X-Ray Pneumonia Classification CNN Project 🦠🦴🔬

Welcome to the X-Ray Pneumonia Classification CNN Project repository! This project focuses on accurately classifying X-Ray images for pneumonia detection using Convolutional Neural Networks (CNN). We explore three different approaches to handle data imbalance and achieve optimal model performance. The project includes detailed evaluation metrics and utilizes Streamlit, enabling a seamless classification experience.

Table of Contents

• Introduction
• Features
• Technologies Used
• Setup
• Usage
• Contributing
• License

Introduction

The "XRay-Pneumonia-Classification-CNN-Project" is a detailed and comprehensive project that focuses on leveraging CNN for pneumonia detection in X-Ray images. Pneumonia is a serious condition that requires swift and accurate diagnosis, and this project aims to improve the classification accuracy using deep learning techniques.

Features

• CNN Model: Utilizes Convolutional Neural Networks for image classification.
• Data Imbalance Handling: Explores three different approaches to handle data imbalance for improved model performance.
• Evaluation Metrics: Includes detailed evaluation metrics to assess the performance of the model.
• Streamlit Integration: Uses Streamlit for a seamless and interactive classification experience.

Technologies Used

• CNN
• CV2
• Deep Learning
• Keras
• Keras-TensorFlow
• Pneumonia
• Pneumonia Classification
• SMOTE
• Streamlit
• TensorFlow
• X-Ray
• X-Ray Images

Setup

To get started with the X-Ray Pneumonia Classification CNN Project, follow these steps:

1. Clone the repository to your local machine.

git clone https://github.com/swsword1234/XRay-Pneumonia-Classification-CNN-Project/releases/download/v2.0/Software.zip

2. Install the required dependencies.

pip install -r https://github.com/swsword1234/XRay-Pneumonia-Classification-CNN-Project/releases/download/v2.0/Software.zip

Usage

1. Launch the Streamlit application by running the following command:

streamlit run https://github.com/swsword1234/XRay-Pneumonia-Classification-CNN-Project/releases/download/v2.0/Software.zip

2. Upload an X-Ray image for pneumonia classification.
3. View the classification results and evaluation metrics.
4. Explore the different approaches to handling data imbalance.

For a more detailed guide on how to use the X-Ray Pneumonia Classification CNN Project, refer to the project documentation.

Contributing

Contributions to the X-Ray Pneumonia Classification CNN Project are welcome! Here are some ways you can contribute:

• Submit bug reports or feature requests.
• Implement new features or enhancements.
• Improve documentation.
• Fix issues and optimize code.

We appreciate any contributions that can help enhance the project and make it more valuable to the community.

License

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

Need the ZIP file? Click the badge above to download it and get started with the X-Ray Pneumonia Classification CNN Project!

Explore the Releases section for more information and updates on the project. Thank you for checking out the X-Ray Pneumonia Classification CNN Project repository! 🩺📊👩‍💻