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Inspiration
The goal of unClutter is to create more readable math documents. The team noticed that messy handwriting can lead to points being lost on tests, and they wanted to find a solution to this problem.
What it does
unClutter is a tool that helps improve the readability of math documents. It takes a picture of a math document and converts it into a well-formatted LaTeX document, which can be downloaded. The tool also includes a spellchecker to fix any spelling mistakes.
How we built it
To build unClutter, the team used OpenCV to extract math equations and text from uploaded documents. The team also used Azure's Bing Spell Check API to correct any typos before generating a PDF. The PDF is uploaded to Azure blob storage and a preview image is also created and stored in Azure. The front-end and user interface were built using React.
Challenges we ran into
The team had limited experience with OpenCV and struggled to properly extract math equations line by line in a way that humans could identify them. They also initially planned to create a mobile app, but had to pivot to a web app to reach a larger audience.
Accomplishments we're proud of
Some of the accomplishments the team is proud of include creating a web application with OpenCV, designing a clean user interface, and working on a machine learning problem related to sentence simplification. They also successfully implemented real-time text analysis and deployed a complex back-end pipeline using Azure.
What we learned
Through the process of building unClutter, the team learned how to use OpenCV to extract features from documents, and how to configure and use various offerings from Azure.
What's next for unClutter
In the future, the team plans to improve the accuracy of equation recognition, add support for multiple languages, verify the equity of math equations in images, and increase the efficiency of the processing pipeline. They also hope to find and investigate sources or websites with similar concepts to those in the document.
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