This is a Machine Learning project that aims to detect COVID-19 from X-ray images. The goal is to build a classification model that can distinguish between healthy X-rays and those that show signs of COVID-19 infection. The model uses Convolutional Neural Networks (CNN) and VGG16 model to extract features from the images and classify them into their respective categories.
The dataset used in this project is taken from Kaggle's Chest X-Ray Images (Pneumonia) dataset, which contains X-ray images of COVID-19 patients as well as healthy individuals. Chest X-ray images (anterior-posterior) were selected from retrospective cohorts of pediatric patients of one to five years old from Guangzhou Women and Children’s Medical Center, Guangzhou. All chest X-ray imaging was performed as part of patients’ routine clinical care.
This project requires the following dependencies:
- Python 3.x
- TensorFlow 2.x
- Keras
- NumPy
- Matplotlib
- Pandas
You can install these dependencies using pip.
pip install tensorflow keras numpy matplotlib pandas
To train the model, run the training.py script. The trained model will be saved in the model directory.
python training.py
To test the model on a single X-ray image, run the main.py script.
python predict.py path/to/image
The model achieves an accuracy of 98.05% on the test set. The plots and a sample test report can be found in the results directory.
- Improve the accuracy of the model by fine-tuning the hyperparameters and using a larger dataset.
- Develop a web application for easy access to the model for healthcare professionals.
- Explore the use of other deep learning architectures for this task.