Create app.py

app.py

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+import gradio as gr
+from video_processor import process_video
+from lbw_detector import detect_lbw_event
+from trajectory_predictor import predict_trajectory
+from visualizer import generate_output_video
+import tempfile
+import os
+
+def handle_upload(video_file):
+    # Step 1: Extract frames and data
+    video_path = video_file.name
+    frames, metadata = process_video(video_path)
+
+    # Step 2: Object detection and impact analysis
+    detections = detect_lbw_event(frames)
+
+    # Step 3: Trajectory prediction
+    trajectory_result = predict_trajectory(detections)
+
+    # Step 4: Visualization and decision video
+    result_video_path, decision = generate_output_video(
+        frames, detections, trajectory_result
+    )
+
+    return result_video_path, f"Decision: {decision}"
+
+def handle_live_simulation():
+    return "Live stream analysis is under development. Coming soon!"
+
+with gr.Blocks() as app:
+    gr.Markdown("# 🏏 LBW DRS System\nUpload a video or simulate a live appeal.")
+
+    with gr.Tabs():
+        with gr.TabItem("📤 Upload Video"):
+            video_input = gr.Video(label="Upload LBW Video")
+            run_button = gr.Button("Analyze")
+            output_video = gr.Video(label="Replay with AI Overlays")
+            decision_text = gr.Textbox(label="Final Decision")
+
+            run_button.click(
+                fn=handle_upload,
+                inputs=[video_input],
+                outputs=[output_video, decision_text]
+            )
+
+        with gr.TabItem("📺 Live Stream"):
+            live_info = gr.Textbox(value=handle_live_simulation(), label="Live System Status", interactive=False)
+
+app.launch()