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Receipt Scanning using OCR and NLP, 2019 HackMIT FinTech Track Winner

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Project Horus - HackMIT 2019

Recognition

Awarded the 2019 HackMIT FinTech Track Award and the 2019 HackMIT Instabase Sponsor Award

Overview

Project Horus is an application that reads paper and digital receipts with OCR to better inform customers with their purchase decision making. Using a combination of machine learning algorithms, Project Horus scans, parses, augments, and analyzes purchases from receipts. Currently, we run analytics on grocery receipt to inform customers on the healthiness and unhealthiness of their food selections based on statistics from a nutritional facts database. In addition to serving as a personal finance tool, we are donating a percentage of the total value of healthy purchases in a month to a hunger-related charity. In the future, we plan to expand our technology to analyze receipts from other industries, including clothing, technology, wellness, education, and business applications.

Built with:

  • Python
  • HTML/CSS
  • Pandas
  • Numpy
  • AWS (Textract)
  • Instabase

Team Members

  • Adit Gupta - Yale University
  • Abhijit Gupta - Yale University
  • Mason Mitchell - WPI

Website

Please visit https://avgupta456.github.io/HackMIT-2019/ for more information about our project

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Receipt Scanning using OCR and NLP, 2019 HackMIT FinTech Track Winner

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