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| title: SmartVision AI | |
| emoji: π | |
| colorFrom: blue | |
| colorTo: green | |
| sdk: docker | |
| pinned: false | |
| license: mit | |
| app_port: 7860 | |
| # π SmartVision: Advanced Object Detection & Classification | |
| This project is an end-to-end Computer Vision pipeline designed for training and comparing multiple Deep Learning architectures (VGG16, ResNet50, MobileNetV2, EfficientNet) and real-time detection via YOLOv8. | |
| ## π Project Features | |
| * **Multi-Model Comparison:** Dynamic leaderboard comparing accuracy and inference latency. | |
| * **YOLOv8 Integration:** Real-time object detection on 25 COCO-subset classes. | |
| * **Automated Pipeline:** Scripts for dataset generation, model training, and evaluation. | |
| ## π Directory Structure | |
| * `app.py`: Main Streamlit interface. | |
| * `models/`: Contains the trained `.h5` and `.pt` weights. | |
| * `pages/`: Additional dashboard pages for performance analytics. | |
| * `training/`: Specialized scripts for each architecture. | |
| ## π οΈ Local Setup | |
| 1. Clone the repository. | |
| 2. Install dependencies: `pip install -r requirements.txt` | |
| 3. Run the app: `streamlit run app.py` |