LinX - AMD Edition. ※ LinX - AMD Edition은 전용 MKL이 포함되어 있습니다. (MKL을 추가 설치하지 말 것) LinX v0.6.5. 9600k 공랭으로 47배수 시도중인데 LinX 0.6.4 AVX 와 본문에 올려두신 링스와 무슨 차이가 있을까요?
In today’s post, we will learn how to recognize text in images using an open source tool called Tesseract and OpenCV. The method of extracting text from images is also called Optical Character Recognition ( OCR) or sometimes simply text recognition. Tesseract was developed as a proprietary software by Hewlett Packard Labs.
In 2005, it was open sourced by HP in collaboration with the University of Nevada, Las Vegas. Since 2006 it has been actively developed by Google and many open source contributors. Tesseract acquired maturity with version 3.x when it started supporting many image formats and gradually added a large number of scripts (languages). Tesseract 3.x is based on traditional computer vision algorithms. In the past few years, Deep Learning based methods have surpassed traditional machine learning techniques by a huge margin in terms of accuracy in many areas of Computer Vision. Handwriting recognition is one of the prominent examples.
So, it was just a matter of time before Tesseract too had a Deep Learning based recognition engine. In version 4, Tesseract has implemented a Long Short Term Memory (LSTM) based recognition engine. LSTM is a kind of Recurrent Neural Network (RNN). Note for beginners: To recognize an image containing a single character, we typically use a Convolutional Neural Network (CNN). Text of arbitrary length is a sequence of characters, and such problems are solved using RNNs and LSTM is a popular form of RNN. Read to learn more about LSTM.
![Avx Avx](http://i069.radikal.ru/1207/88/263f4e839829.jpg)
![Cnn Cnn](https://image.slidesharecdn.com/siggraphvictoruhdvideoscalingfinallegal-160824225731/95/ultra-hd-video-scaling-lowpower-hw-ff-vs-cnnbased-superresolution-50-638.jpg?cb=1472079817)
Version 4 of Tesseract also has the legacy OCR engine of Tesseract 3, but the LSTM engine is the default and we use it exclusively in this post. Tesseract library is shipped with a handy command line tool called tesseract. We can use this tool to perform OCR on images and the output is stored in a text file. If we want to integrate Tesseract in our C++ or Python code, we will use Tesseract’s API. The usage is covered in, but let us first start with installation instructions. How to install Tesseract on Ubuntu and macOS We will install: • Tesseract library (libtesseract) • Command line Tesseract tool (tesseract-ocr) • Python wrapper for tesseract (pytesseract) Later in the tutorial, we will discuss how to install language and script files for languages other than English.
Install Tesseract 4.0 on Ubuntu 18.04 Tesseract 4 is included with Ubuntu 18.04, so we will install it directly using Ubuntu package manager. Sudo apt install tesseract-ocr sudo apt install libtesseract-dev sudo pip install pytesseract 1.2. Install Tesseract 4.0 on Ubuntu 14.04, 16.04, 17.04, 17.10 Due to certain dependencies, only Tesseract 3 is available from official release channels for Ubuntu versions older than 18.04. Luckily Ubuntu PPA – alex-p/tesseract-ocr maintains Tesseract 4 for Ubuntu versions 14.04, 16.04, 17.04, 17.10. We add this PPA to our Ubuntu machine and install Tesseract. If you have an Ubuntu version other than these, you will have to compile Tesseract from source. Sudo add-apt-repository ppa:alex-p/tesseract-ocr sudo apt-get update sudo apt install tesseract-ocr sudo apt install libtesseract-dev sudo pip install pytesseract 1.3.