Pytesseract library's application in Python and its principles analysis

Pytesseract library's application in Python and its principles analysis Overview: Pytesseract is an OCR (optical character recognition) library used in Python. It can identify the text in the image and convert it into a editing text format.It is developed based on the Tesseract OCR engine and supports multiple languages, including Chinese.This article will introduce the application and principles of Pytesseract, and provide a complete program code and related configuration description. Install: Before using Pytesseract, we need to install the Tesseract OCR engine and configure it to an environment variable.In the Windows system, we can download the latest Tesseract installation program from the official website (https://github.com/tesseract- -cr/tesseract/wiki) and install it in accordance with the installation guide.After the installation is completed, we need to add the path where the Tesseract is located to the environment variables of the system. Example: Below is a basic example, demonstrate how to use the Pytesseract library to extract Chinese text from the image: python import pytesseract from PIL import Image # Specify image path image_path = 'image.jpg' # Open the image and convert it to gray image image = Image.open(image_path).convert('L') # Use Pytesseract for optical character recognition text = pytesseract.image_to_string(image, lang='chi_sim') # print(text) In this example, we first introduced the Pytesseract library and the Pillow library (for image processing).Then, we specified the image path to be identified, and used the `Image.open ()` function to open the image, and use the `convert ()` method to convert it to gray image, because Tesseract is easier to process grayscale images. Next, we use `pytesseract.image_to_string ()` function to recognize the image optical character recognition.This function receives image objects and optional `LANG` parameters for specifying recognition languages.In this example, we designated `Lang = 'Chi_sim'` to identify Chinese text. Finally, we use the `Print ()` function to print out the results of identification. Original analysis: The principle of the Pytesseract library is to use the Tesseract OCR engine for text recognition of the image.Tesseract is an open source OCR engine, developed and maintained by Google.It is based on artificial neural network technology to identify and understand different characters and text through training models. When we use the Pytesseract library, it is actually a package of the Tesseract engine. It provides some simplified interfaces to facilitate us to perform image text recognition.It uses a series of image processing and character recognition algorithms, including gray conversion, dual -value, character segmentation, feature extraction, etc. In Chinese text recognition, we need to set the identification language to Chinese ('chi_sim').In order to make Tesseract corrective Chinese characters correctly, we can also pre -processes images, such as enhancement and noise to improve the accuracy of recognition. It should be noted that because Tesseract is based on machine learning and model training, the accuracy of identification may be different in different environments and scenarios.In order to improve the accuracy of the identification results, we can pre -process the image according to the actual situation and adjust the relevant parameter configuration. Summarize: Pytesseract is a convenient and easy OCR library that can be used for image text recognition in Python.It is based on the TESSERACT OCR engine and supports a variety of languages, including Chinese.This article introduces the application examples and principles of Pytesseract, and provides a complete program code and related configuration description. I hope to help readers better understand and use the Pytesseract library.