The text recognition application of the ‘pytesseract’ class library in Python
The text recognition application of the ‘pytesseract’ class library in Python
In the digital era, text recognition (OCR) has become an important task in many fields.Whether it is from images, PDF files, or scanning documents, extracting text information is a common requirement.‘Pytesseract’ is a powerful Python class library that uses the OCR engine Tesseract and has good cross -platform performance, which can be used to achieve text recognition in Python.
Tesseract is a open source OCR engine developed by Google, which can recognize a variety of languages.‘Pytesseract’ via the API interface provided by Tesseract, so that Python developers can easily implement text recognition functions in their own projects.This article will introduce how to use ‘pytesseract’ to recognize text in Python and provide related code and configuration.
First, we need to install two necessary libraries: ‘Pytesseract’ and ’Pillow’.You can use the following commands to install these two libraries:
python
pip install pytesseract
pip install pillow
After the installation is completed, we can start writing the Python code.Below is a simple example code that shows how to use ‘pytesseract’ for text recognition:
python
from PIL import Image
import pytesseract
# Open and read image files
image = Image.open('image.jpg')
text = pytesseract.image_to_string(image, lang='chi_sim')
# 文
print(text)
In the above code, first of all, we used the 'Image' class in the 'Pil' library (that is, python image library) to open and read image files called ‘Image.jpg’.Then, using the 'Image_to_String' function of ‘pytesseract’ to convert text recognized in the image into string.The parameter ‘lang’ specify the identifiable language. Here we choose Chinese (using simplified Chinese).Finally, by printing output, we can see the identified text results.
However, to ensure that the above code is running correctly, we also need to configure the relevant environment of Tesseract.First, we need to install the TESSERACT OCR engine.You can download it from its official website (https://github.com/tesseract- -cr/tesseract) and install it in accordance with the corresponding instructions.In addition, we also need to download the language data required by Tesseract, which can be obtained from the GitHub warehouse (https://github.com/tesseract- -tessdata) of TESSERACT.
After completing the above steps, we point the environment variable ‘testa_prefix’ to the directory that contains the Tesseract language data, and add it to the code:
python
pytesseract.pytesseract.tesseract_cmd = r'<path_to_tesseract_executable>'
Among them, ‘PATH_TO_TESSERACT_EXECUTable>’ should be replaced with a complete path for Tesseract executable files.
The text recognition application of the ‘Pytesseract’ class library in Python is very powerful and flexible.By configured the correct environment and using appropriate parameters, we can realize the function of extracting text information from various image sources.Whether it is applied to natural language processing, automated office or information retrieval, ‘Pytesseract’ is an excellent choice.
