Evaluate OMR sheets fast and accurately using a scanner 🖨 or your phone 🤳.
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Updated
May 22, 2024 - Python
Evaluate OMR sheets fast and accurately using a scanner 🖨 or your phone 🤳.
Open Source Document Management System for Digital Archives (Scanned Documents)
A super lightweight image processing algorithm for detection and extraction of overlapped handwritten signatures on scanned documents using OpenCV and scikit-image.
ScanTailor Advanced is the version that merges the features of the ScanTailor Featured and ScanTailor Enhanced versions, brings new ones and fixes.
📷 Computer-Vision Demos
In this repository is the source code of Papermerge DMS backend core, REST API server, and frontend UI
A curated list of awesome projects to simplify and improve paper and document scanning.
The first-ever paper on the Unix shell written by Ken Thompson in 1976 scanned, transcribed, and redistributed with permission
BoxDetect is a Python package based on OpenCV which allows you to easily detect rectangular shapes like character or checkbox boxes on scanned forms.
Dedoc is a library (service) for automate documents parsing and bringing to a uniform format. It automatically extracts content, logical structure, tables, and meta information from textual electronic documents. (Parse document; Document content extraction; Logical structure extraction; PDF parser; Scanned document parser; DOCX parser; HTML parser
Emacs-assisted PDF document filing
ICDAR 2019 Robust Reading Challenge on Scanned Receipts OCR and Information Extraction
Small utility to prepare scanned documents. Supports separating PDF files by separator pages and removing blank pages.
A document scanner that automatically trims the edge with perspective transform
A tool for extracting text from scanned documents (via OCR), with user-defined post-processing.
Android Scanner with OCR support using PDFTron
Make your PDFs look like they were scanned
Segmentation of Scanned Text upto Character Level
Documentation for Papermerge DMS - Installation, Help, User Manual, REST API
The project creates the models and service API for predicting scanned document images' angles ranging between -90° to 90° from the vertical.
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