Team Name: GroupTwo
Team: Shubham Bisht
Shadrak Gurupnor
Mukund Choudhary
Key Information Extraction from Scanned Receipts: The aim of this task is to extract texts of a number of key fields from given receipts, and save the texts for each receipt image in a json
file.
Step 1: Extracting all the text from given Invoice Image. (Text Region Detection, OCR)
Step 2: Recognising Key information from the text like Store Name, Address, Total Amount etc using Bi-directional LSTM based approach
This repository contains three directories. Inside each folder there are documentations of the method we adopted and guide of usage.
- Folder 1 - Bill Label Tool: A GUI tool for efficiently labelling various entities in huge dataset of invoice images.
- Folder 2 - ML: Bi-LSTM Approach for Character-wise classification of invoice text into key entities.
- Folder 3 - Web UI: A user interface for uploading Invoices and receiving results in a HTML form
- Folder 4 - Android UI: Android interface for uploading Invoices, receiving results and to watch previous Bill uploads. Find the Android Repo here
- Task 1 - Scanned Receipt OCR: Tesseract OCR
- Task 2 - Key Information Extraction: Character-wise classification with Bi-LSTM
For the information extraction task, each image in the dataset is annotated with a text file with format shown below:
{
"company": "STARBUCKS STORE #10208",
"address": "11302 EUCLID AVENUE, CLEVELAND, OH (216) 229-0749",
"date": "14/03/2015",
"invoice id":"5628391",
"total": "4.95",
"items": "WhiteMochaV"
}