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PaddleOCR Complete Guide 2025: Installation, Usage, and Comparison

By Jenefey Aaron

2025-11-26 / OCR

Has anyone here used PaddleOCR-VL for multi-column PDFs? Normal PaddleOCR works well for simple text, but complex layouts with Chinese/English mixed text still give me messy results.

Developers today look for OCR tools that are fast, accurate, and simple to set up, and PaddleOCR has become a favorite for exactly these reasons. This open-source OCR system keeps improving every year, and the 2025 lineup is packed with powerful models like PP-OCRv3, PP-OCRv4, PP-OCRv5, and the more advanced PaddleOCR-VL, which handles both text and layout understanding.

This guide walks you through everything you need: how to install PaddleOCR, how each model works, what makes them different, and which version is best for your use case. The explanations are written in clear language so you can start using PaddleOCR without any stress or confusion.

Part 1. What Is PaddleOCR and Why It Matters

Part 2. How to Install and Run PaddleOCR

Part 3. PaddleOCR Versions and Model Selection

Part 4. Best OCR Solution Over PaddleOCR - More Accurate, Smarter & Faster

Part 5. PaddleOCR vs Other OCR Tools

Part 6. PaddleOCR Licensing, Security, and Commercial Use

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Part 1. What Is PaddleOCR and Why It Matters

Overview of OCR Technology

OCR (Optical Character Recognition) is a technology that reads text from images, scanned documents, or PDFs and turns it into editable, searchable text. Modern OCR uses deep learning to detect text regions and recognize characters accurately, even if the text is rotated, curved, or mixed with images. OCR is widely used in digitizing documents, automating data entry, searching text, and making documents accessible.

PaddleOCR Key Features and Supported Languages
PaddleOCR is an open-source OCR toolkit from the PaddlePaddle team (Baidu). It is designed to be fast, accurate, and easy for developers to use.

Key Features:

• Complete OCR Pipeline: Detects text, recognizes characters, and handles text direction and layout.
• Variety of Models: Lightweight for mobile and fast, or heavy for more accurate server use.
• Compression & Deployment: Supports model optimization for mobile or edge devices.
• Multilingual Support: Recognizes over 100 languages including Latin, Cyrillic, Arabic, and Asian scripts.
• Advanced Document Analysis: Can detect tables, forms, and complex document layouts.

Supported Languages:

supports 80+ languages in older vPaddleOCR ersions, and PP-OCRv5 supports over 100 languages, making it great for global applications.

Why Developers and Businesses Use PaddleOCR

• Easy to Use: Clear APIs and pre-trained models make setup simple.
• Accurate & Fast: Modern models provide high accuracy for text detection and recognition.
• Efficient for Production: Works on mobile, CPU, or GPU servers with model compression.
• Multilingual & Global: Handles documents in many languages, ideal for international use.
• Structured Data Extraction: Can read tables, forms, and other structured documents.
• Business-Friendly License: PaddleOCR is under the Apache 2.0 license, so it's free to use and modify for commercial purposes.

Note:

When you start working with OCR tools like PaddleOCR, you often realize that extracting text is just the first step. Many people still struggle to clean the text, fix layout issues, or edit the original PDF afterward. This is where a tool like Tenorshare PDNob PDF Editor helps. It lets you edit text directly, reorganize pages, run built-in AI OCR, and handle everyday PDF tasks without switching between multiple apps.

Part 2. How to Install and Run PaddleOCR

Step-by-Step Installation Guide

• Install PaddlePaddle

PaddleOCR requires PaddlePaddle 3.0 or above. You can install it using pip for CPU or GPU:



CPU version:

python -m pip install paddlepaddle==3.2.0 -i https://www.paddlepaddle.org.cn/packages/stable/cpu/

GPU version (CUDA 11.8):

python -m pip install paddlepaddle-gpu==3.2.0 -i https://www.paddlepaddle.org.cn/packages/stable/cu118/

Verify the installation:

python -c "import paddle; print(paddle.__version__)"

You should see 3.2.0 or higher.

• Install PaddleOCR

For basic text recognition:

python -m pip install paddleocr

For full features, including document parsing and translation:

python -m pip install "paddleocr[all]"

You can also install from source:

python -m pip install "paddleocr@git+https://github.com/PaddlePaddle/PaddleOCR.git"

Optional Dependency Groups:

• doc-parser: Extract tables, formulas, stamps, images (PP-StructureV3)
• ie: Extract key information from documents (PP-ChatOCRv4)
• trans: Translate documents (PP-DocTranslation)
• all: Includes all features
• Installing Training Dependencies

If you want to train or export models:

git clone https://github.com/PaddlePaddle/PaddleOCR

cd PaddleOCR

git checkout release/3.2

python -m pip install -r requirements.txt

Quick Test Example - Extract Text from an Image

Here's a simple Python example using PP-OCRv4 / v5:

from paddleocr import PaddleOCR

# Initialize OCR

ocr = PaddleOCR(use_doc_orientation_classify=False,

use_doc_unwarping=False,

use_textline_orientation=False)

# Run OCR on an image

result = ocr.predict("./example.png")

# Print results

for res in result:

res.print()

res.save_to_img("output.png")

res.save_to_json("output.json")

You can also run from the command line:

paddleocr ocr -i ./example.png --use_doc_orientation_classify False --use_doc_unwarping False

This works with Paddle OCR VL, PP-OCRv5, and other supported models.

Troubleshooting Common Installation Issues

• Module not found errors: Make sure paddleocr is installed in the same Python environment you are using.

