How to analyze and identify Chinese text in class libraries of ‘pytesseract’

How to analyze and identify Chinese text in class libraries of ‘pytesseract’ introduce The rapid development of modern computer vision technology has made text recognition a important and interesting field.‘Pytesseract’ is an open source Python class library. Based on the Tesseract OCR engine, it can help us realize the analysis and recognition of Chinese characters.This article will introduce you to the method of analyzing and identifying Chinese text using the "Pytesseract" class library, and provide a complete example code and related configuration description. step 1. Install Tesseract OCR engine The ‘Pytesseract’ Library is developed based on the Tesseract OCR engine.So before using 'Pytesseract', we need to ensure that the Tesseract OCR engine has been correctly installed on our computer. For the Windows operating system, you can download the suitable installation package from https://github.com/ub-mannheim/tesseract/wiki and install according to the instructions.After the installation is completed, you need to add the installation path of the TESSERACT to the system environment variable. 2. Install Pytesseract Library After installing the Tesseract OCR engine, we can use the PIP tool to install the "Pytesseract" library.Open the command line terminal and run the following command for installation: pip install pytesseract 3. Import the required class library Before writing code, we need to import the Python class library.Please add the following code to your Python script file: python import cv2 import pytesseract 4. Read the image file To analyze and identify Chinese text, we need to read image files with OpenCV libraries.The following code read the image file as an opencv image object: python image = cv2.imread('image_path.jpg') Make sure to replace the 'Image_path.jpg' with the path of the actual image file you want to analyze and recognize. 5. Met the text recognition By calling the API function provided by the "PYTESSERACT" class library, we can identify the image text.The following is an example code that is used to identify the Chinese text in the picture: python text = pytesseract.image_to_string(image, lang='chi_sim') In the above code, we use the 'chi_sim' parameter to specify the use of simplified Chinese language model for text recognition.You can also choose other language models as needed, and the specific available language models can be found in the official documentation of Tesseract OCR. 6. Printing and recognition results Finally, we can use the following code to print the recognition results to the console: python print(text) At this point, you should be able to see the Chinese text recognized in the image on the console. Code example Below is a complete sample code that demonstrates how to use the "Pytesseract" class library to analyze and identify Chinese text: python import cv2 import pytesseract # Read the image file image = cv2.imread('image_path.jpg') # text = pytesseract.image_to_string(image, lang='chi_sim') # print(text) Please note that you need to replace the "image_path.jpg 'with the path of the actual image file you want to analyze and recognize. Summarize This article introduces the method of analyzing and identifying Chinese text by using the "Pytesseract" class library.By installing the Tesseract OCR engine correctly, and combined with the API function provided by the "Pytesseract" class library, we can easily implement the text recognition function in the image.I hope this article can help you make progress in Chinese text recognition!