add PGNetA in table

doc/doc_ch/pgnet.md

@@ -27,9 +27,12 @@ PGNet算法细节详见[论文](https://www.aaai.org/AAAI21Papers/AAAI-2885.Wang
 ![](../imgs_results/e2e_res_img295_pgnet.png)
 
 ### 性能指标
-####测试集: Total Text
-####测试环境: NVIDIA Tesla V100-SXM2-16GB
-| |det_precision|det_recall|det_f_score|e2e_precision|e2e_recall|e2e_f_score|FPS|下载|
+
+测试集: Total Text
+
+测试环境: NVIDIA Tesla V100-SXM2-16GB
+
+|PGNetA|det_precision|det_recall|det_f_score|e2e_precision|e2e_recall|e2e_f_score|FPS|下载|
 | --- | --- | --- | --- | --- | --- | --- | --- | --- |
 |Paper|85.30|86.80|86.1|-|-|61.7|38.20 (size=640)|-|
 |Ours|87.03|82.48|84.69|61.71|58.43|60.03|48.73 (size=768)|[下载链接](https://paddleocr.bj.bcebos.com/dygraph_v2.0/pgnet/en_server_pgnetA.tar)|

doc/doc_en/pgnet_en.md

@@ -25,8 +25,9 @@ The results of detection and recognition are as follows:
 ![](../imgs_results/e2e_res_img295_pgnet.png)
 ### Performance
 ####Test set: Total Text
+
 ####Test environment: NVIDIA Tesla V100-SXM2-16GB
-| |det_precision|det_recall|det_f_score|e2e_precision|e2e_recall|e2e_f_score|FPS|download|
+|PGNetA|det_precision|det_recall|det_f_score|e2e_precision|e2e_recall|e2e_f_score|FPS|download|
 | --- | --- | --- | --- | --- | --- | --- | --- | --- |
 |Paper|85.30|86.80|86.1|-|-|61.7|38.20 (size=640)|-|
 |Ours|87.03|82.48|84.69|61.71|58.43|60.03|48.73 (size=768)|[download link](https://paddleocr.bj.bcebos.com/dygraph_v2.0/pgnet/en_server_pgnetA.tar)|