Update app.py

app.py

@@ -57,13 +57,21 @@ def process_video(video_path):
 def estimate_trajectory(ball_positions, frames):
     if len(ball_positions) < 2:
         return None, None, None, "Error: Fewer than 2 ball detections for trajectory"
+    
     frame_height = frames[0].shape[0]
-
+    
     # Extract x, y coordinates
     x_coords = [pos[0] for pos in ball_positions]
     y_coords = [pos[1] for pos in ball_positions]
     times = np.arange(len(ball_positions)) / FRAME_RATE
 
+    # Detect the pitch point: find when the ball touches the ground
+    pitch_point = None
+    for i, y in enumerate(y_coords):
+        if y > frame_height * 0.75:  # Threshold for ground contact (near the bottom of the frame)
+            pitch_point = ball_positions[i]
+            break
+    
     # Find impact point (closest to batsman, near stumps)
     impact_idx = None
     for i, y in enumerate(y_coords):
@@ -72,8 +80,7 @@ def estimate_trajectory(ball_positions, frames):
             break
     if impact_idx is None:
         impact_idx = len(ball_positions) - 1  # Fallback to last detection
-
-    pitch_point = ball_positions[0]
+    
     impact_point = ball_positions[impact_idx]
 
     # Use positions up to impact for interpolation
@@ -132,51 +139,59 @@ def generate_slow_motion(frames, trajectory, pitch_point, impact_point, detectio
 
     trajectory_points = np.array(trajectory[:len(detection_frames)], dtype=np.int32).reshape((-1, 1, 2))
 
+    pitch_point_detected = False
+    impact_point_detected = False
+
     for i, frame in enumerate(frames):
         # Draw trajectory (blue line) only for frames with detections
         if i in detection_frames and trajectory_points.size > 0:
             cv2.polylines(frame, [trajectory_points[:detection_frames.index(i) + 1]], False, (255, 0, 0), 2)
 
-        # Draw pitch point (red circle with label) when the ball touches the ground (y < ground threshold)
-        if pitch_point and impact_point and i >= detection_frames[0]:
+        # Draw pitch point (red circle with label) when the ball touches the ground
+        if pitch_point and not pitch_point_detected:
             x, y = pitch_point
-            if y > frame.shape[0] * 0.75:  # Threshold for ground contact (adjust as necessary)
-                cv2.circle(frame, (int(x), int(y)), 8, (0, 0, 255), -1)
-                cv2.putText(frame, "Pitch Point", (int(x) + 10, int(y) - 10), 
-                            cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2)
-
-        # Draw impact point (yellow circle with label) when ball is near stumps (y near bottom)
-        if impact_point and i >= detection_frames[min(len(detection_frames) - 1, detection_frames.index(detection_frames[-1]))]:
+            if y > frame.shape[0] * 0.75:  # Adjust this threshold for the ground position
+                pitch_point_detected = True
+        if pitch_point_detected:
+            cv2.circle(frame, (int(x), int(y)), 8, (0, 0, 255), -1)
+            cv2.putText(frame, "Pitch Point", (int(x) + 10, int(y) - 10), 
+                        cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2)
+
+        # Draw impact point (yellow circle with label) when ball is near stumps
+        if impact_point and not impact_point_detected:
             x, y = impact_point
-            if y > frame.shape[0] * 0.85:  # Threshold for impact (adjust as necessary)
-                cv2.circle(frame, (int(x), int(y)), 8, (0, 255, 255), -1)
-                cv2.putText(frame, "Impact Point", (int(x) + 10, int(y) + 20), 
-                            cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 255), 2)
-
+            if y > frame.shape[0] * 0.85:  # Adjust this threshold for impact point
+                impact_point_detected = True
+        if impact_point_detected:
+            cv2.circle(frame, (int(x), int(y)), 8, (0, 255, 255), -1)
+            cv2.putText(frame, "Impact Point", (int(x) + 10, int(y) + 20), 
+                        cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 255), 2)
+
+        # Write frames to output video
         for _ in range(SLOW_MOTION_FACTOR):
             out.write(frame)
+
     out.release()
     return output_path
 
 def drs_review(video):
     frames, ball_positions, detection_frames, debug_log = process_video(video)
     if not frames:
-        return f"Error: Failed to process video\nDebug Log:\n{debug_log}", None
+        return f"Error: Failed to process video", None
     trajectory, pitch_point, impact_point, trajectory_log = estimate_trajectory(ball_positions, frames)
     decision, trajectory, pitch_point, impact_point = lbw_decision(ball_positions, trajectory, frames, pitch_point, impact_point)
 
     output_path = f"output_{uuid.uuid4()}.mp4"
     slow_motion_path = generate_slow_motion(frames, trajectory, pitch_point, impact_point, detection_frames, output_path)
 
-    debug_output = f"{debug_log}\n{trajectory_log}"
-    return f"DRS Decision: {decision}\nDebug Log:\n{debug_output}", slow_motion_path
+    return f"DRS Decision: {decision}", slow_motion_path
 
 # Gradio interface
 iface = gr.Interface(
     fn=drs_review,
     inputs=gr.Video(label="Upload Video Clip"),
     outputs=[
-        gr.Textbox(label="DRS Decision and Debug Log"),
+        gr.Textbox(label="DRS Decision"),
         gr.Video(label="Slow-Motion Replay with Ball Detection (Green), Trajectory (Blue Line), Pitch Point (Red), Impact Point (Yellow)")
     ],
     title="AI-Powered DRS for LBW in Local Cricket",