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# Acne Detection Model |
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![Acne Detection](data:image/jpeg;base64,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) 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## Overview |
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This repository contains a YOLOv8-based model trained for detecting acne on African and dark skin tones. The model is designed to be inclusive, focusing on diverse datasets to improve dermatological applications' accuracy across various skin types. |
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## Model Details |
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- **Model Type:** YOLOv8 |
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- **Architecture:** YOLOv8 |
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- **Version:** 1.0 |
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## Usage |
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### Installation |
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```bash |
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pip install -r requirements.txt |
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``` |
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### Model Loading |
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```python |
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from ultralytics import YOLO |
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# Load the model |
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model = YOLO("acne.pt") |
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# Perform inference |
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result = model.detect_acne(image_path="path/to/test_image.jpg") |
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print(result) |
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``` |
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Replace `"acne.pt"` with the correct model weights file. |
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## License |
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This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details. |
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## Acknowledgments |
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- Data labeling by [Amina Shiga](https://www.linkedin.com/in/amina-shiga-07000522a) |
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- Model Training by [Nathaniel Handan](https://www.linkedin.com/in/nathanielhandan/) |
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## Contributing |
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We welcome contributions from the community. If you find any issues or have suggestions, please open an [issue](https://github.com/Tinny-Robot/acne-detection/issues) or submit a pull request. |
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## Contact |
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For inquiries, please contact [Nathanil Handan](mailto:[email protected]). |
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## References |
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- Ultralytics YOLOv8: https://github.com/ultralytics/ultralytics |
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- VGG Image Annotator (VIA): https://www.robots.ox.ac.uk/~vgg/software/via/ |