X-ray Image Classification: COVID-19, Pneumonia, and Normal Chest X-rays

Introduction

This repository contains a deep learning model developed by Prakhar Biswas to classify chest X-ray images into three categories: COVID-19, Pneumonia, and Normal. The model aims to assist healthcare professionals by providing an automated and accurate method to differentiate between these conditions using X-ray images.

Features

• Multi-class Classification: Classifies X-ray images into COVID-19, Pneumonia, and Normal categories.
• Pre-trained Model: Utilizes a pre-trained Convolutional Neural Network (CNN) for transfer learning to achieve high accuracy.
• Easy to Use: Simple interface for running predictions on new X-ray images.
• Data Augmentation: Includes data augmentation techniques to enhance model robustness.

Requirements

To run the project, you need to have the following dependencies installed:

• Python 3.8+
• TensorFlow 2.4+
• Keras
• NumPy
• Pandas
• Matplotlib
• Scikit-learn
• OpenCV
• ydata-profiling

You can install the required packages using pip:

pip install tensorflow keras numpy pandas matplotlib scikit-learn opencv-python ydata-profiling

Dataset The dataset used for training and testing the model comprises chest X-ray images labeled as COVID-19, Pneumonia, and Normal. You can download the dataset from Kaggle or other relevant sources Usage Clone the Repository:

git clone https://github.com/BAntu10/Detection-of-covid-xray.git
cd xray-classification

You can train the model by running the train.py script:

Results The model achieves high accuracy on the test set, with detailed performance metrics available in the results directory.

Contributing Contributions are welcome! If you have any suggestions, bug reports, or feature requests, feel free to open an issue or submit a pull request.

License This project is licensed under the MIT License. See the LICENSE file for more details.

Acknowledgements Kaggle for providing the dataset. TensorFlow and Keras teams for their powerful deep learning libraries. Contact For any questions or inquiries, please contact Prakhar Biswas at prakhar@example.com.

This README.md provides a comprehensive overview of the repository, including installation inst