Application instance of the ‘pytesseract’ class library in natural language processing

‘Pytesseract’ is a Python library for extracting text information in the image.It was developed based on Google's open source project TESSERACT-OCR. 1. Installation and configuration: First of all, you need to install the TESSERACT-OCR and add its path to the system environment variable.Then, install the Pytesseract library through PIP. 2. Import library: In the Python program, the Pytesseract library is first introduced. python import pytesseract 3. Load the image: Use OpenCV or Pil library to load images to be processed.Pytesseract can handle image files in various formats. python from PIL import Image image = Image.open('image.jpg') 4. Extract text information: Use the Pytesseract library to extract text information in the image.You can change the extraction result by setting different parameters. python text = pytesseract.image_to_string(image, lang='chi_sim') In this example, the Lang parameter uses the language to specify the language as the simplified Chinese (Chi_sim). 5. Output results: Finally, output the extracted text information to the console or write it in the file. python print(text) In this way, the text information in the image can be extracted and output. Application instance of the ‘pytesseract’ class library in natural language processing: In natural language processing, the "Pytesseract" class library can be used for text recognition, information extraction and other tasks.The following is an application example: Suppose we have a scanning version of Chinese books, we want to extract the text information in it to further analyze.First, load the scanning image into the Python program.Then, use the 'Pytesseract' library to identify the image.By setting appropriate parameters to ensure the correct identification of Chinese texts.Finally, save the extracted text into a file for subsequent processing. python from PIL import Image import pytesseract # Load the image image = Image.open('book_scan.jpg') # Extract text information text = pytesseract.image_to_string(image, lang='chi_sim') # Output results print(text) # Write the result to the file with open('extracted_text.txt', 'w', encoding='utf-8') as file: file.write(text) In the above code, we use the `IMAGE.OPEN ()` function to load the image from the file.Then, we use the `pytesseract.image_to_string () function to identify the image text and store the result in the` Text` variable.Finally, we use the `Print ()` function to print the extracted text information to the console, and use the `Open ()` function to write the text into a file named `extracted_text.txt`. By using the "Pytesseract" library, we can easily extract text information from the image, so as to use it in natural language processing tasks.