nothing important

doc/doc_ch/algorithm_overview.md

@@ -16,7 +16,7 @@ PaddleOCR开源的文本检测算法列表：
 在ICDAR2015文本检测公开数据集上，算法效果如下：
 
 |模型|骨干网络|precision|recall|Hmean|下载链接|
-|-|-|-|-|-|-|
+| --- | --- | --- | --- | --- | --- |
 |EAST|ResNet50_vd|88.76%|81.36%|84.90%|[下载链接](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_east_v2.0_train.tar)|
 |EAST|MobileNetV3|78.24%|79.15%|78.69%|[下载链接](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_east_v2.0_train.tar)|
 |DB|ResNet50_vd|86.41%|78.72%|82.38%|[下载链接](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_db_v2.0_train.tar)|
@@ -26,7 +26,7 @@ PaddleOCR开源的文本检测算法列表：
 在Total-text文本检测公开数据集上，算法效果如下：
 
 |模型|骨干网络|precision|recall|Hmean|下载链接|
-|-|-|-|-|-|-|
+| --- | --- | --- | --- | --- | --- |
 |SAST|ResNet50_vd|89.05%|76.80%|82.47%|[下载链接](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_sast_totaltext_v2.0_train.tar)|
 
 **说明：** SAST模型训练额外加入了icdar2013、icdar2017、COCO-Text、ArT等公开数据集进行调优。PaddleOCR用到的经过整理格式的英文公开数据集下载：[百度云地址](https://pan.baidu.com/s/12cPnZcVuV1zn5DOd4mqjVw) (提取码: 2bpi)

doc/doc_en/algorithm_overview_en.md

@@ -18,7 +18,7 @@ PaddleOCR open source text detection algorithms list:
 On the ICDAR2015 dataset, the text detection result is as follows:
 
 |Model|Backbone|precision|recall|Hmean|Download link|
-|-|-|-|-|-|-|
+| --- | --- | --- | --- | --- | --- |
 |EAST|ResNet50_vd|88.76%|81.36%|84.90%|[Download link](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_east_v2.0_train.tar)|
 |EAST|MobileNetV3|78.24%|79.15%|78.69%|[Download link](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_east_v2.0_train.tar)|
 |DB|ResNet50_vd|86.41%|78.72%|82.38%|[Download link](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_db_v2.0_train.tar)|
@@ -28,7 +28,7 @@ On the ICDAR2015 dataset, the text detection result is as follows:
 On Total-Text dataset, the text detection result is as follows:
 
 |Model|Backbone|precision|recall|Hmean|Download link|
-|-|-|-|-|-|-|
+| --- | --- | --- | --- | --- | --- |
 |SAST|ResNet50_vd|89.05%|76.80%|82.47%|[Download link](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_sast_totaltext_v2.0_train.tar)|
 
 **Note：** Additional data, like icdar2013, icdar2017, COCO-Text, ArT, was added to the model training of SAST. Download English public dataset in organized format used by PaddleOCR from [Baidu Drive](https://pan.baidu.com/s/12cPnZcVuV1zn5DOd4mqjVw) (download code: 2bpi).