Revert "[cherry-pick] Cherry pick visualize parameter (#4258)" (#4324)

This reverts commit d2ccedc.

Author: boomercat

docs/CHANGELOG.en.md

@@ -6,34 +6,34 @@ comments: true
 
 ## Latest Version Information
 
-### PaddleX v3.0.0(5.20/2025)
+### PaddleX v3.0.0(5.20/2025) 
 
 Core upgrades are as follows:
 
-- **Rich Model Library:**
-  - **Extensive Model Coverage:** PaddleX 3.0 includes **270+ models**, covering diverse scenarios such as image/video classification/detection/segmentation, OCR, speech recognition, time series analysis, and more.
-  - **Mature Solutions:** Built on this robust model library, PaddleX 3.0 offers **critical and production-ready AI solutions**, including general document parsing, key information extraction, document understanding, table recognition, and general image recognition.
-
-- **Unified Inference API & Enhanced Deployment Capabilities:**
-  - **Standardized Inference Interface:** Reduces API fragmentation across model types, lowering the learning curve for users and accelerating enterprise adoption.
-  - **Multi-Model Composition:** Complex tasks can be efficiently tackled by combining different models, achieving synergistic performance (1+1>2).
-  - **Upgraded Deployment:** Unified commands now manage deployments for diverse models, supporting **multi-GPU inference** and **multi-instance serving deployments**.
-
-- **Full Compatibility with PaddlePaddle Framework 3.0:**
-  - **Leveraging New Paddle 3.0 Features:**
-    - Compiler-accelerated training: Enable by appending `-o Global.dy2st=True` to training commands. **Most GPU-based models see >10% speed gains, with some exceeding 30%.**
-    - Inference upgrades: Full adaptation to Paddle 3.0’s Program Intermediate Representation (PIR) enhances flexibility and compatibility. Static graph models now use `xxx.json` instead of `xxx.pdmodel`.
-  - **ONNX Model Support:** Seamless format conversion via the Paddle2ONNX plugin.
-
-- **Flagship Capabilities:**
-  - **PP-OCRv5:** Powers **multi-hardware inference, multi-backend support, and serving deployments** for this industry-leading OCR system.
-  - **PP-StructureV3:** Orchestrates **15+ models** in hybrid (serial/parallel) pipelines, achieving **SOTA accuracy on OmniDocBench**.
-  - **PP-ChatOCRv4:** Integrates with **PP-DocBee2 and ERNIE 4.5Turbo**, boosting key information extraction accuracy by **15.7 percentage points** over the previous generation.
-
-- **Multi-Hardware Support:**
-  - **Broad Compatibility:** Training and inference supported on **NVIDIA, Intel, Apple M-series, Kunlunxin, Ascend, Cambricon, Hygon, Enflame**, and more.
-  - **Ascend-Optimized:** **200+ fully adapted models**, including **21 OM-accelerated inference models**, plus key solutions like PP-OCRv5 and PP-StructureV3.
-  - **Kunlunxin-Optimized:** Critical classification, detection, and OCR models (including PP-OCRv5) are fully supported.
+- **Rich Model Library:**  
+  - **Extensive Model Coverage:** PaddleX 3.0 includes **270+ models**, covering diverse scenarios such as image/video classification/detection/segmentation, OCR, speech recognition, time series analysis, and more.  
+  - **Mature Solutions:** Built on this robust model library, PaddleX 3.0 offers **critical and production-ready AI solutions**, including general document parsing, key information extraction, document understanding, table recognition, and general image recognition.  
+
+- **Unified Inference API & Enhanced Deployment Capabilities:**  
+  - **Standardized Inference Interface:** Reduces API fragmentation across model types, lowering the learning curve for users and accelerating enterprise adoption.  
+  - **Multi-Model Composition:** Complex tasks can be efficiently tackled by combining different models, achieving synergistic performance (1+1>2).  
+  - **Upgraded Deployment:** Unified commands now manage deployments for diverse models, supporting **multi-GPU inference** and **multi-instance serving deployments**.  
+
+- **Full Compatibility with PaddlePaddle Framework 3.0:**  
+  - **Leveraging New Paddle 3.0 Features:**  
+    - Compiler-accelerated training: Enable by appending `-o Global.dy2st=True` to training commands. **Most GPU-based models see >10% speed gains, with some exceeding 30%.**  
+    - Inference upgrades: Full adaptation to Paddle 3.0’s Program Intermediate Representation (PIR) enhances flexibility and compatibility. Static graph models now use `xxx.json` instead of `xxx.pdmodel`.  
+  - **ONNX Model Support:** Seamless format conversion via the Paddle2ONNX plugin.  
+
+- **Flagship Capabilities:**  
+  - **PP-OCRv5:** Powers **multi-hardware inference, multi-backend support, and serving deployments** for this industry-leading OCR system.  
+  - **PP-StructureV3:** Orchestrates **15+ models** in hybrid (serial/parallel) pipelines, achieving **SOTA accuracy on OmniDocBench**.  
+  - **PP-ChatOCRv4:** Integrates with **PP-DocBee2 and ERNIE 4.5Turbo**, boosting key information extraction accuracy by **15.7 percentage points** over the previous generation.  
+
+- **Multi-Hardware Support:**  
+  - **Broad Compatibility:** Training and inference supported on **NVIDIA, Intel, Apple M-series, Kunlunxin, Ascend, Cambricon, Hygon, Enflame**, and more.  
+  - **Ascend-Optimized:** **200+ fully adapted models**, including **21 OM-accelerated inference models**, plus key solutions like PP-OCRv5 and PP-StructureV3.  
+  - **Kunlunxin-Optimized:** Critical classification, detection, and OCR models (including PP-OCRv5) are fully supported.  
 
