$ sudo apt-get install tk8.5 tcl8.5 tk8.5-dev tcl8.5-dev $ sudo apt-get install libopencv-dev libtesseract-dev $ sudo apt-get install autoconf automake libtool If you’re running OSX, you can use VirtualBox, Docker (check out the Dockerfile along with an install guide are included) or a droplet on DigitalOcean (recommended!) to create the appropriate environment. This post has been tested on Ubuntu version 14.04 but it should work for 12.x and 13.x versions as well. As always, configuring your environment is 90% of the fun. This will not be covered by the tutorial, but you will have access to the code.įirst, we have to install some dependencies. We’ll also add a bit of back-end code to generate an HTML form as well as the front-end code to consume the API. All of this is covered in detail by the tutorial. From there you can just hit the endpoint and serve the results to the end user in the manner that suits you.
We’ll start by developing the Flask back-end layer to serve the results of the OCR engine. A trivial example is a basic OCR tool used to extract text from screenshots so you don’t have to re-type the text later on.
With the advent of libraries such as Tesseract and Ocrad, more and more developers are building libraries and bots that use OCR in novel, interesting ways. OCR (Optical Character Recognition) has become a common Python tool. The following is a collaboration piece between Bobby Grayson, a software developer at Ahalogy, and Real Python.
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