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Skin Disease Detection using YOLOv8

Description

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.

Dataset

The dataset used is from Roboflow and includes images of different skin diseases with annotations.

How to Use

  1. Clone the repository:

    git clone https://github.com/yourusername/Skin-Disease-Detection-YOLOv8.git
cd Skin-Disease-Detection-YOLOv8

  2. Install dependencies:

    pip install -r requirements.txt

  3. Train the model:

    python train.py --data data/skin_disease.yaml --img 640 --batch 16 --epochs 100 --weights yolov8s.pt

  4. Run detection on new images:

    python detect.py --weights runs/train/exp/weights/best.pt --source path/to/your/image_or_video

Results

The model outputs detection results with bounding boxes and class labels, helping in the identification of skin diseases.

License

This project is licensed under the MIT License.