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README.md

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Pneumonia-Classification

This is a Python3 (TensorFlow) implementation of Pneumonia Detection using chest X-ray image.

The Dataset

The dataset comprises 5,863 frontal-view chest X-ray images organized into three folders - train, test, val. The folders are divided into sub-folders for each image category - Pneumonia and Normal. The dataset is available on the Kaggle platform.

Acknowledgements

Prerequisites

  • Python 3.8+
  • TensorFlow 2.5+
  • All the specified requirements in the text file

Usage

  1. Clone this repository.
  2. Install requirements.txt using pip install -r requirements.txt.
  3. Use DVC to pull the files that are stored on the DAGsHub remote storage by running dvc pull
  4. Modify the code as you wish.
  5. Run dvc repro to run the pipeline and train the model.

Note: If you are adding/removing/moving files to different directories, it can affect the DVC pipeline, and therefore the dvc repro command might not run properly.

Tip!

Press p or to see the previous file or, n or to see the next file

About

⚡ Keras reimplementation of CheXNet: pathology classification from chest X-Ray images 💼

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