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SWHL d82132f510 Add processing logic for single line text.

2022-07-05 10:01:17 +08:00

change_log_en.md

Add processing logic for single line text.

2022-07-05 10:01:17 +08:00

change_log.md

Add processing logic for single line text.

2022-07-05 10:01:17 +08:00

FAQ.md

Update openvino infer

2022-06-25 20:59:02 +08:00

README_en.md

Add processing logic for single line text.

2022-07-05 10:01:17 +08:00

README_en.md

RapidOCR

简体中文 | English

Contents

RapidOCR
- Introduction
- Recently updates(more)
- FAQ
- SDK compilation status
- Online demo
- Directory structure
- Current Progress
- Model related
  - [Download models( Google Drive|Baidu NetDisk )](#download-models-google-drivebaidu-netdisk-)
  - Model to onnx
  - Compared
    - Text Det
    - Text Recognition
- PaddleOCR-FAQ
- Original initiator and start-up author
- Acknowledgements
- Authorization
- Contact us
- Demo

Introduction

Completely open source, free and support offline deployment of multi-platform and multi-language OCR SDK
Chinese Advertising: Welcome to join our QQ group to download the model and test program, QQ group number: 887298230
Cause: Baidu paddlepaddle engineering is not very good, in order to facilitate everyone to perform OCR reasoning on various terminals, we convert it to onnx format, use ``python/c++/java/swift/c#'' to change It is ported to various platforms.
Name Source: Light, fast, economical and smart. OCR technology based on deep learning technology focuses on artificial intelligence advantages and small models, with speed as the mission and effect as the leading role.
Based on Baidu's open source PaddleOCR model and training, anyone can use this inference library, or use Baidu's paddlepaddle framework for model optimization according to their own needs.

Recently updates(more)

😁2022-07-05 update:

Add the ability to handle single line text, for single line text, you can set your own threshold, but the detection module, direct recognition can be. For details, see README
Optimize some code logic of python, more elegant and concise.

🏝2022-06-30 update:

In the python inference section, add a configuration option for whether to use GPU inference, which can be used with one click if the onnxruntime-gpu version is correctly installed (Fix issue#30)
The specific GPU-based reasoning will need to wait for me to sort it out and update it later.
For details, see: [onnxruntime-gpu version reasoning configuration](./python/README.md#onnxruntime-gpu version reasoning configuration)

📌2022-06-25 update:

Reorganize some of the python inference code, put all the common adjustment parameters into the yaml file, easy to adjust, easier to use, see: README
The old inference code is located in the branch: old_python_infer

🍿2022-05-15 update

Add the ONNX model converted from the PaddleOCR v3 rec model, just go to the network disk to download and replace it. (Baidu Netdisk | Google Drive)
Added a comparison table of the effects of each version of the text recognition model. For details, click [Comparison of the effects of various versions of ONNX models] (#Comparison of the effects of various versions of onnx models). The text recognition model of v3 is not as good as the previous one in terms of the indicators on the test set constructed by itself.

😀2022-05-12 upadte

Add the ONNX model converted from the PaddleOCR v3 det model, download it directly from the network disk, and replace it. (Baidu Netdisk | Google Drive)
Added a comparison table of text detection model effects of various versions. For details, click [Comparison of the effects of various versions of ONNX models] (#Comparison of the effects of various versions of onnx models). The text detection model of v3 is better than the previous v2 in terms of the indicators on the test set constructed by itself, and it is recommended to use it.

FAQ

SDK compilation status

Since ubuntu users are all commercial users and have the ability to compile, pre-compiled packages are not provided for the time being, and they can be compiled by themselves.

Platform	Compilation Status	Offer Status
Windows x86/x64		Download Link
Linux x64		Not available yet, compile by yourself

Online demo

Web demo
The model combination used in the demo is: ch_PP-OCRv3_det + ch_ppocr_mobile_v2.0_cls + ch_ppocr_mobile_v2.0_rec
Environment: 4 Core AMD EPYC 7K62 48-Core Processor
Gif Demo:

Directory structure

click to expand

RapidOCR
    ├── android         # Android project directory
    ├── api4cpp         # C language cross-platform interface library source code directory, directly compile with CMakelists.txt under the root
    ├── assets          # Some pictures for demonstration, not a test set
    ├── commonlib       # common library
    ├── cpp             # C++-based project folder
    ├── datasets        # Additional training datasets
    ├── dotnet          # .Net program directory
    ├── FAQ.md          # Some questions and answers
    ├── images          # Test pictures, two typical test pictures, one is a natural scene, the other is a long text
    ├── include         # The header file directory when compiling the c language interface library
    ├── ios             # Apple mobile phone platform project directory
    ├── jvm             # java-based project directory
    ├── lib             # Compilation library file directory, used to compile the C language interface library. Binary files are not uploaded by default
    ├── ocrweb          # Based on python and Flask web
    ├── python          # python reasoning code directory
    ├── release         #
    └── tools           # Some conversion scripts and the like

Current Progress

C++ example (Windows/Linux/macOS): demo
Jvm example (Java/Kotlin): demo
.Net example (C#): demo
Android example: demo
python example: demo
IOS example: waiting for someone to contribute code
Rewrite the C++ reasoning code according to the python version to improve the reasoning effect, and add support for gif/tga/webp format pictures

Download models( Google Drive|Baidu NetDisk )

Model to onnx

⭐PaddleOCRModelConverter by @SWHL
Paddle2OnnxConvertor by @benjaminwan
Teach you to use ONNXRunTime to deploy PP-OCR by @Channingss

Compared

Text Det

test dataset: Chinese and English (111, including cards, documents and natural images)

Model	infer_Speed(s/img)	precision	recall	hmean	Model Size
ch_ppocr_mobile_v2.0_det_infer.onnx	0.4345742	0.7277	0.8413	0.7785	2.3M
ch_PP-OCRv2_det_infer.onnx	0.5116553	0.7817	0.8472	0.8123	2.3M
ch_PP-OCRv3_det_infer.onnx	0.5723512	0.7740	0.8837	0.8237	2.4M

Text Recognition

test dataset: Chinese and English (168)

Model	infer_speed(s/img)	Score	Exact_Match	Char_Match	Model Size
ch_ppocr_mobile_v2.0_rec_infer.onnx	0.0111	0.7287	0.5595	0.8979	4.3M
ch_PP-OCRv2_rec_infer.onnx	0.0193	0.6955	0.4881	0.9029	8.0M
ch_PP-OCRv3_rec_infer.onnx	0.0145	0.5537	0.3274	0.7800	11M
ch_PP-OCRv3_rec_train_student.onnx	0.0157	0.5537	0.3274	0.7800	11M
ch_PP-OCRv3_rec_train_teacher.onnx	0.0140	0.5381	0.3095	0.7667	11M

PaddleOCR-FAQ

Original initiator and start-up author

Acknowledgements

Many thanks to DeliciaLaniD for fixing the misplaced start position of scan animation in ocrweb.
Many thanks to zhsunlight for the suggestion about parametric call GPU inference.

Authorization

The copyright of the OCR model belongs to Baidu, and the copyright of other engineering codes belongs to the owner of this warehouse.
This software is licensed under LGPL. You are welcome to contribute code, submit an issue or even pr.