yujunjun/PaddleOCR
1
0
Fork 0
mirror of https://github.com/PaddlePaddle/PaddleOCR.git synced 2025-06-26 21:24:27 +00:00
Code Issues Packages Projects Releases Wiki Activity

PP-OCRv5 Docs (#15201)

Browse Source 
* update PP-OCRv5 docs

* update

* update docs
This commit is contained in:
cuicheng01 2025-05-20 06:12:44 +08:00 committed by GitHub
parent 8b2c757c2b
commit 18d0fed174
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
2 changed files with 410 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

203
docs/version3.x/algorithm/PP-OCRv5/PP-OCRv5.en.md Normal file
View File

@ -0,0 +1,203 @@
# Introduction to PP-OCRv5
**PP-OCRv5** is the new generation text recognition solution of PP-OCR, focusing on multi-scenario and multi-text type recognition. In terms of text types, PP-OCRv5 supports 5 major mainstream text types: Simplified Chinese, Chinese Pinyin, Traditional Chinese, English, and Japanese. For scenarios, PP-OCRv5 has upgraded recognition capabilities for challenging scenarios such as complex Chinese and English handwriting, vertical text, and uncommon characters. On internal complex evaluation sets across multiple scenarios, PP-OCRv5 achieved a 13 percentage point end-to-end improvement over PP-OCRv4.
<div align="center">
<img src="https://raw.githubusercontent.com/cuicheng01/PaddleX_doc_images/refs/heads/main/images/paddleocr/PP-OCRv5/algorithm_ppocrv5.png" width="600"/>
</div>
# Key Metrics
### 1. Text Detection Metrics
<table>
<thead>
<tr>
<th>Model</th>
<th>Handwritten Chinese</th>
<th>Handwritten English</th>
<th>Printed Chinese</th>
<th>Printed English</th>
<th>Traditional Chinese</th>
<th>Ancient Text</th>
<th>Japanese</th>
<th>General Scenario</th>
<th>Pinyin</th>
<th>Rotation</th>
<th>Distortion</th>
<th>Artistic Text</th>
<th>Average</th>
</tr>
</thead>
<tbody>
<tr>
<td><b>PP-OCRv5_server_det</b></td>
<td><b>0.803</b></td>
<td><b>0.841</b></td>
<td><b>0.945</b></td>
<td><b>0.917</b></td>
<td><b>0.815</b></td>
<td><b>0.676</b></td>
<td><b>0.772</b></td>
<td><b>0.797</b></td>
<td><b>0.671</b></td>
<td><b>0.8</b></td>
<td><b>0.876</b></td>
<td><b>0.673</b></td>
<td><b>0.827</b></td>
</tr>
<tr>
<td>PP-OCRv4_server_det</td>
<td>0.706</td>
<td>0.249</td>
<td>0.888</td>
<td>0.690</td>
<td>0.759</td>
<td>0.473</td>
<td>0.685</td>
<td>0.715</td>
<td>0.542</td>
<td>0.366</td>
<td>0.775</td>
<td>0.583</td>
<td>0.662</td>
</tr>
<tr>
<td><b>PP-OCRv5_mobile_det</b></td>
<td><b>0.744</b></td>
<td><b>0.777</b></td>
<td><b>0.905</b></td>
<td><b>0.910</b></td>
<td><b>0.823</b></td>
<td><b>0.581</b></td>
<td><b>0.727</b></td>
<td><b>0.721</b></td>
<td><b>0.575</b></td>
<td><b>0.647</b></td>
<td><b>0.827</b></td>
<td>0.525</td>
<td><b>0.770</b></td>
</tr>
<tr>
<td>PP-OCRv4_mobile_det</td>
<td>0.583</td>
<td>0.369</td>
<td>0.872</td>
<td>0.773</td>
<td>0.663</td>
<td>0.231</td>
<td>0.634</td>
<td>0.710</td>
<td>0.430</td>
<td>0.299</td>
<td>0.715</td>
<td><b>0.549</b></td>
<td>0.624</td>
</tr>
</tbody>
</table>
Compared to PP-OCRv4, PP-OCRv5 shows significant improvement in all detection scenarios, especially in handwriting, ancient texts, and Japanese detection capabilities.
