Extract text from images in multiple languages
Extract text from a PDF file
Qwen2-VL is a vision-language model that performs OCR
A robust offline system for recognizing handwritten Hindi
Convert images to text
Read text from captcha images
Convert images to text using OCR without code changes
OCR System. Homepage: https://github.com/Topdu/OpenOCR
Extract text from single-line Kurdish images
Recognize text from images
Convert images to multiplication pairs text
Read text from images
Extract text from images using OCR
PaddleOCR is a powerful Optical Character Recognition (OCR) tool designed to extract text from images in multiple languages. It leverages cutting-edge AI technology to deliver high accuracy and versatility, making it suitable for both individual and enterprise applications. With support for a wide range of languages and image formats, PaddleOCR is a robust solution for digitizing text from various sources.
• Multilingual Support: Recognizes text in multiple languages, including English, Chinese, French, Spanish, German, Italian, Portuguese, and many more.
• State-of-the-Art Models: Utilizes advanced AI models for accurate text recognition, optimized for both accuracy and performance.
• Image Format Compatibility: Supports popular image formats such as PNG, JPG, BMP, and TIFF.
• Customizable: Users can customize OCR templates and models according to specific requirements.
• Hardware Acceleration: Supports hardware acceleration for faster inference, making it suitable for edge devices.
• Real-Time Inference: Enables real-time text recognition for applications requiring instantaneous responses.
Install PaddleOCR:
pip install paddleocr
Import the Library:
from paddleocr import PaddleOCR
Initialize the OCR Engine:
ocr = PaddleOCR(lang='en') # Replace 'en' with your desired language
Load and Recognize Text:
text = ocr.ocr(image_path='path_to_your_image.jpg') # Replace with your image path
Process the Results:
print(text) # Displays the extracted text
What languages does PaddleOCR support?
PaddleOCR supports a wide array of languages, including English, Chinese, French, Spanish, German, Italian, Portuguese, and many others. Users can specify the language during initialization for optimal results.
How do I optimize PaddleOCR for low-quality images?
For low-quality images, you can preprocess the images by applying filters, increasing contrast, or binarizing the images before passing them to PaddleOCR.
Can I use PaddleOCR on mobile or edge devices?
Yes, PaddleOCR supports hardware acceleration and is lightweight enough to run on mobile and edge devices, making it suitable for real-time applications.