 ### PaddleX v3.0.0rc1(4.22/2025)
 

docs/CHANGELOG.md

@@ -7,7 +7,7 @@ comments: true
 ## 最新版本信息
 
 
-### PaddleX v3.0.0(5.20/2025)
+### PaddleX v3.0.0(5.20/2025) 
 
 **丰富的模型库：**
 - **模型丰富：** PaddleX3.0 包含270+模型，涵盖了图像（视频）分类/检测/分割、OCR、语音识别、时序等多种场景。

docs/pipeline_usage/tutorials/cv_pipelines/face_recognition.en.md

@@ -917,26 +917,6 @@ Below is the API reference for basic service deployment and multi-language servi
 <td>Yes</td>
 </tr>
 <tr>
-<td><code>visualize</code></td>
-<td><code>boolean</code> | <code>null</code></td>
-<td>
-Whether to return the final visualization image and intermediate images during the processing.<br/>
-<ul style="margin: 0 0 0 1em; padding-left: 0em;">
-<li>If <code>true</code> is provided: return images.</li>
-<li>If <code>false</code> is provided: do not return any images.</li>
-<li>If this parameter is omitted from the request body, or if <code>null</code> is explicitly passed, the behavior will follow the value of <code>Serving.visualize</code> in the pipeline configuration.</li>
-</ul>
-<br/>
-For example, adding the following setting to the pipeline config file:<br/>
-<pre><code>Serving:
-  visualize: False
-</code></pre>
-will disable image return by default. This behavior can be overridden by explicitly setting the <code>visualize</code> parameter in the request.<br/>
-If neither the request body nor the configuration file is set (If <code>visualize</code> is set to <code>null</code> in the request and  not defined in the configuration file), the image is returned by default.
-</td>
-<td>No</td>
-</tr>
-<tr>
 <td><code>indexKey</code></td>
 <td><code>string</code></td>
 <td>The key corresponding to the index. Provided by the <code>buildIndex</code> operation.</td>

docs/pipeline_usage/tutorials/cv_pipelines/face_recognition.md

@@ -914,23 +914,6 @@ data_root             # 数据集根目录，目录名称可以改变
 <td>是</td>
 </tr>
 <tr>
-<td><code>visualize</code></td>
-<td><code>boolean</code> | <code>null</code></td>
-<td>是否返回可视化结果图以及处理过程中的中间图像等。
-<ul style="margin: 0 0 0 1em; padding-left: 0em;">
-<li>传入 <code>true</code>：返回图像。</li>
-<li>传入 <code>false</code>：不返回图像。</li>
-<li>若请求体中未提供该参数或传入 <code>null</code>：遵循产线配置文件<code>Serving.visualize</code> 的设置。</li>
-</ul>
-<br/>例如，在产线配置文件中添加如下字段：<br/>
-<pre><code>Serving:
-  visualize: False
-</code></pre>
-将默认不返回图像，通过请求体中的<code>visualize</code>参数可以覆盖默认行为。如果请求体和配置文件中均未设置（或请求体传入<code>null</code>、配置文件中未设置），则默认返回图像。
-</td>
-<td>否</td>
-</tr>
-<tr>
 <td><code>indexKey</code></td>
 <td><code>string</code></td>
 <td>索引对应的键。由<code>buildIndex</code>操作提供。</td>