### 2. Text Recognition Metrics
<div align="center">
<img src="https://raw.githubusercontent.com/cuicheng01/PaddleX_doc_images/refs/heads/main/images/paddleocr/PP-OCRv5/ocrv5_rec_acc.png" width="600"/>
</div>
<table>
<thead>
<tr>
<th>Evaluation Set Category</th>
<th>Handwritten Chinese</th>
<th>Handwritten English</th>
<th>Printed Chinese</th>
<th>Printed English</th>
<th>Traditional Chinese</th>
<th>Ancient Text</th>
<th>Japanese</th>
<th>Confusable Characters</th>
<th>General Scenario</th>
<th>Pinyin</th>
<th>Vertical Text</th>
<th>Artistic Text</th>
<th>Weighted Average</th>
</tr>
</thead>
<tbody>
<tr>
<td>PP-OCRv5_server_rec</td>
<td><b>0.5807</b></td>
<td><b>0.5806</b></td>
<td><b>0.9013</b></td>
<td><b>0.8679</b></td>
<td><b>0.7472</b></td>
<td><b>0.6039</b></td>
<td><b>0.7372</b></td>
<td><b>0.5946</b></td>
<td><b>0.8384</b></td>
<td><b>0.7435</b></td>
<td><b>0.9314</b></td>
<td><b>0.6397</b></td>
<td><b>0.8401</b></td>
</tr>
<tr>
<td>PP-OCRv4_server_rec</td>
<td>0.3626</td>
<td>0.2661</td>
<td>0.8486</td>
<td>0.6677</td>
<td>0.4097</td>
<td>0.3080</td>
<td>0.4623</td>
<td>0.5028</td>
<td>0.8362</td>
<td>0.2694</td>
<td>0.5455</td>
<td>0.5892</td>
<td>0.5735</td>
</tr>
<tr>
<td>PP-OCRv5_mobile_rec</td>
<td><b>0.4166</b></td>
<td><b>0.4944</b></td>
<td><b>0.8605</b></td>
<td><b>0.8753</b></td>
<td><b>0.7199</b></td>
<td><b>0.5786</b></td>
<td><b>0.7577</b></td>
<td><b>0.5570</b></td>
<td>0.7703</td>
<td><b>0.7248</b></td>
<td><b>0.8089</b></td>
<td>0.5398</td>
<td><b>0.8015</b></td>
</tr>
<tr>
<td>PP-OCRv4_mobile_rec</td>
<td>0.2980</td>
<td>0.2550</td>
<td>0.8398</td>
<td>0.6598</td>
<td>0.3218</td>
<td>0.2593</td>
<td>0.4724</td>
<td>0.4599</td>
<td><b>0.8106</b></td>
<td>0.2593</td>
<td>0.5924</td>
<td><b>0.5555</b></td>
<td>0.5301</td>
</tr>
</tbody>
</table>
A single model can cover multiple languages and text types, with recognition accuracy significantly ahead of previous generation products and mainstream open-source solutions.
# PP-OCRv5 Demo Examples
# Deployment and Secondary Development
* **Multiple System Support**: Compatible with mainstream operating systems including Windows, Linux, and Mac.
* **Multiple Hardware Support**: Besides NVIDIA GPUs, it also supports inference and deployment on Intel CPU, Kunlun chips, Ascend, and other new hardware.
* **High-Performance Inference Plugin**: Recommended to combine with high-performance inference plugins to further improve inference speed. See [High-Performance Inference Guide](../../deployment/high_performance_inference.md) for details.
* **Service Deployment**: Supports highly stable service deployment solutions. See [Service Deployment Guide](../../deployment/serving.md) for details.
* **Secondary Development Capability**: Supports custom dataset training, dictionary extension, and model fine-tuning. Example: To add Korean recognition, you can extend the dictionary and fine-tune the model, seamlessly integrating into existing production lines. See [Text Recognition Module Usage Tutorial](../../module_usage/text_recognition.md) for details.

