Urine Stripe Analyzer

This project is a web application that analyzes an image of a urine strip and returns the RGB values of each segment on the strip. It is built using Django, HTML, CSS, JavaScript, NumPy, and OpenCV.

Tech Stack and Methodology

Frontend

The Frontend is build with Vanilla Javascript and HTML and CSS with GoogleFonts

Backend

The Backend is built with the help of Django.

Methodology

The main methodology that has been used can be divided into 2 parts :-

1. Cropping - to get the useful part of the image.
2. PreProcessing - A billinear extrapolator is used to replace value of each pixel with the average value of the row to remove artifacts like granular noise and dark patches
3. Segmentation - small segments of 10x10 are used to get the average RGB value of each segment.

Installation

1. Clone this repository using

   git clone https://github.com/pnaskardev/urine_strip_analyser.git
   

2. Navigate to the project folder,install the required dependencies and start the webserver on port 8000

   cd urine_strip_analyser
   pip install virtualenv
   

3. create a virtual environment(For Windows OS users)

   python -m venv venv
   venv\Scripts\activate
   
   

4. create a virtual environment(For Linux/MacOS users)

   virtualenv venv
   source venv/bin/activate
   

5. Install all the dependencies

   pip install -r requirements.txt
   

6. Start the server

   python manage.py makemigrations
   python manage.py migrate
   python manage.py runserver
   

7. Navigate to for testing

   http://localhost:8000/analyse/
   

To run the Dockerized version

Clone the project

  git clone https://github.com/pnaskardev/urine_strip_analyser.git

Go to the project directory

  cd urine_strip_analyser

Start Docker

  docker-compose up

Navigate to the given link for testing

http://localhost:8000/analyse/

Screenshots

Authors

• @pnaskardev