
-                rgba_frame = cv.addWeighted(rgba_frame, 1, zero_overlay, alpha, 0)
-        return rgba_frame
-    except Exception as e:
-        print(f"Error in process_frame: {e}")
-        traceback.print_exc()
+def process_frame(frame, overlay, alpha, LEFT_EYE, RIGHT_EYE, LEFT_IRIS, RIGHT_IRIS):
+    rgb_frame = cv.cvtColor(frame, cv.COLOR_BGR2RGB)
+    rgba_frame = cv.cvtColor(frame, cv.COLOR_BGR2RGBA)
+    height, width = rgba_frame.shape[:2]
+    results = face_mesh.process(rgb_frame)
+    if results.multi_face_landmarks:
+        zero_overlay = np.zeros_like(rgba_frame)
+        mesh_points = np.array([np.multiply([p.x, p.y],
+                [width, height]).astype(int) for p in results.multi_face_landmarks[0].landmark])
+        iris_mask_left = np.zeros(rgba_frame.shape, dtype=np.uint8)
+        iris_mask_right = np.zeros(rgba_frame.shape, dtype=np.uint8)
+        _, re_ratio, le_ratio = blinkRatio(rgb_frame, mesh_points, RIGHT_EYE, LEFT_EYE)
+        (l_cx, l_cy), l_radius = cv.minEnclosingCircle(mesh_points[LEFT_IRIS])
+        (r_cx, r_cy), r_radius = cv.minEnclosingCircle(mesh_points[RIGHT_IRIS])
+        center_left = (int(l_cx), int(l_cy))
+        center_right = (int(r_cx), int(r_cy))
+        cv.circle(iris_mask_left, center_left, int(l_radius), (255, 0, 0, 255), -1, cv.LINE_AA)
+        cv.circle(iris_mask_right, center_right, int(r_radius), (255, 0, 0, 255), -1, cv.LINE_AA)
+        bbx_size_l = int((l_radius * 2) / 2)
+        bbx_size_r = int((r_radius * 2) / 2)
+        resized_overlay_l = cv.resize(overlay, (bbx_size_l * 2, bbx_size_l * 2), interpolation=cv.INTER_CUBIC)
+        resized_overlay_r = cv.resize(overlay, (bbx_size_r * 2, bbx_size_r * 2), interpolation=cv.INTER_CUBIC)
+        y1_r = center_right[1] - bbx_size_r
+        y2_r = center_right[1] + bbx_size_r
+        x1_r = center_right[0] - bbx_size_r
+        x2_r = center_right[0] + bbx_size_r
+        y1_l = center_left[1] - bbx_size_l
+        y2_l = center_left[1] + bbx_size_l
+        x1_l = center_left[0] - bbx_size_l
+        x2_l = center_left[0] + bbx_size_l
+        if (resized_overlay_l.shape == zero_overlay[y1_l:y2_l, x1_l:x2_l].shape) & (le_ratio < 5.0) & (le_ratio > 2.0):
+            zero_overlay[y1_l:y2_l, x1_l:x2_l] = resized_overlay_l
+        if (resized_overlay_r.shape == zero_overlay[y1_r:y2_r, x1_r:x2_r].shape) & (re_ratio < 5.0) & (re_ratio > 2.0):
+            zero_overlay[y1_r:y2_r, x1_r:x2_r] = resized_overlay_r
+        eye_mask_left = np.zeros(rgba_frame.shape, dtype=np.uint8)
+        eye_mask_right = np.zeros(rgba_frame.shape, dtype=np.uint8)
+        cv.fillPoly(eye_mask_left, [mesh_points[LEFT_EYE]], (255, 0, 0, 255))
+        cv.fillPoly(eye_mask_right, [mesh_points[RIGHT_EYE]], (255, 0, 0, 255))
+        zero_overlay[np.where((iris_mask_left[:, :, 3] > 0) & (eye_mask_left[:, :, 3] == 0))] = 0
+        zero_overlay[np.where((iris_mask_right[:, :, 3] > 0) & (eye_mask_right[:, :, 3] == 0))] = 0
+        rgba_frame = cv.addWeighted(rgba_frame, 1, zero_overlay, alpha, 0)
+    return rgba_frame
 
