It supports English, Spanish, Thai all the way upto Tamil, Uzbec and Yiddish. Tesseract supports a whole slew of languages like no other framework. Most OCR frameworks out there is probably built on top of Tesseract and it is the most popular among the bunch which has pretty good outcomes.
In this document, we will be do a deep dive into the Tesseract framework and how to have it setup and how good or bad would the outcomes be. There were not many open source options for being able to build on your own. Tesseract is considered as one of the most accurate open-source OCR engines currently available. It was later developed and sponsored by Google since 2006. In 2005 Tesseract was open sourced by HP.
Tesseract is an optical character recognition engine for various operating systems.It is free software released under the Apache License, Version 2.0, and was originally developed at Hewlett-Packard Laboratories Bristol and at Hewlett-Packard Co, Greeley Colorado between 19, with some more changes made in 1996 to port to Windows, and some C++izing in 1998. It can read all image types supported by Pillow, including jpeg, png, gif, bmp, tiff, and others. PyOCR can be used as a wrapper for google’s Tesseract-OCR or Cuneiform. It may or may not work on Windows, MacOSX, etc. It should also work on similar systems (*BSD, etc). That is, it helps using OCR tools from a Python program.It has been tested only on GNU/Linux systems. PyOCR( ) is an optical character recognition (OCR) tool wrapper for python. Listed below are a couple of such frameworks. They are effective too as long as you know how to train it for your requirements.
There are a couple of open source frameworks that can be used to build an OCR framework in house. If your requirement is less than 25K request a month you can even get away for free. This SDK does a neat job of getting the needed information but not to the level of Rekognition and Vision APIs. OCR Space( ) is a more of a budget friendly option compared to the first 2 options. This is little less expensive than Vision API. This framework is really expensive unless your base set of images are a few.Īmazon Rekognition( ) is again an image processing framework just like the Google’s Vision API.This framework uses deep learning technology to identify objects, image and faces. If the intention is to just identify what characters are present in the image, this framework has a lot more to it.
Vision API is more of an image processing framework than just an optical character recognition framework. Google vision api( ) is one of the most popular API’s available and it gets you the most accurate information. There are many softwares/APIs available out there which could be do a pretty good job of processing an image and based on what they could do and how well they do the prices vary. There is a lot of pre-processing work involved before the most accurate information could be retrieved. In order to get it more closer to 100%, requires a lot of tuning and training. OCR has been gaining recent popularity and being able to identify what is present in the image opens up a new horizon of opportunities.įor the past few years OCR frameworks has evolved a lot but not to an extent where they could be 100% for any image size or any image quality. It converts these documents into machine coded text.
Optical Character Recognition, or OCR is a technology that enables you to convert different types of documents, such as scanned paper documents, PDF files or images captured by a digital camera into editable and searchable data.