| # RF-DETR SoccerNet - Requirements | |
| # Professional soccer object detection model | |
| # Core ML and Computer Vision | |
| torch>=1.9.0 | |
| torchvision>=0.10.0 | |
| rfdetr>=1.0.0 | |
| # Data Processing and Analysis | |
| pandas>=1.3.0 | |
| numpy>=1.19.0 | |
| # Image and Video Processing | |
| opencv-python-headless>=4.5.0 | |
| pillow>=8.0.0 | |
| # Progress and Utilities | |
| tqdm>=4.62.0 | |
| pyyaml>=5.4.0 | |
| # Optional: For advanced analysis and visualization | |
| # matplotlib>=3.5.0 | |
| # plotly>=5.0.0 | |
| # seaborn>=0.11.0 | |
| # Optional: For Hugging Face Hub integration | |
| # huggingface_hub>=0.10.0 | |
| # transformers>=4.20.0 | |
| # Optional: For distributed processing | |
| # accelerate>=0.12.0 | |
| # System Requirements Notes: | |
| # - CUDA 11.0+ recommended for GPU acceleration | |
| # - Python 3.8+ required | |
| # - At least 8GB RAM for video processing | |
| # - 4GB+ GPU memory for optimal performance |