mikemwai/oncolyticnet

An Automated Cancer Diagnostics Machine Learning model

Oncolyticnet

This project aims to develop a machine learning model for detecting brain tumors from MRI scans using the VGG-19 architecture with transfer learning and data augmentation techniques to fine-tune the pre-trained model, enabling accurate and reliable brain tumor detection.

Installation

1. Clone the repository:

   git clone https://github.com/mikemwai/oncolyticnet.git
   

2. Navigate to the project directory:

   cd oncolyticnet
   

3. Install the required packages:

   pip install -r requirements.txt
   

Usage

• Run the following command to start the application:

  • On Windows:

        set FLASK_APP=app.py
        flask run

  • On Unix/Linux/Mac:

        export FLASK_APP=app.py
        flask run

• This will start a development server on http://127.0.0.1:5000/ where you can access the application.

Dataset

• The dataset used for this project can be downloaded here or extract it from here.

• An additional dataset for image validation was downloaded from here.

• The image validation model and detection model can be downloaded from here.

Contributions

If you'd like to contribute to this project:

• Please fork the repository.
• Create a new branch for your changes.
• Submit a pull request.

Contributions, bug reports, and feature requests are welcome!

Issues

If you have any issues with the project, feel free to open up an issue.

License

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