Merge branch 'PaddlePaddle:main' into main

Author: self4m

README_en.md

@@ -45,7 +45,7 @@ In addition to providing an outstanding model library, PaddleOCR 3.0 also offers
 ## 📣 Recent updates
 🔥🔥2025.05.20: Official Release of **PaddleOCR v3.0**, including:
 - **PP-OCRv5**: High-Accuracy Text Recognition Model for All Scenarios - Instant Text from Images/PDFs.
-   1. 🌐 Single-model support for **five** text types - Seamlessly process **Simplified Chinese, Traditional Chinese, Simplified Chinese Pinyin, English** and **Japanse** within a single model.
+   1. 🌐 Single-model support for **five** text types - Seamlessly process **Simplified Chinese, Traditional Chinese, Simplified Chinese Pinyin, English** and **Japanese** within a single model.
    2. ✍️ Improved **handwriting recognition**: Significantly better at complex cursive scripts and non-standard handwriting.
    3. 🎯 **13-point accuracy gain** over PP-OCRv4, achieving state-of-the-art performance across a variety of real-world scenarios.
 

docs/version3.x/deployment/python_and_cpp_infer.md

@@ -0,0 +1,7 @@
+# 基于Python或C++预测引擎推理
+
+自 2.x 分支以来，基于 Python 或 C++ 的预测引擎推理一直是一项重要功能。该功能允许用户在无需安装 wheel 包的情况下加载OCR相关模型并进行推理。有关具体使用方法，请参考以下文档：
+
+* [基于Python预测引擎推理](../../version2.x/legacy/python_infer.md)
+* [基于C++预测引擎推理](../../version2.x/legacy/cpp_infer.md)
+* [支持的模型列表](../../version2.x/legacy/model_list_2.x.md)

docs/version3.x/deployment/serving.en.md

@@ -60,7 +60,7 @@ The command-line options related to serving are as follows:
 </tr>
 <tr>
 <td><code>--device</code></td>
-<td>Deployment device for the pipeline. Defaults to <code>cpu</code> (if GPU is unavailable) or <code>gpu</code> (if GPU is available).</td>
+<td>Deployment device for the pipeline. By default, a GPU will be used if available; otherwise, a CPU will be used."</td>
 </tr>
 <tr>
 <td><code>--host</code></td>

docs/version3.x/deployment/serving.md

@@ -60,7 +60,7 @@ INFO:     Uvicorn running on http://0.0.0.0:8080 (Press CTRL+C to quit)
 </tr>
 <tr>
 <td><code>--device</code></td>
-<td>产线部署设备。默认为 <code>cpu</code>（如 GPU 不可用）或 <code>gpu</code>（如 GPU 可用）。</td>
+<td>产线部署设备。默认情况下，当 GPU 可用时，将使用 GPU；否则使用 CPU。</td>
 </tr>
 <tr>
 <td><code>--host</code></td>

docs/version3.x/model_list.md

@@ -127,21 +127,21 @@ PaddleOCR 内置了多条产线，每条产线都包含了若干模块，每个
 </tr>
 <tr>
 <td>PP-OCRv5_server_rec</td>
-<td>-</td>
-<td>- / -</td>
-<td>- / -</td>
-<td>206 M</td>
+<td>86.38</td>
+<td>8.45/2.36</td>
+<td>122.69/122.69</td>
+<td>81 M</td>
 <td><a href="https://github.com/PaddlePaddle/PaddleX/blob/develop/paddlex/configs/modules/text_recognition/PP-OCRv5_server_rec.yaml">PP-OCRv5_server_rec.yaml</a></td>
-<td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/PP-OCRv5_server_rec_infer.tar">推理模型</a>/<a href="">训练模型</a></td>
+<td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/PP-OCRv5_server_rec_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PP-OCRv5_server_rec_pretrained.pdparams">训练模型</a></td>
 </tr>
 <tr>
 <td>PP-OCRv5_mobile_rec</td>
-<td>-</td>
-<td>- / -</td>
-<td>- / -</td>
-<td>137 M</td>
+<td>81.29</td>
+<td>1.46/5.43</td>
+<td>5.32/91.79</td>
+<td>16 M</td>
 <td><a href="https://github.com/PaddlePaddle/PaddleX/blob/develop/paddlex/configs/modules/text_recognition/PP-OCRv5_mobile_rec.yaml">PP-OCRv5_mobile_rec.yaml</a></td>
-<td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/PP-OCRv5_mobile_rec_infer.tar">推理模型</a>/<a href="">训练模型</a></td>
+<td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/PP-OCRv5_mobile_rec_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PP-OCRv5_mobile_rec_pretrained.pdparams">训练模型</a></td>
 </tr>
 <tr>
 <td>PP-OCRv4_server_rec_doc</td>

