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# Apply dilate to merge text into meaningful lines/paragraphs.

Gray = cv2.cvtColor(newImage, cv2.COLOR_BGR2GRAY) # Prep image, copy, convert to gray scale, blur, and threshold Putting all together for getting the angle of skewed image to deskew the image before sending the input image to the tesseract-ocrДef getpreprocessImage(cvImage) -> float: Return cv2.erode(image, kernel, iterations = 1) Img = cv2.imread('excel-invoice-template.png', 0) Return cv2.morphologyEx(image, cv2.MORPH_OPEN, kernel) Kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (30, 5))Дilate = cv2.dilate(thresh, kernel, iterations=5) Thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)

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#dilate to merge text to meaning full text

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To run tesseract OCR we should install it in our system, Download executable Tesseract from this link Now letвЂ™s get dirt on our hands with python code using open CV and tesseract OCR The Tesseract after processing gives a printed text of the image taken as the output. The trained data set is fed to the Tesseract engine.

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Leptonica is an open-source library that contains software used for image processing and analysis. Tesseract acts as the brain of the application. This input image is pre-processed and then pre-processed image is fed to the Tesseract. In the following flowchart of the OCR system, the image is taken by the camera acts as the input image which has text in it. With just a single line of code, it will extract text from the image. Tesseract can extract text from a wide variety of languages. Tesseract is an API, used directly to extract text (printed) from images. Tesseract is an open-source OCR engine used to extract text, It is available under the Apache 2.0 license. To learn image processing techniques follow click here. If you donвЂ™t have any idea about OpenCV, no worries, Please follow our Image Processing section for an easy understanding of OpenCV.Д«ut here we will go through few image processing techniques that will be necessary for OCR steps. These preprocessing steps can have many sub-processes depends on the use cases. The basic process we follow in OCR are preprocessing, text detection, text extraction, and post-processing, OCR extracts the text from any image that contains text to machine-encoded text, whether the image can be a scanned document, a photo of a document, a photo from a scene (say vehicle number, landscape names, street address ). Now I am going to show the text extraction using Python, OpenCV, and tesseract OCRДЄs mentioned earlier, OCR stands for optical character recognition.

Mv *.As we have gone through the basic introduction and brief history of OCR in the previous blog. # download another other languages you like Wget https : // /tesseract-ocr/tessdata/raw/master/chi_sim.traineddata Wget https : // /tesseract-ocr/tessdata/raw/master/eng.traineddata Wget https : // /tesseract-ocr/tessdata/raw/master/equ.traineddata Wget https : // /tesseract-ocr/tessdata/raw/master/osd.traineddata # Download and install tesseract language files (Tesseract 4 traineddata files) LDFLAGS = '-L/usr/local/lib' CFLAGS = '-I/usr/local/include' make - j configure - with - extra - includes = /usr/ local / include - with - extra - libraries = /usr/ local / lib PKG_CONFIG_PATH = /usr/ local / lib / pkgconfig LIBLEPT_HEADERSDIR = /usr/ local / include. Wget https : // /tesseract-ocr/tesseract/archive/4.0.0-beta.1.tar.gz # check if leptonica is installed: type 'ls /usr/local/include' and expect to see 'leptonica' # check if libpng is installed: type 'whereis libpng' and expect to see a directory a blank line is not good Wget http : // tar - zxvf leptonica - 1.75. Yum group install - y 'Development Tools'

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Yum - y install libstdc ++ autoconf automake libtool autoconf - archive pkg - config gcc gcc - c ++ make libjpeg - devel libpng - devel libtiff - devel zlib - devel # The following line will take 30 minutes to install. # Instructions taken (and slightly modified) from # (Estimated Time of Completion: 45 minutes)

Tesseract ocr download linux