Sometimes you need to get a text written inside a GUI control or find a place on the screen that contains a given text. It is not always possible to solve this task using objects natively supported by Rapise or Simulated Objects. In this case the Optical Character Recognition (OCR) functionality may help.
Optical character recognition (OCR) is the conversion of images containing text into actual editable text. Often during testing you need to be able to dynamically parse the text from a graphic on the screen so that you can determine if an action passed correctly.
For example, many applications are using the CAPTCHA image system for preventing automated spam posts to applications. If you need to test such an application, the ability to respond correctly to the CAPTCHA is critical.
Rapise can be integrated with a number of OCR engines, including Tesseract and Windows, and provides a special OCR Global Object to make the task of extracting text straightforward.
There are benefits to each of the two supported engines:
Benefits:
Benefits:
So, in summary, if you are looking at the two options:
The OCR Global Object makes it easy to use the OCR capabilities in either a RVL codeless test:
Or in a similar, JavaScript based scripted test:
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