Merge branch 'main' into docs_for_vl

Author: SWHL

docs/version3.x/algorithm/PaddleOCR-VL/PaddleOCR-VL.en.md

@@ -166,19 +166,19 @@ To improve the inference performance of PaddleOCR-VL, we introduce multi-threadi
 
 ## 6. FAQ
 
-1. How to use PaddleOCR-VL for document parsing?
+**1.How to use PaddleOCR-VL for document parsing?**
 
 Please refer to our usage documentation [PaddleOCR-VL Usage](../../pipeline_usage/PaddleOCR-VL.en.md).
 
-2. How to fine-tune the PaddleOCR-VL model?
+**2. How to fine-tune the PaddleOCR-VL model?**
 
-We recommend using the [ERNIEKit toolkit](https://github.com/PaddlePaddle/ERNIE/tree/release/v1.4) to perform Supervised Fine-Tuning (SFT) on the PaddleOCR-VL-0.9B model. For detailed steps, please refer to the [ERNIEKit documentation](https://github.com/PaddlePaddle/ERNIE/blob/release/v1.4/docs/paddleocr_vl_sft.md).
+Currently, we do not support fine-tuning of the model, but it is a high-priority feature and will be released soon. Please stay tuned.
 
-3. Why was my chart not recognized and how can I use chart recognition?
+**3. Why was my chart not recognized and how can I use chart recognition?**
 
 Because our default chart recognition function is turned off, it needs to be manually turned on. Please refer to [PaddleOCR-VL Usage](../../pipeline_usage/PaddleOCR-VL.en.md) and set the use_chart_recognition为True parameters to True turn it on.
 
-4. What are the 109 supported languages?
+**4. What are the 109 supported languages?**
 
 Chinese, English, Korea, Japanese, Thai, Greek, Tamil, Telugu
 
@@ -189,3 +189,8 @@ Latin: French, German, Afrikaans, Italian, Spanish, Bosnian, Portuguese, Czech,
 Cyrillic: Russian, Belarusian, Ukrainian, Serbian (Cyrillic), Bulgarian, Mongolian, Abkhazian, Adyghe, Kabardian, Avar, Dargin, Ingush, Chechen, Lak, Lezgin, Tabasaran, Kazakh, Kyrgyz, Tajik, Macedonian, Tatar, Chuvash, Bashkir, Malian, Moldovan, Udmurt, Komi, Ossetian, Buryat, Kalmyk, Tuvan, Sakha, Karakalpak 
 
 Devanagari: Hindi, Marathi, Nepali, Bihari, Maithili, Angika, Bhojpuri, Magahi, Santali, Newari, Konkani, Sanskrit, Haryanvi 
+
+**5. If the results of the layout check are not satisfactory, what solutions can be optimized?**
+
+Since layout detection is mainly trained for various document scenarios, if your test data is non-standard documents such as license plates, tickets images or ID Cards and you want to do OCR recognition, you can directly use the PaddleOCR-VL-0.9B model and turn off the layout detection model by setting use_layout_detection to False. If you find any layout detection errors, you can directly try the effect of using PaddleOCR-VL-0.9B alone. 
+We recommend using the [ERNIEKit toolkit](https://github.com/PaddlePaddle/ERNIE/tree/release/v1.4) to perform Supervised Fine-Tuning (SFT) on the PaddleOCR-VL-0.9B model. For detailed steps, please refer to the [ERNIEKit documentation](https://github.com/PaddlePaddle/ERNIE/blob/release/v1.4/docs/paddleocr_vl_sft.md).

docs/version3.x/algorithm/PaddleOCR-VL/PaddleOCR-VL.md

@@ -170,19 +170,19 @@ PaddleOCR-VL能够支持多种类型的文档解析，以下是一些预测案
 
 ## 六、FAQ
 
-1. 如何使用 PaddleOCR-VL 做文档解析 ？
+**1.如何使用 PaddleOCR-VL 做文档解析 ？**
 
 参考我们的使用文档 [PaddleOCR-VL使用](../../pipeline_usage/PaddleOCR-VL.md)
 
-2. 如何对 PaddleOCR-VL 模型进行微调 ？
+**2.如何对 PaddleOCR-VL 模型进行微调 ？**
 
-我们推荐使用 [ERNIEKit 套件](https://github.com/PaddlePaddle/ERNIE/tree/release/v1.4) 对 PaddleOCR-VL-0.9B 模型进行有监督微调（SFT）。具体操作步骤可参考 [ERNIEKit 官方文档](https://github.com/PaddlePaddle/ERNIE/blob/release/v1.4/docs/paddleocr_vl_sft_zh.md)。
+目前我们暂不支持模型的微调，但已经在高优的支持中，即将发布，请保持关注。
 
-3. 为什么我的图表没有识别出来，如何使用图表识别 ？
+**3.为什么我的图表没有识别出来，如何使用图表识别 ？**
 
 因为我们默认图表识别的功能是关闭的，需要手动开启，请参考 [PaddleOCR-VL使用](../../pipeline_usage/PaddleOCR-VL.md), 设置 use_chart_recognition为True 参数来开启。
 
