Stray Dog Skin Disease Detection

Overview

This project aims to detect skin diseases in stray dogs using computer vision and deep learning techniques. By analyzing images, the model can classify whether a dog has a skin disease, helping in early detection and intervention for animal welfare.

Features

• Automated Disease Detection: Identifies skin diseases in stray dogs from images.
• Deep Learning Model: Uses CNN-based architectures for classification.
• Preprocessing Pipeline: Includes image augmentation and normalization.
• Evaluation Metrics: Uses accuracy, precision, recall, and F1-score for performance assessment.

Dataset

• The dataset consists of images of stray dogs with and without skin diseases.
• Images are labeled for supervised learning.

Technologies Used

• Python
• TensorFlow/Keras
• OpenCV
• NumPy & Pandas
• Matplotlib & Seaborn

Installation

1. Clone the repository:

   git clone https://github.com/guruprashanth2004/stray-dog-skin-disease-detection.git

Results

• Model performance is evaluated using various metrics.
• Visualizations of sample predictions are provided.

Contributions

Contributions are welcome! Feel free to submit issues or pull requests.

License

This project is licensed under the MIT License.

Contact

For any inquiries, reach out at [email protected].