• GPU errors: Check your CUDA version matches your PaddlePaddle GPU installation.

• PyMuPDF errors: Install PyMuPDF manually if paddleocr[all] fails:

python -m pip install PyMuPDF

High CPU usage on Mac M1: Try using lightweight models (PP-OCRv5_mobile_det and PP-OCRv5_mobile_rec) for faster performance.

AWS EC2 / Linux issues: Install missing dependencies like libglvnd-glx on Amazon Linux:

sudo dnf install libglvnd-glx

Following these steps ensures PaddleOCR works correctly for both PaddleOCR huggingface deployments and local environments.

Part 3. PaddleOCR Versions and Model Selection

PP‑OCRv3 vs PP‑OCRv4 vs PP‑OCRv5

PP‑OCRv3

• Designed as an ultra‑lightweight OCR system. Its architecture improves efficiency while maintaining decent accuracy.
• Uses the SVTR + LCNet model for recognition, instead of CRNN, which results in faster inference and lower computational cost.
• Incorporates several training strategies: attention-guided CTC loss, data augmentation (TextConAug), and self‑supervised pretraining (TextRotNet), plus distillation / mutual learning (UDML, UIM) to improve performance.
• Very small model sizes: for example, the English mobile-rec model is just ~9.6 MB.
• Good for use on mobile or edge devices where resources are constrained.

PP‑OCRv4

• Builds on v3 but optimizes both detection and recognition for better accuracy, especially in document-style text.
• Comes in different flavors: mobile (for speed and small memory) and server (for accuracy).
• According to Paddle's GitHub, v4 models are still widely used and have strong support.
• Ideal when you need a balance: you want decent speed + good accuracy for fairly standard printed or typed text.

PP‑OCRv5

• The most advanced generation of the PP‑OCR series. Focused on multi‑scenario and multi‑text type recognition.
• Supports five mainstream text types: Simplified Chinese, Traditional Chinese, Pinyin, English, and Japanese.
• Strong support for complex scenarios: vertical text, complex or rare characters, handwriting.
• In internal tests, v5 delivered a 13-percentage-point improvement in end-to-end accuracy compared to PP‑OCRv4.
• In multilingual experiments, PP‑OCRv5 supports 106 languages, including Korean, Spanish, French, Russian, Arabic, and many more.
• Trade-off: because of a larger recognition dictionary and more capacity, inference is slower and uses more memory compared to v4.

Choosing the Right Model for Speed, Accuracy, and Language

Here's how to decide which version fits your needs:

Part 4. Best OCR Solution Over PaddleOCR - More Accurate, Smarter & Faster

While PaddleOCR is a powerful tool for developers, it requires Python setup, dependencies, and proper model selection. For users who want a quick, reliable, and easy OCR solution, Tenorshare PDNob is a perfect alternative. PDNob is a lightweight, offline, all-in-one PDF tool with built-in OCR capabilities.

Advantages of PDNob PDF Editor Over PaddleOCR

• Accuracy: Reliable text recognition for multiple languages, suitable for contracts, scanned books, assignments, and receipts.
• Speed: Instant startup, fast OCR response, and smooth batch processing for large document sets.
• Simplicity: A clean, intuitive interface-no programming, no configuration, no environment setup.
• Security: 100% offline OCR, ensuring sensitive documents never leave your device.

How to Use Tenorshare PDNob PDF Editor

• Open the PDNob PDF Editor,then click on “Open PDF” button to import any PDF file you’ve downloaded.

• Click the “Edit” button on the top toolbar, then select the text you want to modify. A text box will appear, allowing you to change the text, font, style, size, and color.

• To add new text, click “Add Text” under the “Edit” section and place it where needed.
• To insert images, click the “Add Image” button and choose the image file to add.

• Once you have made all the necessary edits, click on the "Save" button in the top left corner.

When to Use PDNob vs PadleOCR

Part 5. PaddleOCR vs Other OCR Tools

To understand where PaddleOCR stands in the broader OCR landscape, it helps to compare it with two other popular open-source OCR libraries: Tesseract and EasyOCR.

Part 6. PaddleOCR Licensing, Security, and Commercial Use

PaddleOCR is released under the Apache 2.0 License, which allows free use, modification, and commercial deployment with minimal restrictions. This makes it suitable for both personal projects and business-grade applications.

Because PaddleOCR runs entirely offline, documents stay on the user's device. No data is uploaded or transmitted, which is essential for handling sensitive files such as invoices, IDs, legal documents, and internal records.

For commercial use, businesses only need to keep the Apache license notice and ensure the chosen model fits their workflow. As long as the deployment environment is secure and properly optimized, PaddleOCR can be safely integrated into enterprise systems or custom OCR solutions.

Conclusion

PaddleOCR is a strong and flexible OCR tool, especially for developers. It provides accurate text recognition, supports many languages, works offline, and offers models like PP-OCRv3, v4, and v5. However, for non-technical users or those seeking a faster, simpler, and ready-to-use solution, Tenorshare PDNob PDF Editor is a great alternative. It offers high accuracy, batch processing, multi-language support, and works completely offline without any coding required.

downloads :

PDNob PDF Editor Software- Smarter, Faster, Easier

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• Instantly read, summarize, and extract insights from PDF
• Convert PDF to 30+ formats like Word, Excel, and images
• Edit text, images, watermarks, links, and backgrounds for PDF
• 99% OCR precision for making scanned PDFs editable and searchable

The END