pneumonia-prediction https://pneumonia-diagnosis.streamlit.app/

README for Pneumonia Detection from Chest X-rays

Project Overview:

This project utilizes machine learning to detect pneumonia from chest X-ray images. It includes two main components: a pneumonia classification model and an X-ray detector model. The application allows users to upload an image, classify if it's an X-ray, and predict the presence of pneumonia if applicable.

Features:

• Upload Images: Users can upload chest X-ray images (in JPG, JPEG, or PNG format) directly through the web interface.
• Prediction: The application uses a trained model to predict whether an uploaded image is an X-ray. If it is, it further predicts whether pneumonia is present.
• User-Friendly Interface: Built with Streamlit, the interface provides a seamless experience for users to interact with the prediction models.

Requirements:

Ensure you have the following dependencies installed:

• Python 3.8+
• streamlit
• fastai
• PIL (Pillow)

Setup Instructions:

1. Clone the repository:

   git clone https://github.com/khurshiduktamov/pneumonia-detection.git
   cd pneumonia-detection
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Run the Streamlit app:

   streamlit run app.py
   

4. Open your browser and navigate to http://localhost:8501 to use the application.

Usage:

• Upload a chest X-ray image using the file uploader.
• Wait for the prediction results to appear.
• If the image is classified as an X-ray, the app will predict whether pneumonia is present.

Contributions:

Contributions to improve the models or enhance the application's features are welcome! Please fork the repository, make your changes, and submit a pull request.

---