Using an OCR Engine for Your AI Projects
OCR makes it possible to obtain translation of photos with printed text into machine-encoded text. Python allows you to do it by utilizing Tesseract, an OCR engine with an open source code.
Have you ever dealt with a scanned document and wished there was some way for your computer to read the text and process it for you without having to type everything? The good news is that there is a way, and this solution is called Optical Character Recognition or OCR.
OCR refers to the electronic and mechanical translation of photos with printed text into machine-encoded text. Whether it is from a scanned text file, a picture of a handwritten letter, a signage with some text, or an image with superimposed text like a screenshot of a TV show with subtitles, the text can be converted through OCR.
OCR consists mainly of certain sub-processes to convert text images as accurately as possible. These include pre-processing, text detection, text recognition, and post-processing. These can vary according to the specific case, but these are generally the steps involved in the overall OCR process.
Implementing OCR Python
If OCR is something you need access to, especially for an AI project, you'll be happy to know that there is an open source OCR solution you could use. Tesseract is an OCR engine with an open source code. You can implement OCR in Python utilizing Tesseract.
Tesseract supports unicode and can recognize over 100 languages. It can also be trained to understand text in other languages that are not already included in its established list. You can use Tesseract for text detection on smartphones and other mobile devices, as well as in video.
You can use Tesseract in conjunction with an external text recognition software to recognize a single text line from a photo or you can use it with an existing layout analysis to recognize the text contained in a large document.
Tesseract is also compatible with a variety of programming languages and frameworks. You can use it directly or with an API to extract a printed text from an image.
Tesseract works by finding templates in letters, words, sentences, and even in pixels. It uses a two-stage approach.
- First is character recognition, requiring one data storage.
- Second involves filling in undetectable letters by analyzing the context of words and sentences.
Pytesseract, a wrapper for Google’s Tesseract-OCR, can be used as standalone invocation script to tesseract since it can read jpeg, gif, png, tiff, bmp, and other image types that are supported by the Leptonica and Pillow imaging libraries. Also, if you use Pytesseract as a script, it won’t write a recognized text to a file but will instead print it.
While installing Tesseract on Windows and applying it for a particular AI project may be simple and easy for developers and IT professionals, it can be too technical for most other users who also need OCR solutions. This is not an app that you merely download, install, and run on your device or on your program. To begin, you will need to incorporate a few commands to install it. Importantly, you will also need precompiled binaries.
Needless to say, Tesseract is one of the most effective and powerful OCR engines to add text recognition capabilities to a project. But like most open source solutions, it doesn’t come without limitations.
These limitations include:
- It is not equally accurate compared to commercial OCR solutions.
- It cannot work with images whose text is affected by distorted perspective, distorted background, or partial occlusion.
- It cannot recognize handwriting.
- It may produce poor-quality OCR for poor-quality scans.
- It may fail to analyze the reading order of a document, like those having two columns.
Use Tesseract Without the Hassle
Tesseract has gained popularity among OCR developers, especially since there hasn't been a lot of powerful and free OCR alternatives available for the longest time. The problem with Tesseract, however, is that it can be a hassle to implement and to modify.
The PurpleDye Marketplace gives you a solution to this dilemma by allowing you to add Tesseract to your AI project in just a simple click. PurpleDye has made it a no-fuss, hassle-free, ready-to-use OCR solution for you.
With this option, you can now integrate text recognition capabilities to your app or AI projects minus the headaches. You can instead focus on other aspects of your venture.