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| title: WBC Classification | |
| emoji: 🩸 | |
| colorFrom: red | |
| colorTo: blue | |
| sdk: docker | |
| pinned: false | |
| license: mit | |
| app_port: 7860 | |
| # WBC Classification System | |
| An AI-powered White Blood Cell (WBC) classification system that can identify different types of white blood cells from microscopic images. | |
| ## Features | |
| - **Real-time Classification**: Upload images and get instant predictions | |
| - **Batch Processing**: Process multiple images simultaneously | |
| - **High Accuracy**: Deep learning model trained on medical imagery | |
| - **User-friendly Interface**: Simple web interface for easy interaction | |
| ## Supported Cell Types | |
| - Basophil | |
| - Eosinophil | |
| - Lymphocyte | |
| - Monocyte | |
| - Neutrophil | |
| ## Usage | |
| 1. **Single Image**: Upload a single microscopic image for classification | |
| 2. **Batch Processing**: Upload multiple images for simultaneous processing | |
| 3. **View Results**: Get detailed predictions with confidence scores | |
| ## API Endpoints | |
| - `GET /` - Main web interface | |
| - `POST /api/predict` - Single image prediction | |
| - `POST /api/predict_batch` - Batch image prediction | |
| - `GET /api/health` - Health check | |
| - `GET /api/model_info` - Model information | |
| ## Technical Details | |
| - **Framework**: FastAPI with TensorFlow | |
| - **Model**: Custom CNN architecture | |
| - **Input**: 128x128 RGB images | |
| - **Output**: Classification with confidence scores | |
| ## Development | |
| Built for medical image analysis and research purposes. The model is trained on high-quality microscopic images of white blood cells. | |
| ## License | |
| MIT License - See LICENSE file for details. |