Human Disease Prediction GitHub license

Overview Human Disease Prediction is a machine learning project that uses transfer learning with ResNet-50 and ImageNet weights to predict various skin diseases. The project provides an easy-to-use web interface for users to upload images of skin conditions and get predictions for the following diseases:

'BA- cellulitis': 0 'BA-impetigo': 1 'FU-athlete-foot': 2 'FU-nail-fungus': 3 'FU-ringworm': 4 'PA-cutaneous-larva-migrans': 5 'VI-chickenpox': 6 'VI-shingles': 7 The application is deployed locally using Streamlit.

Project Structure The project's structure is organized as follows:

bash Copy code ├── app.py # Streamlit application source code ├── Disease_prediction.h5 # Pretrained model for disease prediction ├── requirements.txt # Project dependencies ├── screenshots/ # Screenshots of the application ├── README.md # This README file Setup and Installation Clone this repository to your local machine:

cd human-disease-prediction Install the required Python packages:

pip install -r requirements.txt Usage Start the Streamlit application:

streamlit run app.py Access the application by opening the provided URL in your web browser.

Upload an image of the skin condition you want to predict.

Click the "Predict" button to get the disease prediction.

Acknowledgments ResNet-50 with ImageNet weights Streamlit for the web interface# Human-Disease-Prediction