deploy app

app.py

@@ -70,7 +70,7 @@ file_urls = [
     'https://github.com/lucarei/orientation-detection-robotic-grasping/assets/22428774/cefd9731-c57c-428b-b401-fd54a8bd0a95',
     'https://github.com/lucarei/orientation-detection-robotic-grasping/assets/22428774/acbad76a-33f9-4028-b012-4ece5998c272',
     'https://github.com/lucarei/orientation-detection-robotic-grasping/assets/22428774/ce8a0fb9-99ea-4952-bcc4-3afa023066d9',
-    'https://www.dropbox.com/s/7sjfwncffg8xej2/video_7.mp4?dl=1'
+    'https://www.dropbox.com/scl/fi/z706oqbexdbk3gjvlzzjo/video-2160p.mp4?rlkey=7s3cx7tiwitwuad4k34f6jo9g&dl=0'
 ]
 
 def download_file(url, save_name):
@@ -165,6 +165,23 @@ def show_preds_video(video_path):
         if ret:
             frame_copy = frame.copy()
             outputs = model.predict(source=frame)
+            for object in range(len(outputs[0].masks.masks)):
+                #obtain BW image
+                bw=(outputs[0].masks.masks[object].cpu().numpy() * 255).astype("uint8")
+                contours, _ = cv2.findContours(bw, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)
+                for i, c in enumerate(contours):
+                    # Calculate the area of each contour
+                    area = cv2.contourArea(c)
+                    
+                    # Ignore contours that are too small or too large
+                    if area < 2500 or 500000 < area:
+                        continue
+                    
+                    # Draw each contour only for visualisation purposes
+                    cv2.drawContours(frame_copy, contours, i, (0, 0, 255), 2)
+                    
+                    # Find the orientation of each shape
+                    angle_deg = getOrientation(c, frame_copy)
             results = outputs[0].cpu().numpy()
             for i, det in enumerate(results.boxes.xyxy):
                 cv2.rectangle(