Update app.py

app.py

@@ -130,21 +130,32 @@ def spatial_pyramid(image, num_bins):
     # Concatenate histograms from all channels
     feature_vector = np.concatenate(histograms)
     return feature_vector
-def apply_circular_mask(frame, input_frame):
-    height, width, _ = frame.shape
+def add_circle_image_to_black_image(image):
+    # Convert the image to RGB format if it is not already
+    if len(image.shape) == 2:
+        image = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR)
+
+    # Get the height and width of the input image
+    height, width, _ = image.shape
+
+    # Create a black image with the same height and width as the input image
+    black_image = np.zeros((height, width, 3), dtype=np.uint8)
+
+    # Calculate the radius of the circle
+    radius = int(min(height, width) / 2)
+
+    # Create a mask for the circle
     mask = np.zeros((height, width), dtype=np.uint8)
-    center = (width // 2, height // 2)
-    radius = min(width, height) // 2
-
-    cv2.circle(mask, center, radius, 255, -1)  # Create a circular mask
-    circular_frame = cv2.bitwise_and(frame, frame, mask=mask)  # Apply the circular mask
-
-    # Overlay the circular frame onto a black background with the same shape as the input frame
-    black_frame = np.zeros_like(input_frame)
-    x_offset = (input_frame.shape[1] - circular_frame.shape[1]) // 2
-    y_offset = (input_frame.shape[0] - circular_frame.shape[0]) // 2
-    black_frame[y_offset:y_offset + circular_frame.shape[0], x_offset:x_offset + circular_frame.shape[1]] = circular_frame
-    return black_frame
+    cv2.circle(mask, (width // 2, height // 2), radius, (255, 255, 255), -1)
+
+    # Bitwise AND the input image with the mask to create a circular image
+    circular_image = cv2.bitwise_and(image, image, mask=mask)
+
+    # Add the circular image to the black image at the center
+    black_image[height // 2 - radius: height // 2 + radius, width // 2 - radius: width // 2 + radius] = circular_image
+
+    # Return the black image with the circular image in the center
+    return black_image
 class VideoProcessor:
     num_bins = 256
     video_stopped = False
@@ -323,7 +334,7 @@ class VideoProcessor:
                 cv2.putText(frm, text, (20, 50), cv2.FONT_HERSHEY_SIMPLEX, 2, (0, 255, 0))
             else:
                 cv2.putText(frm, text, (20, 50), cv2.FONT_HERSHEY_SIMPLEX, 2, (0, 0, 255))
-            frm = apply_circular_mask(frm, frame.to_ndarray(format="bgr24"))    
+            frm = add_circle_image_to_black_image(frm)    
             return av.VideoFrame.from_ndarray(frm, format='bgr24')
 # Inside your Streamlit app