Brain Tumor Detection

This repository implements a deep learning-based brain tumor detection system using Convolutional Neural Networks (CNNs). The project includes a Flask web application for real-time MRI image classification and a CI/CD pipeline for streamlined development, deployment, and reproducibility.

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Features

• CNN-based Detection: Accurate classification of brain tumor types from MRI images using deep learning models.
• Flask Application: User-friendly web interface for uploading MRI images and obtaining predictions in real-time.
• CI/CD Pipeline: Automated workflows leveraging Docker and DVC for efficient development and deployment processes.
• Modular Pipeline Structure: Components for data ingestion, preprocessing, training, evaluation, and deployment are organized for scalability and maintainability.

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Technologies Used

• Deep Learning Frameworks: TensorFlow/Keras
• Web Framework: Flask
• Pipeline Tools: DVC, Docker
• CI/CD: GitHub Actions
• Versioning: Git

Workflows

1. Update config.yaml
2. Update secrets.yaml [Optional]
3. Update params.yaml
4. Update the entity
5. Update the configuration manager in src config
6. Update the components
7. Update the pipeline
8. Update the main.py
9. Update the dvc.yaml