BrainTumorSegmentationUsingOpenCV

This repository implements a Convolutional Neural Network (CNN) to analyze MRI scans and determine whether a brain tumor is present. The project is designed to function as a backend system, providing the necessary infrastructure to train and deploy the model.

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Setup Instructions

Prerequisites

• Python 3.x installed on your system
• A stable internet connection to download the dataset and dependencies

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Steps to Set Up the Project

1. Clone the repository:

   git clone https://github.com/Cleveridiot07/BrainTumorClassificationUsingOpenCV
   cd BrainTumorClassificationUsingOpenCV

2. Initialize a virtual environment:

   python -m venv venv

3. Activate the virtual environment:

   • On Windows:

     .\venv\Scripts\activate

   • On macOS/Linux:

     source venv/bin/activate

4. Install dependencies:

   pip install -r requirements.txt

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Dataset

1. Download the dataset:

   • Brain Tumor Classification Dataset

2. Unzip the dataset:

   • After downloading, unzip the dataset:
     • On Windows: Right-click the file and select Extract All....
     • On macOS/Linux: Use the command:

       unzip datasets.zip

3. Place the dataset:

   • After unzipping, place the dataset in the following directory structure:

     backend/
     ├── model/
     │   ├── maintrain.py
     │   └── <dataset-folder>
     

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Train the Model

1. Navigate to the model/ directory:

   cd model

2. Run the training script:

   python maintrain.py

3. After training, the .h5 file for the model will be generated automatically in the model/ directory.

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Running the Project

1. Return to the backend directory:

   cd ..

2. Start the backend:

   uvicorn main:app --reload

   • This will run the backend at http://127.0.0.1:8000.
   • You can proceed to http://127.0.0.1:8000/docs to test the app using the interactive API documentation provided by Swagger UI.
   • Press CTRL+C to stop the server.

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Contribution

Feel free to fork the repository, create a branch, and submit a pull request to contribute to the project.