-4. 支持的109种语言有哪些？
+**4.支持的109种语言有哪些？**
 
 中文、英语、韩语、日语、泰语、希腊语、泰米尔语、泰卢固语
 
@@ -193,3 +193,8 @@ PaddleOCR-VL能够支持多种类型的文档解析，以下是一些预测案
 西里尔文：俄语、白俄罗斯语、乌克兰语、塞尔维亚语（西里尔文）、保加利亚语、蒙古语、阿布哈兹语、阿迪杰语、卡巴尔达语、阿瓦尔语、达尔金语、印古什语、车臣语、拉克语、列兹金语、塔巴萨兰语、哈萨克语、吉尔吉斯语、塔吉克语、马其顿语、鞑靼语、楚瓦什语、巴什基尔语、马里语、摩尔多瓦语、乌德穆尔特语、科米语、奥塞梯语、布里亚特语、卡尔梅克语、图瓦语、萨哈语、卡拉卡尔帕克语
 
 天城语：印地语、马拉地语、尼泊尔语、比哈里语、迈蒂利语、安吉卡语、博杰普里语、马基语、桑塔利语、纽瓦里语、康卡尼语、梵语、哈里亚维语
+
+**5.如果版面检测的结果不理想，有什么方案可以优化？**
+
+由于版面检测主要针对各种文档场景训练，所以您的测试数据如果是非标准文档，如车牌，火车票或身份证图像想做OCR识别，那可以直接使用PaddleOCR-VL-0.9B的模型，通过设置 use_layout_detection 为 False 关闭版面检测模型。如果您发现有任何版面检测的错误，都可以直接尝试一下单独使用PaddleOCR-VL-0.9B的效果。
+我们推荐使用 [ERNIEKit 套件](https://github.com/PaddlePaddle/ERNIE/tree/release/v1.4) 对 PaddleOCR-VL-0.9B 模型进行有监督微调（SFT）。具体操作步骤可参考 [ERNIEKit 官方文档](https://github.com/PaddlePaddle/ERNIE/blob/release/v1.4/docs/paddleocr_vl_sft_zh.md)。

docs/version3.x/pipeline_usage/OCR.en.md

@@ -2620,10 +2620,10 @@ pipeline = PaddleOCR(paddlex_config="PaddleOCR.yaml")
    </tr>
   </thead>
   <tbody>
-   <tr>
-     <td><code>PP-OCRv5</code></td>
-     <td><code>ch</code>, <code>en</code>, <code>fr</code>, <code>de</code>, <code>japan</code>, <code>korean</code>, <code>chinese_cht</code>, <code>af</code>, <code>it</code>, <code>es</code>, <code>bs</code>, <code>pt</code>, <code>cs</code>, <code>cy</code>, <code>da</code>, <code>et</code>, <code>ga</code>, <code>hr</code>, <code>hu</code>, <code>rslatin</code>, <code>id</code>, <code>oc</code>, <code>is</code>, <code>lt</code>, <code>mi</code>, <code>ms</code>, <code>nl</code>, <code>no</code>, <code>pl</code>, <code>sk</code>, <code>sl</code>, <code>sq</code>, <code>sv</code>, <code>sw</code>, <code>tl</code>, <code>tr</code>, <code>uz</code>, <code>la</code>, <code>ru</code>, <code>be</code>, <code>uk</code></td>
-   </tr>
+    <tr>
+      <td><code>PP-OCRv5</code></td>
+      <td><code>ch</code>, <code>en</code>, <code>fr</code>, <code>de</code>, <code>japan</code>, <code>korean</code>, <code>chinese_cht</code>, <code>af</code>, <code>it</code>, <code>es</code>, <code>bs</code>, <code>pt</code>, <code>cs</code>, <code>cy</code>, <code>da</code>, <code>et</code>, <code>ga</code>, <code>hr</code>, <code>hu</code>, <code>rslatin</code>, <code>id</code>, <code>oc</code>, <code>is</code>, <code>lt</code>, <code>mi</code>, <code>ms</code>, <code>nl</code>, <code>no</code>, <code>pl</code>, <code>sk</code>, <code>sl</code>, <code>sq</code>, <code>sv</code>, <code>sw</code>, <code>tl</code>, <code>tr</code>, <code>uz</code>, <code>la</code>, <code>ru</code>, <code>be</code>, <code>uk</code>, <code>th</code>, <code>el</code>, <code>az</code>, <code>ku</code>, <code>lv</code>, <code>mt</code>, <code>pi</code>, <code>ro</code>, <code>vi</code>, <code>fi</code>, <code>eu</code>, <code>gl</code>, <code>lb</code>, <code>rm</code>, <code>ca</code>, <code>qu</code>, <code>te</code>, <code>sr</code>, <code>bg</code>, <code>mn</code>, <code>ab</code>, <code>ady</code>, <code>kbd</code>, <code>av</code>, <code>dar</code>, <code>inh</code>, <code>ce</code>, <code>lki</code>, <code>lez</code>, <code>tab</code>, <code>kk</code>, <code>ky</code>, <code>tg</code>, <code>mk</code>, <code>tt</code>, <code>cv</code>, <code>ba</code>, <code>mhr</code>, <code>mo</code>, <code>udm</code>, <code>kv</code>, <code>os</code>, <code>bua</code>, <code>xal</code>, <code>tyv</code>, <code>sah</code>, <code>kaa</code>, <code>ar</code>, <code>fa</code>, <code>ug</code>, <code>ur</code>, <code>ps</code>, <code>ku</code>, <code>sd</code>, <code>bal</code>, <code>hi</code>, <code>mr</code>, <code>ne</code>, <code>bh</code>, <code>mai</code>, <code>ang</code>, <code>bho</code>, <code>mah</code>, <code>sck</code>, <code>new</code>, <code>gom</code>, <code>sa</code>, <code>bgc</code>, <code>ta</code></td>
+    </tr>
    <tr>
      <td><code>PP-OCRv4</code></td>
      <td><code>ch</code>, <code>en</code></td>

