# PaddleOCR: A Powerful OCR Toolkit for Structured Document Data

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PaddleOCR is an industry-leading, production-ready OCR and document AI engine that transforms any PDF or image document into structured, AI-friendly data. It offers end-to-end solutions from text extraction to intelligent document understanding, supporting over 100 languages with high accuracy and efficiency.

GitHub: https://github.com/PaddlePaddle/PaddleOCR
OSRepos URL: https://osrepos.com/repo/paddlepaddle-paddleocr

## Summary

PaddleOCR is an industry-leading, production-ready OCR and document AI engine that transforms any PDF or image document into structured, AI-friendly data. It offers end-to-end solutions from text extraction to intelligent document understanding, supporting over 100 languages with high accuracy and efficiency.

## Topics

- ocr
- document-parsing
- ai
- python
- machine-learning
- multilingual-ocr
- pdf-processing
- information-extraction

## Repository Information

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## Content

## Introduction
PaddleOCR is an industry-leading, production-ready Optical Character Recognition (OCR) and document AI engine developed by PaddlePaddle. It provides comprehensive, end-to-end solutions, transforming any PDF or image document into structured, AI-friendly data like JSON and Markdown. With support for over 100 languages, PaddleOCR bridges the gap between raw visual documents and advanced Large Language Models (LLMs), making it a powerful and lightweight toolkit for various AI applications. The project boasts over 72,000 stars on GitHub, highlighting its widespread adoption and impact in the AI community. Recent advancements include PaddleOCR-VL-1.5 for real-world document parsing and text spotting, and PP-OCRv5 for universal scene text recognition.

## Installation
To get started with PaddleOCR, you first need to install PaddlePaddle. Refer to the [PaddlePaddle Installation Guide](https://www.paddlepaddle.org.cn/en/install/quick?docurl=/documentation/docs/en/develop/install/pip/linux-pip_en.html) for detailed instructions. Once PaddlePaddle is installed, you can install the PaddleOCR toolkit using pip:

bash
# If you only want to use the basic text recognition feature (returns text position coordinates and content), including the PP-OCR series
python -m pip install paddleocr


For full functionality, including document parsing, understanding, and translation, you can install with the `[all]` dependency group:

bash
# If you want to use all features such as document parsing, document understanding, document translation, key information extraction, etc.
python -m pip install "paddleocr[all]"


PaddleOCR also supports installing partial optional features by specifying other dependency groups like `doc-parser` for document parsing, `ie` for information extraction, and `trans` for document translation.

## Examples
PaddleOCR offers both command-line interface (CLI) and API for inference.

### CLI Examples:

bash
# Run PP-OCRv5 inference
paddleocr ocr -i https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/general_ocr_002.png --use_doc_orientation_classify False --use_doc_unwarping False --use_textline_orientation False  

# Run PP-StructureV3 inference
paddleocr pp_structurev3 -i https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/pp_structure_v3_demo.png --use_doc_orientation_classify False --use_doc_unwarping False

# Run PaddleOCR-VL inference
paddleocr doc_parser -i https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/paddleocr_vl_demo.png


### API Example (PP-OCRv5):

python
# Initialize PaddleOCR instance
from paddleocr import PaddleOCR
ocr = PaddleOCR(
    use_doc_orientation_classify=False,
    use_doc_unwarping=False,
    use_textline_orientation=False)

# Run OCR inference on a sample image 
result = ocr.predict(
    input="https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/general_ocr_002.png")

# Visualize the results and save the JSON results
for res in result:
    res.print()
    res.save_to_img("output")
    res.save_to_json("output")


## Why Use PaddleOCR
PaddleOCR stands out as a premier solution for intelligent document applications in the AI era due to several compelling reasons:
*   **Industry-Leading Accuracy:** It consistently achieves state-of-the-art performance in various OCR and document parsing benchmarks, including complex real-world scenarios.
*   **Multilingual Support:** With robust support for over 100 languages, it caters to global applications and diverse linguistic needs.
*   **Comprehensive Functionality:** Beyond basic text recognition, it offers advanced features like document parsing (PP-StructureV3), intelligent information extraction (PP-ChatOCRv4), and document translation (PP-DocTranslation).
*   **Production-Ready and Efficient:** Designed for practical deployment, PaddleOCR is lightweight, resource-efficient, and supports high-performance inference across various hardware, including CPU, GPU, XPU, and NPU.
*   **Strong Community and Integrations:** Integrated into leading projects like MinerU, RAGFlow, and pathway, it benefits from an active community and extensive documentation.

## Links
*   **GitHub Repository:** [PaddlePaddle/PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR)
*   **Official Website:** [PaddleOCR Official Website](https://www.paddleocr.com)
*   **PaddleOCR 3.0 Technical Report:** [arXiv](https://arxiv.org/abs/2507.05595)
*   **PaddleOCR-VL Technical Report:** [arXiv](https://arxiv.org/abs/2510.14528)
*   **HuggingFace Demo (PaddleOCR-VL-1.5):** [PaddleOCR-VL-1.5 Online Demo](https://huggingface.co/spaces/PaddlePaddle/PaddleOCR-VL-1.5_Online_Demo)
*   **ModelScope Demo (PaddleOCR-VL-1.5):** [PaddleOCR-VL-1.5 Online Demo](https://www.modelscope.cn/studios/PaddlePaddle/PaddleOCR-VL-1.5_Online_Demo)
*   **Documentation:** [PaddleOCR Documentation](https://paddlepaddle.github.io/PaddleOCR/latest/en/)