![]() ![]() Git blame to know which lines belong to which author). (see the file AUTHORS for the contributors list, and If you know of any other applications that use Pyocr, pleaseĬopyright belongs to the authors of each piece of code There are many algorithms possible to do that. If you want to run OCR on natural scenes (photos, etc), you will have to filter To run the tesseract tests, you will need the following lang data files: The first tests verify that you're using the expected version. Note that this code assumes that there is an image named ‘image.png’ in the current. Then it opens the image and uses the OCR tool to perform OCR on it. ![]() It first gets the available OCR tools and selects the first one. Tests are made to be run with the latest versions of Tesseract and Cuneiform. This code uses the PyOCR library to get an OCR tool and perform OCR on an image. Orientation detectionĬurrently only available with Tesseract or Libtesseract. Text at all (depends on the OCR tool behavior). If the OCR fails, an exception pyocr.PyocrExceptionĪn exception MAY be raised if the input image contains no ![]() The default value depends ofĪrgument 'builder' is optional. ![]() # Digits - Only Tesseract (not 'libtesseract' yet !)Īrgument 'lang' is optional. Heres how you can configure pyocr to recognize individual digits: from PIL import Image import sys import pyocr import pyocr.builders tools pyocr.getavailabletools () if len (tools) 0: print ('No OCR tool found') sys.exit (1) tool tools 0 im Image.open digit. # Beware that some OCR tools (Tesseract for instance) may return boxes # with an empty content. Only supported with Tesseract and Libtesseract (always 0 # with Cuneiform). Pyocr is an optical character recognition (OCR) tool wrapper for python. Confidence score depends entirely on # the OCR tool. For each line object: # line.word_boxes is a list of word boxes (the individual words in the line) # ntent is the whole text of the line # line.position is the position of the whole line on the page (in pixels) # Each word box object has an attribute 'confidence' giving the confidence # score provided by the OCR tool. Line_and_word_boxes = tool.image_to_string( I have used it many times before, but when I use this script: from PIL import Image import sys import pyocr import pyocr.builders tools pyocr.getavailabletools() if. For each box object: # box.content is the word in the box # box.position is its position on the page (in pixels) # Beware that some OCR tools (Tesseract for instance) # may return empty boxes Orientation detectionĬurrently only available with Tesseract or Libtesseract.# list of box objects. DigitBuilder()Īrgument 'lang' is optional. # Digits - Only Tesseract (not 'libtesseract' yet !) digits = tool. Only supported with Tesseract and Libtesseract (always 0 # with Cuneiform). For each line object: # line.word_boxes is a list of word boxes (the individual words in the line) # ntent is the whole text of the line # line.position is the position of the whole line on the page (in pixels) # Each word box object has an attribute 'confidence' giving the confidence # score provided by the OCR tool. from PIL import Image import sys import pyocr import pyocr.builders tools pyocr.getavailabletools() if len(tools) 0: print(No OCR tool found). For each box object: # box.content is the word in the box # box.position is its position on the page (in pixels) # Beware that some OCR tools (Tesseract for instance) # may return empty boxes line_and_word_boxes = tool. # txt is a Python string word_boxes = tool. ![]()
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