VGG19 to diagnose COVID-19 in X-Rayimages

VGG19 Architecture

So in simple language VGG is a deep CNN used to classify images. The layers in VGG19 model are as follows:

Conv3x3 (64)
Conv3x3 (64)
MaxPool
Conv3x3 (128)
Conv3x3 (128)
MaxPool
Conv3x3 (256)
Conv3x3 (256)
Conv3x3 (256)
Conv3x3 (256)
MaxPool
Conv3x3 (512)
Conv3x3 (512)
Conv3x3 (512)
Conv3x3 (512)
MaxPool
Conv3x3 (512)
Conv3x3 (512)
Conv3x3 (512)
Conv3x3 (512)
MaxPool
Fully Connected (4096)
Fully Connected (4096)
Fully Connected (1000)
SoftMax

Dataset Link

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

What things you need to install the software and how to install them

pip install --upgrade tensorflow
pip install --upgrade numpy

Installation

First clone the repository

git clone https://github.com/madscientistCS/VGG19-to-diagnose-COVID-19-in-X-Ray-images.git

run train

cd .\src\CNN\vgg19.py\
python .\vgg19.py

predict run train

python .\predict.py

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

License MIT