docs/version3.x/module_usage/module_overview.en.md

@@ -0,0 +1,3 @@
+# Module Overview
+
+A module is the smallest unit that implements basic functionality. Modules typically use a single model to accomplish specific tasks, such as text detection, image classification, and other basic functions. As fundamental building blocks, modules provide the necessary functional support for more complex application scenarios. This design approach allows users to flexibly select and combine different modules according to their needs, thereby simplifying the development process and enhancing development flexibility and efficiency.

docs/version3.x/module_usage/module_overview.md

@@ -0,0 +1,3 @@
+# 模块概述
+
+模块是实现基本功能的最小单位。模块通常使用单个模型去完成特定的任务，比如文本检测、图像分类等基本功能。模块作为基础构建单元，为更复杂的应用场景提供了必要的功能支持。这种设计方式使得用户可以根据需要灵活选择和组合不同的模块，从而简化了开发流程，并提高了开发的灵活性和效率。

docs/version3.x/module_usage/table_cells_detection.en.md

@@ -81,7 +81,7 @@ The Table Cell Detection Module is a key component of the table recognition task
 
 ## III. Quick Start
 
-> ❗ Before starting quickly, please first install the PaddleOCR wheel package. For details, please refer to the [installation tutorial](../installation.md).
+> ❗ Before starting quickly, please first install the PaddleOCR wheel package. For details, please refer to the [installation tutorial](../installation.en.md).
 
 You can quickly experience it with one command:
 
@@ -187,8 +187,8 @@ The relevant methods, parameters, etc., are described as follows:
 <td><code>float/dict</code></td>
 <td>
 <ul>
-  <li><b>float</b>, e.g., 0.2, indicates filtering out all bounding boxes with confidence lower than 0.2</li>
-  <li><b>dictionary</b>, where the key is of type <b>int</b> representing <code>cls_id</code>, and the value is of type <b>float</b> representing the threshold. For example, <code>{0: 0.45, 2: 0.48, 7: 0.4}</code> applies a threshold of 0.45 for category cls_id 0, 0.48 for category cls_id 1, and 0.4 for category cls_id 7</li>
+  <li><b>float</b>, e.g., 0.3, indicates filtering out all bounding boxes with confidence lower than 0.3</li>
+  <li><b>dictionary</b>, where the key is of type <b>int</b> representing <code>cls_id</code>, and the value is of type <b>float</b> representing the threshold. For example, <code>{0: 0.3}</code> applies a threshold of 0.3 for category cls_id 0</li>
 </ul>
 </td>
 <td>None</td>

docs/version3.x/module_usage/table_cells_detection.md

@@ -236,11 +236,11 @@ for res in output:
 <td><code>float/dict</code></td>
 <td>
 <ul>
-  <li><b>float</b>，如 0.2， 表示过滤掉所有阈值小于0.2的目标框</li>
-  <li><b>字典</b>，字典的key为<b>int</b>类型，代表<code>cls_id</code>，val为<b>float</b>类型阈值。如 <code>{0: 0.45, 2: 0.48, 7: 0.4}</code>，表示对cls_id为0的类别应用阈值0.45、cls_id为1的类别应用阈值0.48、cls_id为7的类别应用阈值0.4</li>
+  <li><b>float</b>，如 0.3， 表示过滤掉所有阈值小于0.3的目标框</li>
+  <li><b>字典</b>，字典的key为<b>int</b>类型，代表<code>cls_id</code>，val为<b>float</b>类型阈值。如 <code>{0: 0.3}</code>，表示对cls_id为0的类别应用阈值0.3</li>
 </ul>
 </td>
-<td>无</td>
+<td>None</td>
 </tr>
 </table>
 

docs/version3.x/module_usage/table_classification.en.md

@@ -74,7 +74,7 @@ The Table Classification Module is a key component in computer vision systems, r
 
 ## 3. Quick Start
 
-> ❗ Before starting quickly, please first install the PaddleOCR wheel package. For details, please refer to the [installation tutorial](../installation.md).
+> ❗ Before starting quickly, please first install the PaddleOCR wheel package. For details, please refer to the [installation tutorial](../installation.en.md).
 
 You can quickly experience it with one command: