PaddleOCR Tutorial: How to Quickly Achieve High-Precision Image Text Recognition (Including Practical Examples)

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PaddleOCRAs an open-source, high-precision, multilingual OCR engine from Baidu's PaddlePaddle team, PaddleOCR is widely used in document archiving, invoice processing, mobile translation, and other fields due to its ease of use, flexible deployment, and industry-leading recognition capabilities. This article provides a detailed explanation of PaddleOCR's core advantages and operational processes, combining command-line interfaces, APIs, and real-world industry application examples to help developers and enterprises quickly and efficiently achieve accurate text reading within images.
High precision, multifunctional, customizable and free to useThis makes PaddleOCR the preferred solution for AI image and text recognition scenarios both domestically and internationally.

PaddleOCR Tutorial: How to Quickly Achieve High-Precision Image Text Recognition (Including Practical Examples)

Introduction and Core Advantages of PaddleOCR

What is PaddleOCR?

PaddleOCRIt is an open-source OCR toolkit based on the Baidu PaddlePaddle platform, covering many functions such as multilingual support, tables, handwriting, and layout analysis, and has a wide range of applications in the global AI vision field.

Main features：

Supports 80+ languagesCoverage in Chinese, English, Japanese, and Korean
Flexible deployment on mobile devices/serversCompatible with multiple platforms including x86/ARM/embedded systems
Numerous pre-trained modelsOne-stop solution for scenarios such as subtitles, document scanning, ID cards, and license plates.
Rich command-line and API interfacesMinimalist and easy to customize
The official documentation is continuously maintained and improved.

Screenshot of PaddleOCR's official homepage — Image/Screenshot from PaddleOCR official homepage

Key features	Details
Multilingual support	Covering 80+ languages, serving users worldwide
Deployment flexibility	Supports Linux/Windows/macOS/Android/iOS
pre-trained model	Subtitles, scene text, handwritten text, documents, cards, etc.
Ease of use	The API is user-friendly and can be used immediately via command line.
Performance and accuracy	Industry-leading, highly accurate document recognition
Scalability	It can be further developed and the parameter model can be customized.

Product Homepage and Resource Downloads

How to quickly deploy and use PaddleOCR

Environment and Dependency Installation

With just Python and PaddlePaddle, you can install it with a single click!

python -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple python -m pip install "paddleocr>=2.6.1" -i https://mirror.baidu.com/pypi/simple

Detailed dependencies:Python 3.6 and above，PaddlePaddle(Supports CPU/GPU)

Command-line one-click OCR

No programming required, just one command line!

paddleocr --image_dir ./imgs/test.jpg --use_angle_cls=True --lang=ch

–image_dirEnter the image path
-langSelect language packs such as ch/en/ru/ja/ko, etc.
–use_angle_clsAutomatically correct text slant

Scene	Command Examples
Local Images	paddleocr –image_dir img1.jpg –lang=ch
Batch images	paddleocr –image_dir imgs/ –rec –det
Output visualization results	paddleocr –image_dir test.jpg –visualize=True
GPU Inference	paddleocr –image_dir test.jpg –use_gpu=True

For more parameters and practical tutorials, please seeOfficial documentation

Official document screenshot — Image/Screenshot from official document

Python API integration

Suitable for developers to use flexibly and perform secondary development.

from paddleocr import PaddleOCR ocr = PaddleOCR(use_angle_cls=True, lang="ch") results = ocr.ocr('test.jpg', cls=True) for line in results[0]: print('Content:', line[1][0], 'Confidence:', line[1][1])

Supports multi-threading and batch recognition, suitable for enterprise automation processes.
Python API documentation

Python code interface — Image/Python code calling interface

Sharing common high-precision application cases

High-quality input leads to high recognition rate

The image needs to be clear and have strong background contrast.
Avoid watermark obscuring or distortion
The model can be customized for specific domains and adapted to professional scenarios.

Typical Scenario 1: Digitization of Corporate Invoices and Documents

The large volume of paper documents, contracts, and invoices archived by financial institutions and government/enterprise units can be batch scanned and quickly converted into text, greatly improving efficiency.Improve efficiency and reduce human error。

paddleocr --image_dir ./bills/ --output ./output/ --lang=ch --det --rec

Typical Scenario 2: Mobile Photo Translation

Combining PaddleOCR and online translation APIs can easily achieve...Photo translationThis feature is suitable for low-server-cost applications such as mini-programs and cross-border mobile applications.

Photo/Detailed Explanation of Mobile Deployment

Camera captures image → OCR recognition → Translation interface → Display translated text
Detailed Explanation of Mobile Deployment

Typical Scenario 3: Intelligent Manufacturing and License Plate Recognition

Application scenarios	describe
Production line label collection	One-click reading of conveyor belt batch number and identification
Smart Transportation	CCTV automatically captures and recognizes vehicle license plate numbers.
Security access control	Automatic entry of ID cards/digital cards and other documents

Typical Scenario 4: Complex Tables and Page Layout Reconstruction

One-click reconstruction of tables/structured documents into Excel/JSONIt is suitable for automated office scenarios such as bank statements and news columns.

Table recognition experience entry

Table recognition interface — Image/Table Recognition Interface

Precautions and Frequently Asked Questions

Blurry or low-resolution images can affect recognition rates.
Angle classification should be enabled for text that is tilted or overlapping.
Choosing the right language pack and model is crucial; industry trends require fine-tuning.
Supports batch processing with Shell scripts/Python, and offers convenient enterprise-level integration.

PaddleOCR code and models are licensed under the Apache-2.0 license, and are open source, commercially usable, and customizable.

Project open source homepage

In the wave of digital transformation and AI industry upgradingWith its simple deployment, unparalleled recognition accuracy, and broad industry adaptability, PaddleOCR has become the preferred choice for many enterprises and developers to efficiently process image text.Applications such as invoice archiving, mobile AI recognition, smart factories, and international multilingual scenarios have all achieved excellent results in practice.Welcome to download and experience it for free, and embrace the new era of efficient intelligent image text recognition!