Giter Site home page Giter Site logo

scorpiusjin / dive-into-ocr Goto Github PK

View Code? Open in Web Editor NEW

This project forked from paddleocr-community/dive-into-ocr

0.0 0.0 0.0 17.13 MB

“Dive Into OCR” is a textbook developed by the PaddleOCR community that integrates OCR theory and practice.

License: Apache License 2.0

Jupyter Notebook 100.00%

dive-into-ocr's Introduction

English | 简体中文

E-book: Dive Into OCR

"Dive Into OCR" is a textbook that combines OCR theory and practice, written by the PaddleOCR team, the main features are as follows:

  • OCR full-stack technology covering text detection, recognition and document analysis
  • Closely integrate theory and practice, cross the code implementation gap, and supporting instructional videos
  • Jupyter Notebook textbook, flexibly modifying code for instant results

Structure

  • The first part is the preliminary knowledge of the book, including the knowledge index and resource links needed in the process of positioning and using the book content of the book

  • The second part is chapters 4-8 of the book, which introduce the concepts, applications, and industry practices related to the detection and identification capabilities of the OCR engine. In the "Introduction to OCR Technology", the application scenarios and challenges of OCR, the basic concepts of technology, and the pain points in industrial applications are comprehensively explained. Then, in the two chapters of "Text Detection" and "Text Recognition", the two basic tasks of OCR are introduced. In each chapter, an algorithm is accompanied by a detailed explanation of the code and practical exercises. Chapters 6 and 7 are a detailed introduction to the PP-OCR series model, PP-OCR is a set of OCR systems for industrial applications, on the basis of the basic detection and identification model, after a series of optimization strategies to achieve the general field of industrial SOTA model, while opening up a variety of predictive deployment solutions, enabling enterprises to quickly land OCR applications.

  • The third part is chapter 9-12 of the book, which introduces applications other than the two-stage OCR engine, including data synthesis, preprocessing algorithm, and end-to-end model, focusing on OCR's layout analysis, table recognition, visual document question and answer capabilities in the document scene, and also through the combination of algorithm and code, so that readers can deeply understand and apply.

Address

dive-into-ocr's People

Contributors

evezerest avatar swhl avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.