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This project uses deep learning algorithms and the Keras library to determine if a person has certain diseases or not from their chest x-rays and other scans. The trained model is displayed using Streamlit, which enables the user to upload an image and receive instant feedback.

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Pneumonia Detection using Chest X-rays

This project uses deep learning algorithms and Keras library to determine if a person has pneumonia or not from their chest x-rays. The trained model is displayed using Streamlit, which enables the user to upload an image and receive instant feedback.

Requirements

The following libraries are required for running this project:

  • TensorFlow
  • Keras
  • Pillow
  • Streamlit

Installation

If you have the requirements already installed, you can skip this section. If not, follow the steps below to install them:

  1. Install TensorFlow:

    pip install tensorflow
    
  2. Install Keras:

    pip install keras
    
  3. Install Pillow:

    pip install pillow
    
  4. Install Streamlit:

    pip install streamlit
    

Usage

  1. Clone the repository:

    git clone https://github.com/SiddharthRajpal/Pneumonia-Recognition-With-Python.git
    cd Pneumonia-Recognition-With-Python
    
  2. Run the Streamlit app:

    python3 -m streamlit run main.py
    

    or

    python -m streamlit run main.py
    

    or

    py -m streamlit run main.py
    
  3. Upload a chest x-ray image to see if a person has pneumonia or not.

About

This project uses deep learning algorithms and the Keras library to determine if a person has certain diseases or not from their chest x-rays and other scans. The trained model is displayed using Streamlit, which enables the user to upload an image and receive instant feedback.

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