There are 9 repositories under ocr-engine topic.
Tesseract Open Source OCR Engine (main repository)
A super lightweight image processing algorithm for detection and extraction of overlapped handwritten signatures on scanned documents using OpenCV and scikit-image.
multi-task learning for text recognition with joint CTC-attention
⭐️ The native node.js bindings to the Tesseract OCR project.
Android app to extract name, email and phone from business card using OCR library tess-two (Fork of Tesseract Tools for Android) and phone's camera.
A simple Julia wrapper for Tesseract OCR
Engine for Optical Character Recognition to scan Business Cards locally on Android devices.
PyraDox is a python tool which helps in document digitization by extracting text information and masking of personal information with the help of Tesseract-ocr.
Tesseract OCR implementation in React JS
Staff Identity Card OCR Project
An OCR engine that works by finding pre-known letters in a word's image
Undergraduate Final Project
Streamlit based web frontend for PyraDox
Java Tesseract 3.4.4 Example
JPEG to PDF conversion using tesseract v4 through cmd. Includes OCR'ing the JPEG's and combining multi-page PDF to one.
Tesseract on few examples, such as template matching for different languages (AZE)
Vision AI service ( REST API ) for OCR ( optical character recognition ) 📷
Hello, this is Brix OCR, an open-source project where we try to build an OCR engine with the help of others as well as make a custom model.
Engine using the https://ocr.space API.
A basic ocr pipeline code written in tensorflow for CPU on EMNIST dataset
How to integrate Vidado Read OCR into Kofax Transformation's Advanced Zone Locator
PresentID Optical character recognition API can extract data from all types of cards including driver's license, National ID card, Certificate, etc.
Expense Tracker Application With MachineLearning and Optical Character Recognition
.NET OCR Engine based on Tesseract 4
This Flask application empowers users to seamlessly upload image files like invoices or receipts, extract text using robust OCR technologies, and efficiently isolate key fields using precise regular expressions and multiprocessing to streamline data extraction and enhance productivity.