SMARTurinalysis

Smartphone-based Colorimetric Analysis of Urine Dipsticks for At-Home Prenatal Care

This project is aimed for an automatic detection and evaluation of urine dipsticks from images. Steps performed during the analysis:

• Detection of the stick: Feature matching & Mask R-CNN
• Detection of the reference card: Feature matching
• Localisation of the single test and reference fields
• Color analysis and comparison

The main scripts to perform the detection and colour evaluation can be found in the urinalysis folder. All scripts that support the main scripts can be found in the helper subfolder, scripts analyzing the calculated results in the evaluation subfolder. The used implementation of Mask R-CNN is in the mask-rcnn subfolder.

Prerequisites

Required python libraries can be found in requirements.txt

Getting Started

Authors

• Madeleine Flaucher - Initial work

Acknowledgments

• Matterport Inc. - Mask R-CNN implementation