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TimeYWL/PaddleOCR: Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)

English | 简体中文 | हिन्दी | 日本語 | 한국인 | Pу́сский язы́к

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

• 🔨2022.11 Add implementation of 4 cutting-edge algorithms：Text Detection DRRG, Text Recognition RFL, Image Super-Resolution Text Telescope，Handwritten Mathematical Expression Recognition CAN

• 2022.10 Release optimized JS version PP-OCRv3 model with 4.3M model size, 8x faster inference time, and a ready-to-use web demo

• 💥 Live Playback: Introduction to PP-StructureV2 optimization strategy. Scan the QR code below using WeChat, follow the PaddlePaddle official account and fill out the questionnaire to join the WeChat group, get the live link and 20G OCR learning materials (including PDF2Word application, 10 models in vertical scenarios, etc.)

• 🔥2022.8.24 Release PaddleOCR release/2.6

  • Release PP-StructureV2，with functions and performance fully upgraded, adapted to Chinese scenes, and new support for Layout Recovery and one line command to convert PDF to Word;
  • Layout Analysis optimization: model storage reduced by 95%, while speed increased by 11 times, and the average CPU time-cost is only 41ms;
  • Table Recognition optimization: 3 optimization strategies are designed, and the model accuracy is improved by 6% under comparable time consumption;
  • Key Information Extraction optimization：a visual-independent model structure is designed, the accuracy of semantic entity recognition is increased by 2.8%, and the accuracy of relation extraction is increased by 9.1%.

• 🔥2022.8 Release OCR scene application collection

  • Release 9 vertical models such as digital tube, LCD screen, license plate, handwriting recognition model, high-precision SVTR model, etc, covering the main OCR vertical applications in general, manufacturing, finance, and transportation industries.

• 2022.8 Add implementation of 8 cutting-edge algorithms

  • Text Detection: FCENet, DB++
  • Text Recognition: ViTSTR, ABINet, VisionLAN, SPIN, RobustScanner
  • Table Recognition: TableMaster

• 2022.5.9 Release PaddleOCR release/2.5

  • Release PP-OCRv3: With comparable speed, the effect of Chinese scene is further improved by 5% compared with PP-OCRv2, the effect of English scene is improved by 11%, and the average recognition accuracy of 80 language multilingual models is improved by more than 5%.
  • Release PPOCRLabelv2: Add the annotation function for table recognition task, key information extraction task and irregular text image.
  • Release interactive e-book "Dive into OCR", covers the cutting-edge theory and code practice of OCR full stack technology.

• 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

• For international developers, we regard PaddleOCR Discussions as our international community platform. All ideas and questions can be discussed here in English.

• For Chinese develops, Scan the QR code below with your Wechat, you can join the official technical discussion group. For richer community content, please refer to 中文README, looking forward to your participation.

• 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
    • PaddleCloud
    • Benchmark
• PP-Structure 🔥
  • Quick Start
  • Model Zoo
  • Model training
    • Layout Analysis
    • Table Recognition
    • Key Information Extraction
  • Inference and Deployment
    • Python Inference
    • C++ Inference
    • Serving
• Academic Algorithms
  • Text detection
  • Text recognition
  • End-to-end OCR
  • Table Recognition
  • Key Information Extraction
  • 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)
  • Layout Analysis
  • Table Recognition
  • Key Information Extraction
• Code Structure
• Visualization
• Community
• New language requests
• FAQ
• References
• License

• layout analysis + table recognition

• SER (Semantic entity recognition)

• RE (Relation Extraction)

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

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