This project implements a YOLOv8 model to detect and classify various skin diseases from images. The model is trained on a dataset of labeled images and can identify different types of skin conditions in real-time.
The dataset used is from Roboflow and includes images of different skin diseases with annotations.
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Clone the repository:
git clone https://github.com/yourusername/Skin-Disease-Detection-YOLOv8.git cd Skin-Disease-Detection-YOLOv8 -
Install dependencies:
pip install -r requirements.txt
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Train the model:
python train.py --data data/skin_disease.yaml --img 640 --batch 16 --epochs 100 --weights yolov8s.pt
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Run detection on new images:
python detect.py --weights runs/train/exp/weights/best.pt --source path/to/your/image_or_video
The model outputs detection results with bounding boxes and class labels, helping in the identification of skin diseases.
This project is licensed under the MIT License.