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.
- Clone the repository:
git clone https://github.com/mikemwai/oncolyticnet.git - Navigate to the project directory:
cd oncolyticnet - Install the required packages:
pip install -r requirements.txt
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Run the following command to start the application:
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On Windows:
set FLASK_APP=app.py flask run -
On Unix/Linux/Mac:
export FLASK_APP=app.py flask run
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This will start a development server on http://127.0.0.1:5000/ where you can access the application.
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The dataset used for this project can be downloaded here or extract it from here.
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An additional dataset for image validation was downloaded from here.
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The image validation model and detection model can be downloaded from here.
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!
If you have any issues with the project, feel free to open up an issue.
This project is licensed under the MIT License - see the LICENSE file for details.