Welcome to the official blog for my GSoC’2022 project under Mifos Initiative. I am working on the project Computer Vision Based PPI Tool Version 3.0 under my mentors Nayan Ambali and Ed Cable. The project aims at extending the application by adding new features and refining it to achieve the original vision of an AI-based PPI Tool.

Executive Summary

The Poverty Probability Index (PPI) is a poverty measurement tool for organizations and businesses with a mission to serve the poor. A PPI survey consists of 10 questions about a household’s characteristics using which asset ownership is scored to compute the likelihood that the household is living below the poverty line.

Leveraging Cloud Vision, a field officer would simply have to take a series of photos with their smartphone camera inside and outside of the house, and then the Cloud Vision would be able to deduce based on the images the response to the 10 questions by detecting whether the objects mentioned in the survey are present in the household or not.

Testing

Preview link to the application

https://appetize.io/app/cqkjoygzdyyyr6fqdfzt44egfy?device=pixel4&osVersion=11.0&scale=75

Using the above link, the app can be tested on a browser itself without installing it on a physical device.

Codebase -

https://github.com/openMF/ppi-vision

Posts

Meeting Notes

Workflow

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