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.
model.py
: Contains functions for image preprocessing and predictionapp.py
: Flask web application for serving predictionstemplates/index.html
: HTML template for the web interface
- 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
- Docker
-
Pull the Docker image:
docker pull pouryare/covid-detection-app:latest
-
Run the Docker container:
docker run -d -p 5000:5000 --name covid-app pouryare/covid-detection-app:latest
-
Open a web browser and go to
http://localhost:5000
to use the prediction interface.
- Click on "Choose File" to select a chest X-ray image (PNG format only).
- Click "Upload and Analyze" to process the image.
- The result will be displayed, indicating whether COVID-19 is detected or not.
The project uses a Convolutional Neural Network (CNN) for COVID-19 detection. The exact architecture details are encapsulated within the Docker image.
The model's performance metrics, such as accuracy, precision, recall, and F1-score, are specific to the trained model included in the Docker image.
For those interested in contributing or further developing the project:
-
Clone the repository:
git clone https://github.com/pouryare/Covid-19-detection.git
-
Install the required dependencies (consider using a virtual environment):
pip install -r requirements.txt
-
Make your changes and test locally:
python app.py
-
Build a new Docker image if necessary:
docker build -t your-username/covid-detection-app:latest .
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.
This project is licensed under the MIT License - see the LICENSE file for details.
- Dataset source: [Add the source of your dataset here]
- Inspired by various COVID-19 detection projects in the medical imaging domain
If you encounter any issues while running the Docker container or using the web application, please check the following:
-
Ensure Docker is properly installed and running on your system.
-
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
. -
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.