Update app.py

app.py

@@ -31,7 +31,7 @@ BATCH_SIZE = 4  # Process 4 frames at a time
 
 # Load model
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-model = attempt_load("yolov5s.pt")  # Load yolov5s.pt instead of best.pt
+model = attempt_load("yolov5s.pt")  # Load yolov5s.pt
 model.to(device).eval()  # Move model to device and set to evaluation mode
 
 # Function to process video and detect ball
@@ -240,14 +240,18 @@ def drs_analysis(video):
         # Overlay pitch map in top-right corner
         if pitch_x is not None and pitch_y is not None:
             map_width = 200
-            map_height = int(map_width * PITCH_LENGTH / PITCH_WIDTH)
+            # Cap map_height to 25% of frame height to ensure it fits
+            map_height = min(int(map_width * PITCH_LENGTH / PITCH_WIDTH), frame_height // 4)
             pitch_map = np.zeros((map_height, map_width, 3), dtype=np.uint8)
             pitch_map[:] = (0, 255, 0)  # Green pitch
             cv2.rectangle(pitch_map, (0, map_height-10), (map_width, map_height), (0, 51, 51), -1)  # Brown stumps
             bounce_x = int((pitch_x + PITCH_WIDTH/2) / PITCH_WIDTH * map_width)
             bounce_y = int((1 - pitch_y / PITCH_LENGTH) * map_height)
             cv2.circle(pitch_map, (bounce_x, bounce_y), 5, (0, 0, 255), -1)  # Red bounce point
-            frame[0:map_height, frame_width-map_width:frame_width] = cv2.resize(pitch_map, (map_width, map_height))
+            # Ensure overlay fits within frame
+            overlay_region = frame[0:map_height, frame_width-map_width:frame_width]
+            if overlay_region.shape[0] >= map_height and overlay_region.shape[1] >= map_width:
+                frame[0:map_height, frame_width-map_width:frame_width] = cv2.resize(pitch_map, (map_width, map_height))
 
         # Add text annotations
         text = f"LBW: {lbw_decision}\nSpeed: {speed_kmh:.2f} km/h"