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| title: AI Sports Coaching | |
| emoji: 🎬 | |
| colorFrom: blue | |
| colorTo: purple | |
| sdk: gradio | |
| sdk_version: 5.34.0 | |
| app_file: app.py | |
| pinned: false | |
| # 🎬 AI Sports Coaching System | |
| A video-based pose estimation and AI analysis platform powered by Vision-Language Models (VLMs). Users can upload videos, perform pose detection, temporal downsampling, and get intelligent feedback. | |
| ## Features | |
| - 📹 **Video Upload**: Support for multiple video formats | |
| - 🤖 **Pose Estimation**: Human keypoint detection | |
| - ⏱️ **Temporal Downsampling**: Configurable frame rate reduction | |
| - 🧠 **AI Analysis**: Integrate LLMs/VLMs for intelligent insights | |
| - 🐍 **Python Processing**: Custom data processing and analysis pipelines | |
| - 📊 **Result Visualization**: Multi-dimensional result display | |
| - ⭐ **Scoring Mechanism**: User feedback scoring for outputs | |
| ## Workflow | |
| 1. **Video Upload** → Upload one or more videos for analysis | |
| 2. **Pose Estimation** → Extract human keypoint data | |
| 3. **Temporal Downsampling** → Reduce frame rate according to settings | |
| 4. **AI Analysis** → Use VLM/LLM to analyze pose features | |
| 5. **Python Processing** → Run custom analysis scripts | |
| 6. **Result Generation** → Produce a comprehensive analysis report | |
| 7. **Scoring** → User rates output quality (e.g., 1–5) | |
| ## Usage | |
| 1. Upload video file(s) | |
| 2. Configure downsampling rate (e.g., 1–10) | |
| 3. Click “Start Processing” | |
| 4. View results in different tabs (pose visualization, analysis report, charts, etc.) | |
| 5. Provide feedback score for the outputs | |
| ## TODO | |
| - **Accelerate Pose Estimation** | |
| - Optimize model inference (e.g., model pruning/quantization, GPU/CPU parallelism) | |
| - Batch processing for multiple videos or frames | |
| - Investigate lightweight architectures or delegate to hardware accelerators | |
| - **Local Deployment of VLMs** | |
| - Documentation for downloading and setting up VLM weights locally | |
| - Instructions for environment configuration (dependencies, hardware requirements) | |
| - Offline inference capabilities and fallback strategies | |
| - Security considerations for storing API keys or model files | |
| - **Support Multiple Video Formats** | |
| - Automatic compatibility check and conversion (e.g., mp4, avi, mov, webm) | |
| - Integrate ffmpeg (or similar) for on-the-fly format handling | |
| - Graceful fallback or user guidance when format is unsupported | |
| - **Extend Scoring & Feedback Loop** | |
| - Store user scores along with video metadata | |
| - Use scores to fine-tune or adjust analysis parameters over time | |
| - **Support Different Language** | |
| - Use different language prompts for different language | |
| - Update prompts for stable language-control | |
| ## License | |
| MIT License |