How to extract text from the PDF file with the "Pytesseract" class library
How to extract text from the PDF file with the "Pytesseract" class library
With the advent of the era of big data, extracting text from PDF files has become more and more important.In Python, we can use the "Pytesseract" class library to implement this function.‘Pytesseract’ is a Python package based on the Tesseract OCR engine, which can identify and extract text.
To extract the text from the PDF file, you need to complete the following steps:
1. Install the Tesseract OCR engine: Tesseract is an open source OCR engine. We first need to install it.The specific installation steps are different depending on the operating system you use.
2. Install Pytesseract Library: After installing the Tesseract OCR engine, we can use the PIP command to install the "Pytesseract" library.Run the following command in the terminal to install the class library:
pip install pytesseract
3. Install other dependencies: In order to enable the "Pytesseract" class library to run in the PDF file, we also need to install other dependent libraries.You can use the following command to install the dependent library you need:
pip install pdf2image
pip install pillow
4. Import the required class library: At the beginning of the python file, you need to import the required library.The class library of specific imports is as follows:
python
import pytesseract
from PIL import Image
from pdf2image import convert_from_path
5. Convert PDF files to images: Since the "Pytesseract" class library cannot directly process the PDF file, the PDF file needs to be converted to an image.Using the `Convert_FROM_PATH` function of the" PDF2Image "library can achieve this conversion:
python
images = convert_from_path('input.pdf')
This will return an image list containing the image extracted from the PDF file.
6. Extract text in the image: Use the `Image_to_String` function of the" Pytesseract "class library to extract the text in the image.In a cycle, pass each image to the `Image_to_String` function, and save the extracted text in a string variable:
python
text = ''
for image in images:
text += pytesseract.image_to_string(image, lang='eng')
In this example, we use the English language model for text extraction.
7. Printing and extraction text: Use Python's `Print` statement to print out the extracted text:
python
print(text)
The complete Python code is shown below:
python
import pytesseract
from PIL import Image
from pdf2image import convert_from_path
images = convert_from_path('input.pdf')
text = ''
for image in images:
text += pytesseract.image_to_string(image, lang='eng')
print(text)
Make sure to replace the `Input.pdf` to the PDF file name you want to extract.
It should be noted that the ‘Pytesseract’ Library may have a certain accuracy problem when identifying text, especially when processing complex documents or noise.Therefore, the extracted text may require further processing and calibration.
At the same time, if your PDF file contains Chinese content, you need to set the corresponding language model in the `Image_to_String` function, such as` lang = 'chi_sim'`.
I hope that this article will help you understand the method of using the ‘Pytesseract’ class library to extract text from the PDF file.If you encounter problems in the above steps, it is recommended to consult relevant documents to obtain more detailed help and guidance.