docs/pipeline_usage/tutorials/cv_pipelines/general_image_recognition.en.md

@@ -872,26 +872,6 @@ Below is the API reference for basic service deployment and multi-language servi
 <td>Yes</td>
 </tr>
 <tr>
-<td><code>visualize</code></td>
-<td><code>boolean</code> | <code>null</code></td>
-<td>
-Whether to return the final visualization image and intermediate images during the processing.<br/>
-<ul style="margin: 0 0 0 1em; padding-left: 0em;">
-<li>If <code>true</code> is provided: return images.</li>
-<li>If <code>false</code> is provided: do not return any images.</li>
-<li>If this parameter is omitted from the request body, or if <code>null</code> is explicitly passed, the behavior will follow the value of <code>Serving.visualize</code> in the pipeline configuration.</li>
-</ul>
-<br/>
-For example, adding the following setting to the pipeline config file:<br/>
-<pre><code>Serving:
-  visualize: False
-</code></pre>
-will disable image return by default. This behavior can be overridden by explicitly setting the <code>visualize</code> parameter in the request.<br/>
-If neither the request body nor the configuration file is set (If <code>visualize</code> is set to <code>null</code> in the request and  not defined in the configuration file), the image is returned by default.
-</td>
-<td>No</td>
-</tr>
-<tr>
 <td><code>indexKey</code></td>
 <td><code>string</code></td>
 <td>The key corresponding to the index. Provided by the <code>buildIndex</code> operation.</td>

docs/pipeline_usage/tutorials/cv_pipelines/general_image_recognition.md

@@ -870,23 +870,6 @@ data_root             # 数据集根目录，目录名称可以改变
 <td>是</td>
 </tr>
 <tr>
-<td><code>visualize</code></td>
-<td><code>boolean</code> | <code>null</code></td>
-<td>是否返回可视化结果图以及处理过程中的中间图像等。
-<ul style="margin: 0 0 0 1em; padding-left: 0em;">
-<li>传入 <code>true</code>：返回图像。</li>
-<li>传入 <code>false</code>：不返回图像。</li>
-<li>若请求体中未提供该参数或传入 <code>null</code>：遵循产线配置文件<code>Serving.visualize</code> 的设置。</li>
-</ul>
-<br/>例如，在产线配置文件中添加如下字段：<br/>
-<pre><code>Serving:
-  visualize: False
-</code></pre>
-将默认不返回图像，通过请求体中的<code>visualize</code>参数可以覆盖默认行为。如果请求体和配置文件中均未设置（或请求体传入<code>null</code>、配置文件中未设置），则默认返回图像。
-</td>
-<td>否</td>
-</tr>
-<tr>
 <td><code>indexKey</code></td>
 <td><code>string</code></td>
 <td>索引对应的键。由<code>buildIndex</code>操作提供。</td>

docs/pipeline_usage/tutorials/cv_pipelines/human_keypoint_detection.en.md

@@ -653,26 +653,6 @@ Below are the API references and multi-language service invocation examples for
 <td>Yes</td>
 </tr>
 <tr>
-<td><code>visualize</code></td>
-<td><code>boolean</code> | <code>null</code></td>
-<td>
-Whether to return the final visualization image and intermediate images during the processing.<br/>
-<ul style="margin: 0 0 0 1em; padding-left: 0em;">
-<li>If <code>true</code> is provided: return images.</li>
-<li>If <code>false</code> is provided: do not return any images.</li>
-<li>If this parameter is omitted from the request body, or if <code>null</code> is explicitly passed, the behavior will follow the value of <code>Serving.visualize</code> in the pipeline configuration.</li>
-</ul>
-<br/>
-For example, adding the following setting to the pipeline config file:<br/>
-<pre><code>Serving:
-  visualize: False
-</code></pre>
-will disable image return by default. This behavior can be overridden by explicitly setting the <code>visualize</code> parameter in the request.<br/>
-If neither the request body nor the configuration file is set (If <code>visualize</code> is set to <code>null</code> in the request and  not defined in the configuration file), the image is returned by default.
-</td>
-<td>No</td>
-</tr>
-<tr>
 <td><code>detThreshold</code></td>
 <td><code>number</code> | <code>null</code></td>
 <td>Threshold for human detection model.</td>

