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PaddleOCR aims to create multilingual, awesome, leading, and practical OCR tools that help users train better models and apply them into practice.

Recent updates

• 2021.12.21 release PaddleOCR v2.4, release 1 text detection algorithm (PSENet), 3 text recognition algorithms (NRTR、SEED、SAR), 1 key information extraction algorithm (SDMGR, tutorial) and 3 DocVQA algorithms (LayoutLM, LayoutLMv2, LayoutXLM, tutorial).

• 2021.9.7 release PaddleOCR v2.3, PP-OCRv2 is proposed. The inference speed of PP-OCRv2 is 220% higher than that of PP-OCR server in CPU device. The F-score of PP-OCRv2 is 7% higher than that of PP-OCR mobile.

• 2021.8.3 released PaddleOCR v2.2, add a new structured documents analysis toolkit, i.e., PP-Structure, support layout analysis and table recognition (One-key to export chart images to Excel files).

• more

PaddleOCR support a variety of cutting-edge algorithms related to OCR, and developed industrial featured models/solution PP-OCR and PP-Structure on this basis, and get through the whole process of data production, model training, compression, inference and deployment.

It is recommended to start with the “quick experience” in the document tutorial

• Web online experience for the ultra-lightweight OCR: Online Experience
• Mobile DEMO experience (based on EasyEdge and Paddle-Lite, supports iOS and Android systems): Sign in to the website to obtain the QR code for installing the App
• One line of code quick use: Quick Start

• Dive Into OCR 📚

• Join us👬: Scan the QR code below with your Wechat, you can join the official technical discussion group. Looking forward to your participation.
• Contribution🏅️: Contribution page contains various tools and applications developed by community developers using PaddleOCR, as well as the functions, optimized documents and codes contributed to PaddleOCR. It is an official honor wall for community developers and a broadcasting station to help publicize high-quality projects.
• Regular Season🎁: The community regular season is a point competition for OCR developers, covering four types: documents, codes, models and applications. Awards are selected and awarded on a quarterly basis. Please refer to the link for more details.

• For more model downloads (including multiple languages), please refer to PP-OCR series model downloads.
• For a new language request, please refer to Guideline for new language_requests.
• For structural document analysis models, please refer to PP-Structure models.

• Environment Preparation
• PP-OCR 🔥
  • Quick Start
  • Model Zoo
  • Model training
    • Text Detection
    • Text Recognition
    • Text Direction Classification
  • Model Compression
    • Model Quantization
    • Model Pruning
    • Knowledge Distillation
  • Inference and Deployment
    • Python Inference
    • C++ Inference
    • Serving
    • Mobile
    • Paddle2ONNX
    • Benchmark
• PP-Structure 🔥
  • Quick Start
  • Model Zoo
  • Model training
    • Layout Parser
    • Table Recognition
    • DocVQA
    • Key Information Extraction
  • Inference and Deployment
    • Python Inference
    • C++ Inference
    • Serving
• Academic algorithms
  • Text detection
  • Text recognition
  • End-to-end
  • Add New Algorithms to PaddleOCR
• Data Annotation and Synthesis
  • Semi-automatic Annotation Tool: PPOCRLabel
  • Data Synthesis Tool: Style-Text
  • Other Data Annotation Tools
  • Other Data Synthesis Tools
• Datasets
  • General OCR Datasets(Chinese/English)
  • HandWritten_OCR_Datasets(Chinese)
  • Various OCR Datasets(multilingual)
• Code Structure
• Visualization
• Community
• New language requests
• FAQ
• References
• License

• Chinese OCR model

• English OCR model

• Multilingual OCR model

If you want to request a new language support, a PR with 1 following files are needed：

1. In folder ppocr/utils/dict, it is necessary to submit the dict text to this path and name it with {language}_dict.txt that contains a list of all characters. Please see the format example from other files in that folder.

If your language has unique elements, please tell me in advance within any way, such as useful links, wikipedia and so on.

More details, please refer to Multilingual OCR Development Plan.

This project is released under Apache 2.0 license