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#Commercial grade ocr for mac how to
#Commercial grade ocr for mac pdf
#Commercial grade ocr for mac software
#Commercial grade ocr for mac license

ALTO XML Documentation - Documentation and use cases for ALTO.

ALTO XML Schema - XML Schema and development of the ALTO XML format.

hOCRTools - hOCR to ALTO conversion XSLT.

hocr-parser - hOCR Specification Python Parser.

ocr-transform - CLI tool to convert between hOCR and ALTO, MIT.

hocr-tools - Tools for doing various useful things with hOCR files, Apache 2.0.

hebOCR - Hebrew character recognition library (previously named hocr, see Wikipedia article) GPL.

xplab - A GTK 2 tool for pattern matching.

#Commercial grade ocr for mac software

OCRchie - Modular Optical Character Recognition Software.

kognition - An omnifont OCR software for KDE.

Eye - an experimental Java OCR (image-to-text) application.

Cuneiform - CuneiForm OCR was developed by Cognitive Technologies.

doctr - A seamless & high-performing OCR library powered by Deep Learning.

Calamari - OCR Engine based on OCRopy and Kraken.

simple-ocr-opencv and its fork - A simple pythonic OCR engine using opencv and numpy.

RWTH-OCR - The RWTH Aachen University Optical Character Recognition System.

attention-ocr - OCR engine using visual attention mechanisms.

SwiftOCR - fast and simple OCR library written in Swift.

ocular - Machine-learning OCR for historic documents.

#Commercial grade ocr for mac license

gocr - OCR engine under the GNU Public License led by Joerg Schulenburg.

kraken - Ocropus fork with sane defaults.

ocropus 0.4 - Older v0.4 state of Ocropus, with tesseract 2.04 and iulib, C++.

ocropus - OCR engine based on LSTM, Apache 2.0.

EasyOCR - OCR engine built on PyTorch by JaidedAI, Apache 2.0.

tesseract - The definitive Open Source OCR engine Apache 2.0.

Older and possibly abandoned OCR engines.

If you don’t select image area, text on the image will also be OCRed, but the image will be missing in the output document.This list contains links to great software tools and libraries and literatureĬontributions are welcome, as is feedback. By doing this, you can keep the original layouts better. The selected area will be preserved as an image in converted Word document and the app will not perform OCR for the select areas. You can remove single selected areas, or all the selected areas in this document.

#Commercial grade ocr for mac pdf

(3) To remove a selected area, simply select and press ‘Delete’ button on your keyboard, or move your mouse cursor to the left top of the built-in PDF reader, you’ll see ‘remove’ buttons appear.

(2) To move or adjust the area, click on it and drag the area border to the desired location. (1) To select image areas, move your mouse cursor to the built-in reader, hold left-click and drag to select an area. Rotate operation only affects the current page.Įxtracting text is the main purpose of performing OCR, if the scanned PDF contains images elements, you need to select them prior to the conversion for better formatting preservation and accuracy. Move your mouse cursor to the left top of the built-in PDF reader, you’ll see rotate buttons appear. Incorrect orientation of the document will result in poor conversion quality.

Or the text will be stuck together and OCR is hard to recognize those text.ģ. Poor document images quality and the skewed document may not be converted accurately.Īnd the image in PDF document should be at least 300 dpi, and 600 dpi is recommended for document with smaller fonts. The quality of conversion depends on the quality of the original PDF. The application supports 10 languages, including English, French, German, Italian, Spanish, Portuguese, Polish, Swedish, Russian and Dutch. This is an extremely important step to get accurate text recognition result.įor example, if your PDF is in French but you choose English as OCR languages, the non-English character like ‘ é à ‘ will not be recognized correctly. You need to select the appropriate document language prior to OCR conversion. Tips for improving the quality of OCR conversion: 1.

#Commercial grade ocr for mac how to

This tutorial will show you how to improve OCR Conversion Quality using PDF to Word OCR. One study based on recognition of 19th- and early 20th-century newspaper pages concluded that character-by-character OCR accuracy for commercial OCR software varied from 71% to 98%. OCR (Optical Character Recognition) is not an easy task, both the quality of the source PDF and OCR option affect the quality and accuracy of the output file.