How to use language models to extract text from PDFs and images

In the digital age, extracting text from PDFs and images has become a common task. This technology has a wide range of applications, such as extracting information from scanned documents, extracting text from images, etc. This article will describe how to use language models to achieve this goal.

1. Extract text from PDF

PDF is a common document format that is usually used to store large amounts of text and images. . Extracting text from PDF is an important task, which can help us quickly obtain the information in the document. Here are the steps to extract text from PDF: 1. Open the PDF file using professional PDF reader software. 2. Find the "Select Text" tool in the software toolbar and use it to select the text that needs to be extracted. 3. Copy the selected text to the clipboard. 4. Open text editing software, such as Microsoft Word or Notepad, and paste the text in the clipboard. 5. Format and edit as needed. Go through these simple steps

Step 1: Install PDF parsing library

To extract text from PDF, you need to install a PDF parsing library, e.g. PyPDF2 or pdfminer. Choose a parsing library that best suits your needs.

Step 2: Open the PDF file

Use the PDF parsing library to open the PDF file. You can use the Python programming language to accomplish this task. Here is a sample code:

import PyPDF2

pdf_file = open('example.pdf', 'rb')
pdf_reader = PyPDF2.PdfFileReader(pdf_file)

Step 3: Get the text content

Once the PDF file is open, you can use a PDF parsing library to extract text from it. Here is a sample code:

page = pdf_reader.getPage(0)
text = page.extractText()
print(text)

The above code will extract the first page of the PDF file and print its text content to the screen.

2. Extracting text from images

Extracting text from images is a relatively new technology that usually uses optical characters recognition (OCR) technology. Here are the steps to extract text from an image:

Step 1: Install the OCR library

To extract text from an image, you need to install An OCR library. Commonly used OCR libraries include Tesseract, OCRopus, etc. You can choose an OCR library that best suits you based on your needs.

Step 2: Read the image file

Read the image file using the Python programming language. Here is a sample code:

import cv2

image = cv2.imread('example.jpg')

Step 3: Use the OCR library to extract text

Use the OCR library to extract text from the image. Here is a sample code:

import pytesseract

text = pytesseract.image_to_string(image)
print(text)

The above code will extract the text from the image and print it to the screen.

Using language models to extract text from PDFs and images is a very useful technique. Extracting text from PDF can help us quickly obtain information in the document, and extracting text from images can help us convert handwritten text or printed text into editable text. In practical applications, we should choose the PDF parsing library and OCR library that suits our needs, and adjust and optimize them according to the specific situation.

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