[SOUND]. In the previous video, you understood the Native method, in this video you will understand the OCR or optical character recognition method. Although both full text and native have excellent results in terms of accuracy and speed, there are specific cases in which both are unusable. For example, the OCR output method, should be used if you need to extract information from virtual environments or ,read, text from images. It is based on the OCR technology used in the recognition of scanned documents. It attempts to recognize each letter of the text given on an image in the target document. It is slow when compared to the other methods, has lower accuracy and cannot extract hidden text and cannot work in the background. The OCR method has three default engines, which are Tesseract OCR, Microsoft OCR and UiPath Screen OCR. The use of these engines depends on the type of information being extracted, in general it's better to switch between the methods to see which engines bring better results for each situation. If you have downloaded and installed the packages of other OCR engines, they will also be available while choosing the OCR engine. Let's understand each of these engines in detail. The first engine is Tesseract OCR. This engine gets better results for character recognition on smaller size areas and supports color inversion. It offers multiple customization options through filters that can be used to select only specific categories of characters. This method offers five options, the first option is languages, this is English by default. The second option is characters, it enables you to select which types of characters are to be extracted. The following options are available, any character, numbers only, letters, uppercase, lowercase, phone numbers, currency, date and custom. When custom selected, two additional fields, Allowed and Denied, are displayed, that enable you to create custom rules on which types of characters to scrape and which to avoid. The third option is scale, the scaling factor of the selected UI element or image, the higher the number is the more enlarged the images. This can provide a better OCR rate and is recommended for small images. The fourth option is invert, when this checkbox is selected, the colors of the UI elements are inverted before scraping, this is useful when the background is darker than the text color. The fifth option is Get Words Info, It helps in getting the onscreen position of each scraped work. The second engine is Microsoft OCR, this engine is used to work with Microsoft fonts and on larger size image, it supports multiple languages. This engine offers three options, the first option is languages, it enables you to change the language of the scraped text, by default English is selected. The second option is scale, the scaling factor of the selected UI element or image, the higher the number is the more enlarged the image is. This can provide a better OCR read and is recommended for small images. The third option is Get Words Info, it gets the onscreen position of each scraped word. The third engine is UiPath Screen OCR, this engine can be used in any UI automation scenario in which an OCR engine is needed. This engine offers three options, the first option is Endpoint, here the end point of UiPath Screen OCR is entered. The second option is API Key, the API Key is used to provide you access to the UiPath Screen OCR, it is not required for the preview period. The third option is Get Words Info, it gets the onscreen position of each scraped word. The next video will show a demonstration where in text has been scraped from a UiPath blog post using the screen scraper wizard and stored in a notepad file. I would encourage you to go through the demonstration and attempt to repeat it on your own. So that's it for this video, thank you for watching.
