Hello! In this video we will talk about PyTessearct. Python-tesseract is an optical character recognition (OCR) tool for python. That is, it will recognize and “read” the text embedded in images. Image to Text with Python - pytesseract.
Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.
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Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.
Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is
Syntax: x = lambda arguments : expression
Now i will show you some python lambda function examples:
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Python-tesseract is an optical character recognition (OCR) tool for python. That is, it will recognize and “read” the text embedded in images.
Python-tesseract is a wrapper for Google’s Tesseract-OCR Engine. It is also useful as a stand-alone invocation script to tesseract, as it can read all image types supported by the Pillow and Leptonica imaging libraries, including jpeg, png, gif, BMP, tiff, and others. Additionally, if used as a script, Python-tesseract will print the recognized text instead of writing it to a file.
We’re going to start experimenting with tesseract using just a simple image of nice clean text.
Lets first import Image from PIL and display the image text.png.
from PIL import Image image = Image.open("../input/ocr.png") display(image)
Great, we have a base image of some big clear text
Let’s import pytesseract and use the dir() function to get a sense of what might be some interesting functions to play with.
import pytesseract dir(pytesseract)
It looks like there are just a handful of interesting functions, and I think image_to_string is probably our best bet. Let’s use the help() function to interrogate this a bit more
Help on function image_to_string in module pytesseract.pytesseract: image_to_string(image, lang=None, config=’’, nice=0, output_type=’string’) Returns the result of a Tesseract OCR run on the provided image to a string.
Ok, let’s try and run tesseract on this image
text = pytesseract.image_to_string(image) print(text)
See the magic of OCR using
pytessaract. we will be able to
read the content of image and
convert it to text.
In the previous example, we were using a clear, unambiguous image for conversion. Sometimes there will be noise in images you want to OCR, making it difficult to extract the text. Luckily, there are techniques we can use to increase the efficacy of OCR with pytesseract and Pillow.
Let’s use a different image this time, with the same text as before but with added noise in the picture.
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OCR technology is implemented by applying technologies like ML, AI, and Data Science. Implementing OCR as a process returns the value depending upon the scanned data set.
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