This repository contains a convolutional neural network (CNN) model to detect COVID-19 from X-ray images. The model is built using TensorFlow and Keras and aims to help in the early detection of COVID-19 through chest X-rays.
- Data preprocessing
- CNN architecture for image classification
- Training and validation of the model
- Evaluation metrics to assess model performance
- Instructions for reproducing the results
The dataset used for this project is sourced from Kaggle's COVID-19 Radiography Database. This dataset contains chest X-ray images of patients diagnosed with COVID-19, Viral Pneumonia, and Normal cases.
- Total Images: The dataset consists of 15,000 X-ray images.
- Classes:
- COVID-19: 3616 images
- Viral Pneumonia: 1345 images
- Normal: 10192 images
The model was trained on the COVID-19 Radiography Database and achieved the following performance metrics:
- Validation Accuracy: 95.92%
- Training Accuracy: 97.08%
- Loss: 0.793