207
docs/version3.x/algorithm/PP-OCRv5/PP-OCRv5.md Normal file
View File

@ -0,0 +1,207 @@
# 一、PP-OCRv5简介
**PP-OCRv5** 是PP-OCR新一代文字识别解决方案，该方案聚焦于多场景、多文字类型的文字识别。在文字类型方面，PP-OCRv5支持简体中文、中文拼音、繁体中文、英文、日文5大主流文字类型，在场景方面，PP-OCRv5升级了中英复杂手写体、竖排文本、生僻字等多种挑战性场景的识别能力。在内部多场景复杂评估集上，PP-OCRv5较PP-OCRv4端到端提升13个百分点。
<div align="center">
<img src="https://raw.githubusercontent.com/cuicheng01/PaddleX_doc_images/refs/heads/main/images/paddleocr/PP-OCRv5/algorithm_ppocrv5.png" width="600"/>
</div>
# 二、关键指标
### 1. 文本检测指标
<table>
<thead>
<tr>
<th>模型</th>
<th>手写中文</th>
<th>手写英文</th>
<th>印刷中文</th>
<th>印刷英文</th>
<th>繁体中文</th>
<th>古籍文本</th>
<th>日文</th>
<th>通用场景</th>
<th>拼音</th>
<th>旋转</th>
<th>扭曲</th>
<th>艺术字</th>
<th>平均</th>
</tr>
</thead>
<tbody>
<tr>
<td><b>PP-OCRv5_server_det</b></td>
<td><b>0.803</b></td>
<td><b>0.841</b></td>
<td><b>0.945</b></td>
<td><b>0.917</b></td>
<td><b>0.815</b></td>
<td><b>0.676</b></td>
<td><b>0.772</b></td>
<td><b>0.797</b></td>
<td><b>0.671</b></td>
<td><b>0.8</b></td>
<td><b>0.876</b></td>
<td><b>0.673</b></td>
<td><b>0.827</b></td>
</tr>
<tr>
<td>PP-OCRv4_server_det</td>
<td>0.706</td>
<td>0.249</td>
<td>0.888</td>
<td>0.690</td>
<td>0.759</td>
<td>0.473</td>
<td>0.685</td>
<td>0.715</td>
<td>0.542</td>
<td>0.366</td>
<td>0.775</td>
<td>0.583</td>
<td>0.662</td>
</tr>
<tr>
<td><b>PP-OCRv5_mobile_det</b></td>
<td><b>0.744</b></td>
<td><b>0.777</b></td>
<td><b>0.905</b></td>
<td><b>0.910</b></td>
<td><b>0.823</b></td>
<td><b>0.581</b></td>
<td><b>0.727</b></td>
<td><b>0.721</b></td>
<td><b>0.575</b></td>
<td><b>0.647</b></td>
<td><b>0.827</b></td>
<td>0.525</td>
<td><b>0.770</b></td>
</tr>
<tr>
<td>PP-OCRv4_mobile_det</td>
<td>0.583</td>
<td>0.369</td>
<td>0.872</td>
<td>0.773</td>
<td>0.663</td>
<td>0.231</td>
<td>0.634</td>
<td>0.710</td>
<td>0.430</td>
<td>0.299</td>
<td>0.715</td>
<td><b>0.549</b></td>
<td>0.624</td>
</tr>
</tbody>
</table>
对比PP-OCRv4，PP-OCRv5在所有检测场景下均有明显提升，尤其在手写、古籍、日文检测能力上表现更优。
### 2. 文本识别指标
<div align="center">
<img src="https://raw.githubusercontent.com/cuicheng01/PaddleX_doc_images/refs/heads/main/images/paddleocr/PP-OCRv5/ocrv5_rec_acc.png" width="600"/>
</div>
<table>
<thead>
<tr>
<th>评估集类别</th>
<th>手写中文</th>
<th>手写英文</th>
<th>印刷中文</th>
<th>印刷英文</th>
<th>繁体中文</th>
<th>古籍文本</th>
<th>日文</th>
<th>易混淆字符</th>
<th>通用场景</th>
<th>拼音</th>
<th>竖直文本</th>
<th>艺术字</th>
<th>加权平均</th>
</tr>
</thead>
<tbody>
<tr>
<td>PP-OCRv5_server_rec</td>
<td><b>0.5807</b></td>
<td><b>0.5806</b></td>
<td><b>0.9013</b></td>
<td><b>0.8679</b></td>
<td><b>0.7472</b></td>
<td><b>0.6039</b></td>
<td><b>0.7372</b></td>
<td><b>0.5946</b></td>
<td><b>0.8384</b></td>
<td><b>0.7435</b></td>
<td><b>0.9314</b></td>
<td><b>0.6397</b></td>
<td><b>0.8401</b></td>
</tr>
<tr>
<td>PP-OCRv4_server_rec</td>
<td>0.3626</td>
<td>0.2661</td>
<td>0.8486</td>
<td>0.6677</td>
<td>0.4097</td>
<td>0.3080</td>
<td>0.4623</td>
<td>0.5028</td>
<td>0.8362</td>
<td>0.2694</td>
<td>0.5455</td>
<td>0.5892</td>
<td>0.5735</td>
</tr>
<tr>
<td>PP-OCRv5_mobile_rec</td>
<td><b>0.4166</b></td>
<td><b>0.4944</b></td>
<td><b>0.8605</b></td>
<td><b>0.8753</b></td>
<td><b>0.7199</b></td>
<td><b>0.5786</b></td>
<td><b>0.7577</b></td>
<td><b>0.5570</b></td>
<td>0.7703</td>
<td><b>0.7248</b></td>
<td><b>0.8089</b></td>
<td>0.5398</td>
<td><b>0.8015</b></td>
</tr>
<tr>
<td>PP-OCRv4_mobile_rec</td>
<td>0.2980</td>
<td>0.2550</td>
<td>0.8398</td>
<td>0.6598</td>
<td>0.3218</td>
<td>0.2593</td>
<td>0.4724</td>
<td>0.4599</td>
<td><b>0.8106</b></td>
<td>0.2593</td>
<td>0.5924</td>
<td><b>0.5555</b></td>
<td>0.5301</td>
</tr>
</tbody>
</table>
单模型即可覆盖多语言和多类型文本，识别精度大幅领先前代产品和主流开源方案。
# 三、PP-OCRv5 Demo示例
# 四、部署与二次开发
* **多系统支持**：兼容Windows、Linux、Mac等主流操作系统。
* **多硬件支持**：除了英伟达GPU外，还支持Intel CPU、昆仑芯、昇腾等新硬件推理和部署。
* **高性能推理插件**：推荐结合高性能推理插件进一步提升推理速度，详见[高性能推理指南](../../deployment/high_performance_inference.md)。
* **服务化部署**：支持高稳定性服务化部署方案，详见[服务化部署指南](../../deployment/serving.md)。
* **二次开发能力**：支持自定义数据集训练、字典扩展、模型微调。举例：如需增加韩文识别，可扩展字典并微调模型，无缝集成到现有产线，详见[文本识别模块使用教程](../../module_usage/text_recognition.md)