viswanani's picture
Act as a senior and expert application developer with strong experience in software engineering, computer vision, and Gradio/Hugging Face deployment. 🎯 Objective: I want to build a professional-grade **DRS (Digital Review System)** app specifically for **LBW (Leg Before Wicket)** analysis in cricket. βš™οΈ Platform: Backend: Python Deployment: Hugging Face Spaces UI Framework: Gradio SDK Video input: Real-time or uploaded video πŸ”‘ Features to include: 1. **Two-page UI:** - **Live Page**: Live match video stream or recording; continuously buffers video. If LBW is appealed, automatically trims the last 5–10 seconds for analysis. - **Upload Page**: User uploads a video clip of an LBW incident manually for review. 2. **AI-Powered LBW Review System**: - Detect ball, bat, stumps, and player using YOLOv8 or MediaPipe - Detect ball-pitch point, bounce, and impact zone (pad/glove/bat) - Predict 3D **ball trajectory** post-impact using polynomial regression - **Virtual pitch & stumps overlay** with accurate alignment - Determine if ball is hitting the stumps (OUT) or missing (NOT OUT) 3. **Visual Output:** - Overlay graphics (trajectory arc, stump zone) - Auto zoom on impact - Ball speed estimation from frames - Batsman pose & impact analysis (hand/pad) - Display OUT / NOT OUT in a textbox - Generate a **Replay Video** with AI overlays 4. **Code Requirements:** - Structure code into modular .py files: - video_processor.py - lbw_detector.py - trajectory_predictor.py - visualizer.py - utils.py - app.py (main file with Gradio UI) - Include a clean requirements.txt file - Hugging Face-compatible (no GPU-only dependencies if deploying on free tier) πŸ“¦ Output I expect: Full modular codebase app.py with Gradio interface requirements.txt Sample input video(s) Instructions to deploy on Hugging Face Start with the folder structure and explain each module briefly. Then give me the requirements.txt and a working version of app.py to kick off development. We'll then go module by module. - Initial Deployment
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