COVID-19 and Pneumonia X-Ray Detector

Project Overview

This project implements a deep learning model to detect and differentiate between COVID-19, viral pneumonia, bacterial pneumonia, and normal conditions using chest X-ray images. The model serves as a diagnostic aid tool for medical professionals.

Dataset Information

The dataset is a custom compilation containing balanced classes with 133 images each:

• COVID-19 X-ray images (Class 0)
• Normal X-ray images (Class 1)
• Viral Pneumonia X-ray images (Class 2)
• Bacterial Pneumonia X-ray images (Class 3)

Data Sources

The dataset was created using images from:

1. COVID-19 Chest X-ray Dataset
2. Chest X-Ray Pneumonia Dataset

Requirements

• Python 3.7+
• TensorFlow
• NumPy
• Pandas
• Matplotlib
• scikit-learn

Model Architecture

• The model uses a convolutional neural network (CNN) architecture
• Input: X-ray images (preprocessed and standardized)
• Output: 4-class classification (COVID-19, Normal, Viral Pneumonia, Bacterial Pneumonia)

Performance Metrics

• Confusion Matrix