docs/pipeline_usage/tutorials/cv_pipelines/human_keypoint_detection.md

@@ -646,23 +646,6 @@ for res in output:
 <td>是</td>
 </tr>
 <tr>
-<td><code>visualize</code></td>
-<td><code>boolean</code> | <code>null</code></td>
-<td>是否返回可视化结果图以及处理过程中的中间图像等。
-<ul style="margin: 0 0 0 1em; padding-left: 0em;">
-<li>传入 <code>true</code>：返回图像。</li>
-<li>传入 <code>false</code>：不返回图像。</li>
-<li>若请求体中未提供该参数或传入 <code>null</code>：遵循产线配置文件<code>Serving.visualize</code> 的设置。</li>
-</ul>
-<br/>例如，在产线配置文件中添加如下字段：<br/>
-<pre><code>Serving:
-  visualize: False
-</code></pre>
-将默认不返回图像，通过请求体中的<code>visualize</code>参数可以覆盖默认行为。如果请求体和配置文件中均未设置（或请求体传入<code>null</code>、配置文件中未设置），则默认返回图像。
-</td>
-<td>否</td>
-</tr>
-<tr>
 <td><code>detThreshold</code></td>
 <td><code>number</code> | <code>null</code></td>
 <td>人体检测模型阈值</td>

docs/pipeline_usage/tutorials/cv_pipelines/image_anomaly_detection.en.md

@@ -413,26 +413,6 @@ Below are the API references for basic service-based deployment and examples of
 <td>The URL of the image file accessible by the server or the Base64 encoded result of the image file content.</td>
 <td>Yes</td>
 </tr>
-<tr>
-<td><code>visualize</code></td>
-<td><code>boolean</code> | <code>null</code></td>
-<td>
-Whether to return the final visualization image and intermediate images during the processing.<br/>
-<ul style="margin: 0 0 0 1em; padding-left: 0em;">
-<li>If <code>true</code> is provided: return images.</li>
-<li>If <code>false</code> is provided: do not return any images.</li>
-<li>If this parameter is omitted from the request body, or if <code>null</code> is explicitly passed, the behavior will follow the value of <code>Serving.visualize</code> in the pipeline configuration.</li>
-</ul>
-<br/>
-For example, adding the following setting to the pipeline config file:<br/>
-<pre><code>Serving:
-  visualize: False
-</code></pre>
-will disable image return by default. This behavior can be overridden by explicitly setting the <code>visualize</code> parameter in the request.<br/>
-If neither the request body nor the configuration file is set (If <code>visualize</code> is set to <code>null</code> in the request and  not defined in the configuration file), the image is returned by default.
-</td>
-<td>No</td>
-</tr>
 </tbody>
 </table>
 <ul>

docs/pipeline_usage/tutorials/cv_pipelines/image_anomaly_detection.md

@@ -415,23 +415,6 @@ for res in output:
 <td>服务器可访问的图像文件的URL或图像文件内容的Base64编码结果。</td>
 <td>是</td>
 </tr>
-<tr>
-<td><code>visualize</code></td>
-<td><code>boolean</code> | <code>null</code></td>
-<td>是否返回可视化结果图以及处理过程中的中间图像等。
-<ul style="margin: 0 0 0 1em; padding-left: 0em;">
-<li>传入 <code>true</code>：返回图像。</li>
-<li>传入 <code>false</code>：不返回图像。</li>
-<li>若请求体中未提供该参数或传入 <code>null</code>：遵循产线配置文件<code>Serving.visualize</code> 的设置。</li>
-</ul>
-<br/>例如，在产线配置文件中添加如下字段：<br/>
-<pre><code>Serving:
-  visualize: False
-</code></pre>
-将默认不返回图像，通过请求体中的<code>visualize</code>参数可以覆盖默认行为。如果请求体和配置文件中均未设置（或请求体传入<code>null</code>、配置文件中未设置），则默认返回图像。
-</td>
-<td>否</td>
-</tr>
 </tbody>
 </table>
 <ul>