Convolutional Neural Network to Classify Chest Pneumonia X-Ray Images

This repository contains the source code for Classifying Chest Pneumonia X-Ray Images using a Convolutional Neural Network. The model architecture used in this project has been inspired by the work of Madaan, Vishnu et al.

This file contains the necessary information about the project environment and the steps required to run the project.

Preliminaries

The required packages needed to run the project can be found in the requirements.txt file. A better workaround, however, would be firing up a Google Colab Notebook and setting up the environment.

Environment Setup

• Sign up or log on to https://www.kaggle.com/ with your account. Click on My Account. Scroll down to API section. Click on Expire API Token. Click on Create New API Token. This step is necessary in order to generate an access token to connect to your Kaggle account via the Kaggle API.
• Download the .json file to your local directory.
• Download the chest_x_ray_pneumonia_classification.ipynb from this repository to your local directory.
• Open Google Colab and upload the chest_x_ray_pneumonia_classification.ipynb to the Colab Notebook.
• Run the entire script and where prompted, upload the .json file downloaded earlier to your Colab environment. This is necessary to link the Kaggle API with the Colab environment so that datasets can be downloaded directly to Colab.
• Please feel free to download the dataset from https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia to get a feel for the data and view the images in the train, test and val sub-directories.

Note: This repository is part of this blog post