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| title: Sickelcellcdcd | |
| emoji: ๐ | |
| colorFrom: red | |
| colorTo: blue | |
| sdk: gradio | |
| sdk_version: 5.45.0 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| # Sickle Cell Classification Gradio App | |
| This repository contains a Gradio application for classifying blood smear images into three categories: Sickle Cell (sickle), Non-Sickle (non_sickle), and Artifact/Impurities/Noise (AIN). | |
| The application uses a trained YOLOv8 classification model. | |
| ## Files | |
| - `app.py`: The Python code for the Gradio interface. | |
| - `requirements.txt`: Lists the Python dependencies required to run the app. | |
| - `sickle_cls_model/weights/best.pt`: The trained YOLOv8 model weights. | |
| ## Setup and Running | |
| 1. Clone this repository. | |
| 2. Install the dependencies: `pip install -r requirements.txt` | |
| 3. Ensure the `sickle_cls_model` directory containing the `best.pt` weights is in the same directory as `app.py`, or update the `model_path` variable in `app.py` to the correct location. | |
| 4. Run the Gradio app: `python app.py` | |
| The Gradio interface will launch in your browser. | |