#Japanese ocr ios download#

To implement an optical character recognition (OCR) function

Or there is a logo and underlined, '' : - or there is a symbol, such as вЂ», I have been charged trap such or not shift character of the line is slightly wavy paper and look good. This time try in the next image (sample.png). Prepare the target image file, leave is taken to the Xcode project. You are now ready to use the Japanese learning data above. It is OK if there is jpn.traineddata under the tessdata folder that is displayed in light blue icon.Option is selected in the following manner.Drag the tessdata folder to the Xcode project.

#Japanese ocr ios download#

Download the jpn.traineddata to tessdata folder that has been created in advance.tessdata_fast access to the repository, jpn.traineddata click.You have to create a folder under the name tessdata on your computer.tessdata (a combination of pattern recognition and LSTM?, compatibility emphasis?)ДЄccording to the commentary of SwiftyTesseract, because the best option in most cases is written, it will be tessdata_fast, this time makes use of the Japanese learning data of tessdata_fast.tessdata_best (LSTM, accurate-oriented).To the learning data for Tesseract, the following three types are available. In SwiftyTesseract, Tesseract 1 can be used as it is a learning data that has been prepared in advance for. To add a learning data to the Xcode project We have completed the introduction of SwiftyTesseract above.ДЄnd later we will promote the development of open a file called 'Project Name. Remarks of SwiftyTesseract, because CocoaPods and Carthage both deployment methods have been introduced, please be introduced in any way you like.Д«y the way this time, try to introduce the SwiftyTesseract using CocoaPods.ДЇirst, open the Podfile add the following line. The introduction of SwiftyTesseract to Xcode projectД¬ocoaPods or, introduces a SwiftyTesseract in Carthage. In accordance with the Swift version of SwiftyTesseract, select the Swift 4.2.

Д®nvironment used in this article are as follows.ДЇirst, the Xcode project to create a new, and change the Swift Language Version at Build Settings. Deep learning does not dig deep because not familiar with, and say this in what is happy, compared with the Tesseract OCR iOS and SwiftOCR, is that to some extent the speed and Japanese OCR that combines the accuracy can be easily achieved. The biggest feature of SwiftyTesseract is, LSTM neural network-based OCR engine is added to the latest stable version Tesseract is that wrapping 4. So, I decided to try out SwiftyTesseract. So are you personally attention SwiftyTesseract is. However, challenges with respect to Japanese recognize that many, have received practical use that are not facing impression. In the course of the previous survey, Tesseract OCR iOS and SwiftOCR two, but we found that it's also popular as viewed from the Stars of GitHub. Of open source OCR library survey is a continuation of.