-def process_image(input_image, overlay_file, alpha=0.3, min_detection_confidence=0.5, min_tracking_confidence=0.5):
+def process_image(input_image, overlay_file, alpha=0.3):
     overlay_file = overlay_file + '.png'
     overlay_path = os.path.join(os.getcwd(),'overlays', overlay_file)
     overlay = cv.imread(overlay_path, cv.IMREAD_UNCHANGED)
@@ -79,13 +67,11 @@ def process_image(input_image, overlay_file, alpha=0.3, min_detection_confidence
     w,h,_ = frame.shape
     new_h = 500
     new_w = int((w/h)*new_h)
-    frame = cv.resize(frame, (new_h,new_w), interpolation=cv.INTER_CUBIC)
-    processed_frame = process_frame(frame, overlay, LEFT_EYE, RIGHT_EYE, LEFT_IRIS, RIGHT_IRIS, 
-                                    min_detection_confidence, min_tracking_confidence, alpha)
+    frame = cv.resize(frame, (new_h,new_w), interpolation=cv.INTER_NEAREST)
+    processed_frame = process_frame(frame, overlay, alpha, LEFT_EYE, RIGHT_EYE, LEFT_IRIS, RIGHT_IRIS)
     return cv.cvtColor(processed_frame, cv.COLOR_BGR2RGB)
 
-def process_video(input_video, overlay_file, alpha=0.3, output_format='mp4', output_frame_rate=30,
-                                    min_detection_confidence=0.5, min_tracking_confidence=0.5):
+def process_video(input_video, overlay_file, alpha=0.3, output_format='mp4', output_frame_rate=30):
     overlay_file = overlay_file + '.png'
     overlay_path = os.path.join(os.getcwd(),'overlays', overlay_file)
     overlay = cv.imread(overlay_path, cv.IMREAD_UNCHANGED)
@@ -107,9 +93,7 @@ def process_video(input_video, overlay_file, alpha=0.3, output_format='mp4', out
             ret, frame = cap.read()
             if ret == True:
                 frame = cv.resize(frame, (new_w,new_h), interpolation=cv.INTER_NEAREST)
-                processed_frame = process_frame(frame,overlay,LEFT_EYE, RIGHT_EYE, LEFT_IRIS, RIGHT_IRIS, 
-                                                float(min_detection_confidence), 
-                                                float(min_tracking_confidence), float(alpha))  # Assuming process_frame is a function that processes a single frame
+                processed_frame = process_frame(frame,overlay,alpha,LEFT_EYE, RIGHT_EYE, LEFT_IRIS, RIGHT_IRIS)  # Assuming process_frame is a function that processes a single frame
                 processed_frame = cv.cvtColor(processed_frame, cv.COLOR_RGBA2BGR)
                 out.write(processed_frame)
             else:
@@ -119,13 +103,15 @@ def process_video(input_video, overlay_file, alpha=0.3, output_format='mp4', out
     return output_path
 
 
-def process_webcam(frame, overlay_file, alpha=0.3, min_detection_confidence=0.5, min_tracking_confidence=0.5):
-    overlay_file = overlay_file + '.png'
-    overlay_path = os.path.join(os.getcwd(), overlay_file)
-    overlay = cv.imread(overlay_path, cv.IMREAD_UNCHANGED)
-    processed_frame = process_frame(frame, overlay, LEFT_EYE, RIGHT_EYE, LEFT_IRIS, RIGHT_IRIS, 
-                                    min_detection_confidence, min_tracking_confidence, alpha)
-    return processed_frame
+
+# Initialize face mesh once and reuse it
+mp_face_mesh = mp.solutions.face_mesh
+face_mesh = mp_face_mesh.FaceMesh(
+        max_num_faces=1,
+        refine_landmarks=True,
+        min_detection_confidence=0.5,
+        min_tracking_confidence=0.5
+    )
 
 LEFT_EYE = [362, 382, 381, 380, 374, 373, 390, 249, 263, 466, 388, 387, 386, 385, 384, 398]
 RIGHT_EYE = [33, 7, 163, 144, 145, 153, 154, 155, 133, 173, 157, 158, 159, 160, 161, 246]