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COVID Detection from Chest X-Ray Images

This project implements a deep learning model to detect COVID-19 from chest X-ray images. It includes a data preprocessing pipeline, model training scripts, and a Flask web application for easy deployment and usage.

Project Structure

  • model.py: Contains functions for image preprocessing and prediction
  • app.py: Flask web application for serving predictions
  • templates/index.html: HTML template for the web interface

Features

  • Data preprocessing for chest X-ray images
  • CNN model architecture for COVID-19 detection
  • Flask web application for easy deployment and usage
  • User-friendly interface for image upload and analysis
  • Docker support for containerized deployment

Prerequisites

  • Docker

Installation and Usage

Running the Web Application using Docker

  1. Pull the Docker image:

    docker pull pouryare/covid-detection-app:latest

  2. Run the Docker container:

    docker run -d -p 5000:5000 --name covid-app pouryare/covid-detection-app:latest

  3. Open a web browser and go to http://localhost:5000 to use the prediction interface.

Using the Interface

  1. Click on "Choose File" to select a chest X-ray image (PNG format only).
  2. Click "Upload and Analyze" to process the image.
  3. The result will be displayed, indicating whether COVID-19 is detected or not.

Model Architecture

The project uses a Convolutional Neural Network (CNN) for COVID-19 detection. The exact architecture details are encapsulated within the Docker image.

Performance

The model's performance metrics, such as accuracy, precision, recall, and F1-score, are specific to the trained model included in the Docker image.

Development

For those interested in contributing or further developing the project:

  1. Clone the repository:

    git clone https://github.com/pouryare/Covid-19-detection.git

  2. Install the required dependencies (consider using a virtual environment):

    pip install -r requirements.txt

  3. Make your changes and test locally:

    python app.py

  4. Build a new Docker image if necessary:

    docker build -t your-username/covid-detection-app:latest .

Contributing

Contributions to this project are welcome! Please fork the repository from https://github.com/pouryare/covid-detection and submit a pull request with your proposed changes.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

  • Dataset source: [Add the source of your dataset here]
  • Inspired by various COVID-19 detection projects in the medical imaging domain

Troubleshooting

If you encounter any issues while running the Docker container or using the web application, please check the following:

  1. Ensure Docker is properly installed and running on your system.

  2. Check if port 5000 is available on your machine. If not, you can map to a different port:

    docker run -d -p 8080:5000 --name covid-app pouryare/covid-detection-app:latest

    Then access the application at http://localhost:8080.

  3. If you're having trouble with image uploads, ensure you're using PNG format images.

For any other issues, please open an issue on the GitHub repository.