Update app.py

app.py

@@ -27,7 +27,7 @@ def process_video(video_path):
     cap = cv2.VideoCapture(video_path)
     frames = []
     ball_positions = []
-    detection_frames = []  # Track frames with detections
+    detection_frames = []  # Track frames with exactly one detection
     debug_log = []
 
     frame_count = 0
@@ -38,28 +38,26 @@ def process_video(video_path):
         frame_count += 1
         frames.append(frame.copy())
         results = model.predict(frame, conf=CONF_THRESHOLD)
-        detections = 0
-        for detection in results[0].boxes:
-            if detection.cls == 0:  # Class 0 is the ball
-                detections += 1
-                x1, y1, x2, y2 = detection.xyxy[0].cpu().numpy()
-                ball_positions.append([(x1 + x2) / 2, (y1 + y2) / 2])
-                detection_frames.append(frame_count - 1)  # 0-based index
-                cv2.rectangle(frame, (int(x1), int(y1)), (int(x2), int(y2)), (0, 255, 0), 2)
+        detections = [det for det in results[0].boxes if det.cls == 0]  # Class 0 is cricketBall
+        if len(detections) == 1:  # Only consider frames with exactly one detection
+            x1, y1, x2, y2 = detections[0].xyxy[0].cpu().numpy()
+            ball_positions.append([(x1 + x2) / 2, (y1 + y2) / 2])
+            detection_frames.append(frame_count - 1)  # 0-based index
+            cv2.rectangle(frame, (int(x1), int(y1)), (int(x2), int(y2)), (0, 255, 0), 2)
         frames[-1] = frame
-        debug_log.append(f"Frame {frame_count}: {detections} ball detections")
+        debug_log.append(f"Frame {frame_count}: {len(detections)} ball detections")
     cap.release()
 
     if not ball_positions:
-        debug_log.append("No balls detected in any frame")
+        debug_log.append("No valid single-ball detections in any frame")
     else:
-        debug_log.append(f"Total ball detections: {len(ball_positions)}")
+        debug_log.append(f"Total valid single-ball detections: {len(ball_positions)}")
 
     return frames, ball_positions, detection_frames, "\n".join(debug_log)
 
 def estimate_trajectory(ball_positions, detection_frames, frames):
     if len(ball_positions) < 2:
-        return None, None, None, None, None, "Error: Fewer than 2 ball detections for trajectory"
+        return None, None, None, None, None, None, "Error: Fewer than 2 valid single-ball detections for trajectory"
     frame_height = frames[0].shape[0]
 
     # Extract x, y coordinates
@@ -67,7 +65,7 @@ def estimate_trajectory(ball_positions, detection_frames, frames):
     y_coords = [pos[1] for pos in ball_positions]
     times = np.array(detection_frames) / FRAME_RATE
 
-    # Pitch point: first detection or when y exceeds PITCH_ZONE_Y
+    # Pitch point: first valid detection or when y exceeds PITCH_ZONE_Y
     pitch_idx = 0
     for i, y in enumerate(y_coords):
         if y > frame_height * PITCH_ZONE_Y:
@@ -97,7 +95,7 @@ def estimate_trajectory(ball_positions, detection_frames, frames):
         fx = interp1d(times, x_coords, kind='linear', fill_value="extrapolate")
         fy = interp1d(times, y_coords, kind='quadratic', fill_value="extrapolate")
     except Exception as e:
-        return None, None, None, None, None, f"Error in trajectory interpolation: {str(e)}"
+        return None, None, None, None, None, None, f"Error in trajectory interpolation: {str(e)}"
 
     # Trajectory for visualization (detected frames only)
     vis_trajectory = list(zip(x_coords, y_coords))
@@ -117,7 +115,7 @@ def lbw_decision(ball_positions, full_trajectory, frames, pitch_point, impact_po
     if not frames:
         return "Error: No frames processed", None, None, None
     if not full_trajectory or len(ball_positions) < 2:
-        return "Not enough data (insufficient ball detections)", None, None, None
+        return "Not enough data (insufficient valid single-ball detections)", None, None, None
 
     frame_height, frame_width = frames[0].shape[:2]
     stumps_x = frame_width / 2
@@ -210,10 +208,10 @@ iface = gr.Interface(
     inputs=gr.Video(label="Upload Video Clip"),
     outputs=[
         gr.Textbox(label="DRS Decision and Debug Log"),
-        gr.Video(label="Very Slow-Motion Replay with Ball Detection (Green), Trajectory (Blue Line), Pitch Point (Red), Impact Point (Yellow)")
+        gr.Video(label="Very Slow-Motion Replay with Ball Detection (Green), Trajectory (Blue Line), Pitch Point (Red), Impact Point (Yellow), Stumps (White)")
     ],
     title="AI-Powered DRS for LBW in Local Cricket",
-    description="Upload a video clip of a cricket delivery to get an LBW decision and slow-motion replay showing ball detection (green boxes), trajectory (blue line), pitch point (red circle), and impact point (yellow circle)."
+    description="Upload a video clip of a cricket delivery to get an LBW decision and slow-motion replay showing ball detection (green boxes), trajectory (blue line), pitch point (red circle), impact point (yellow circle), and stumps (white lines)."
 )
 
 if __name__ == "__main__":