Child Growth Monitor Machine Learning

Child Growth Monitor (CGM) is a game-changing app to detect malnutrition. If you have questions about the project, reach out to [email protected].

This is the Machine Learnine repository associated with the CGM project.

Introduction

This project uses machine learning to identify malnutrition from 3D scans of children under 5 years of age. This one-minute video explains.

Getting started

Requirements

Our development environment is Microsoft Azure ML

You will need:

• Python 3
• TensorFlow version 2
• other libraries

To install, run:

pip install -r requirements.txt

For installing point cloud libraries, refer to README_installation_details_pcl.md.

Dataset access

If you have access to scan data, you can use: src/data_utils to understand and visualize the data.

Data access is provided on as-needed basis following signature of the Welthungerhilfe Data Privacy & Commitment to Maintain Data Secrecy Agreement. If you need data access (e.g. to train your machine learning models), please contact Markus Matiaschek for details.

Contributing

Please see CONTRIBUTING.md for details.

Versioning

Our releases use semantic versioning. You can find a chronologically ordered list of notable changes in CHANGELOG.md.

License

This project is licensed under the GNU General Public License v3.0. See LICENSE for details and refer to NOTICE for additional licensing notes and use of third-party components.