docs/version3.x/pipeline_usage/OCR.md

@@ -2558,7 +2558,7 @@ pipeline = PaddleOCR(paddlex_config="PaddleOCR.yaml")
   <tbody>
     <tr>
       <td><code>PP-OCRv5</code></td>
-      <td><code>ch</code>, <code>en</code>, <code>fr</code>, <code>de</code>, <code>japan</code>, <code>korean</code>, <code>chinese_cht</code>, <code>af</code>, <code>it</code>, <code>es</code>, <code>bs</code>, <code>pt</code>, <code>cs</code>, <code>cy</code>, <code>da</code>, <code>et</code>, <code>ga</code>, <code>hr</code>, <code>hu</code>, <code>rslatin</code>, <code>id</code>, <code>oc</code>, <code>is</code>, <code>lt</code>, <code>mi</code>, <code>ms</code>, <code>nl</code>, <code>no</code>, <code>pl</code>, <code>sk</code>, <code>sl</code>, <code>sq</code>, <code>sv</code>, <code>sw</code>, <code>tl</code>, <code>tr</code>, <code>uz</code>, <code>la</code>, <code>ru</code>, <code>be</code>, <code>uk</code></td>
+      <td><code>ch</code>, <code>en</code>, <code>fr</code>, <code>de</code>, <code>japan</code>, <code>korean</code>, <code>chinese_cht</code>, <code>af</code>, <code>it</code>, <code>es</code>, <code>bs</code>, <code>pt</code>, <code>cs</code>, <code>cy</code>, <code>da</code>, <code>et</code>, <code>ga</code>, <code>hr</code>, <code>hu</code>, <code>rslatin</code>, <code>id</code>, <code>oc</code>, <code>is</code>, <code>lt</code>, <code>mi</code>, <code>ms</code>, <code>nl</code>, <code>no</code>, <code>pl</code>, <code>sk</code>, <code>sl</code>, <code>sq</code>, <code>sv</code>, <code>sw</code>, <code>tl</code>, <code>tr</code>, <code>uz</code>, <code>la</code>, <code>ru</code>, <code>be</code>, <code>uk</code>, <code>th</code>, <code>el</code>, <code>az</code>, <code>ku</code>, <code>lv</code>, <code>mt</code>, <code>pi</code>, <code>ro</code>, <code>vi</code>, <code>fi</code>, <code>eu</code>, <code>gl</code>, <code>lb</code>, <code>rm</code>, <code>ca</code>, <code>qu</code>, <code>te</code>, <code>sr</code>, <code>bg</code>, <code>mn</code>, <code>ab</code>, <code>ady</code>, <code>kbd</code>, <code>av</code>, <code>dar</code>, <code>inh</code>, <code>ce</code>, <code>lki</code>, <code>lez</code>, <code>tab</code>, <code>kk</code>, <code>ky</code>, <code>tg</code>, <code>mk</code>, <code>tt</code>, <code>cv</code>, <code>ba</code>, <code>mhr</code>, <code>mo</code>, <code>udm</code>, <code>kv</code>, <code>os</code>, <code>bua</code>, <code>xal</code>, <code>tyv</code>, <code>sah</code>, <code>kaa</code>, <code>ar</code>, <code>fa</code>, <code>ug</code>, <code>ur</code>, <code>ps</code>, <code>ku</code>, <code>sd</code>, <code>bal</code>, <code>hi</code>, <code>mr</code>, <code>ne</code>, <code>bh</code>, <code>mai</code>, <code>ang</code>, <code>bho</code>, <code>mah</code>, <code>sck</code>, <code>new</code>, <code>gom</code>, <code>sa</code>, <code>bgc</code>, <code>ta</code></td>
     </tr>
     <tr>
       <td><code>PP-OCRv4</code></td>