| import gradio as gr | |
| import cv2 | |
| import numpy as np | |
| from ball_tracker import detect_ball | |
| from trajectory import predict_trajectory | |
| from lbw_engine import evaluate_lbw | |
| from overlay_display import draw_overlay | |
| import tempfile | |
| def process_video(video_file): | |
| cap = cv2.VideoCapture(video_file) | |
| ball_path = [] | |
| output_frames = [] | |
| while cap.isOpened(): | |
| ret, frame = cap.read() | |
| if not ret: | |
| break | |
| ball = detect_ball(frame) | |
| if ball: | |
| ball_path.append(ball) | |
| if len(ball_path) > 5: | |
| try: | |
| a, b, c = predict_trajectory(ball_path) | |
| trajectory_func = lambda x: a * x**2 + b * x + c | |
| pitch_x = ball_path[0][0] | |
| impact_x = ball_path[-1][0] | |
| wicket_x = int((impact_x + 100) / 2) | |
| frame_width = frame.shape[1] | |
| verdict, pitch, impact, wickets = evaluate_lbw(pitch_x, impact_x, wicket_x, ball_path, frame_width) | |
| frame = draw_overlay(frame, ball_path, trajectory_func, verdict, (pitch, impact, wickets)) | |
| except Exception as e: | |
| print("Prediction error:", e) | |
| output_frames.append(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)) | |
| cap.release() | |
| return output_frames[-1] if output_frames else None | |
| demo = gr.Interface( | |
| fn=process_video, | |
| inputs=gr.Video(label="Upload a Cricket Delivery Video"), | |
| outputs=gr.Image(label="Decision Frame with Overlay"), | |
| title="🏏 Gully Cricket DRS - LBW Analysis" | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch(inbrowser=True, share=False) | |