Merge pull request #7233 from WenmuZhou/table_pr

fix table algorithm link in algorithm.md

doc/doc_ch/algorithm.md

@@ -5,7 +5,7 @@ PaddleOCR将**持续新增**支持OCR领域前沿算法与模型，已支持的
 - [文本检测算法](./algorithm_overview.md#11-%E6%96%87%E6%9C%AC%E6%A3%80%E6%B5%8B%E7%AE%97%E6%B3%95)
 - [文本识别算法](./algorithm_overview.md#12-%E6%96%87%E6%9C%AC%E8%AF%86%E5%88%AB%E7%AE%97%E6%B3%95)
 - [端到端算法](./algorithm_overview.md#2-%E6%96%87%E6%9C%AC%E8%AF%86%E5%88%AB%E7%AE%97%E6%B3%95)
-- [表格识别]](./algorithm_overview.md#3-%E8%A1%A8%E6%A0%BC%E8%AF%86%E5%88%AB%E7%AE%97%E6%B3%95)
+- [表格识别](./algorithm_overview.md#3-%E8%A1%A8%E6%A0%BC%E8%AF%86%E5%88%AB%E7%AE%97%E6%B3%95)
 
 **欢迎广大开发者合作共建，贡献更多算法，合入有奖🎁！具体可查看[社区常规赛](https://github.com/PaddlePaddle/PaddleOCR/issues/4982)。**
 

ppstructure/table/README.md

@@ -33,8 +33,8 @@ We evaluated the algorithm on the PubTabNet<sup>[1]</sup> eval dataset, and the
 |Method|Acc|[TEDS(Tree-Edit-Distance-based Similarity)](https://github.com/ibm-aur-nlp/PubTabNet/tree/master/src)|Speed|
 | --- | --- | --- | ---|
 | EDD<sup>[2]</sup> |x| 88.3 |x|
-| TableRec-RARE(ours) |73.8%| 93.32 |1550ms|
-| SLANet(ours) | 76.2%| 94.98 |766ms|
+| TableRec-RARE(ours) |73.8%| 95.3% |1550ms|
+| SLANet(ours) | 76.2%|    95.85% |766ms|
 
 The performance indicators are explained as follows:
 - Acc: The accuracy of the table structure in each image, a wrong token is considered an error.

ppstructure/table/README_ch.md

@@ -38,9 +38,9 @@
 
 |算法|Acc|[TEDS(Tree-Edit-Distance-based Similarity)](https://github.com/ibm-aur-nlp/PubTabNet/tree/master/src)|Speed|
 | --- | --- | --- | ---|
-| EDD<sup>[2]</sup> |x| 88.3 |x|
-| TableRec-RARE(ours) |73.8%| 93.32 |1550ms|
-| SLANet(ours) | 76.2%| 94.98 |766ms|
+| EDD<sup>[2]</sup> |x| 88.3% |x|
+| TableRec-RARE(ours) |73.8%| 95.3% |1550ms|
+| SLANet(ours) | 76.2%|	95.85% |766ms|
 
 性能指标解释如下：
 - Acc: 模型对每张图像里表格结构的识别准确率，错一个token就算错误。

ppstructure/table/predict_structure.py

@@ -148,7 +148,7 @@ def main(args):
                                                 bbox_list_str))
 
             if len(bbox_list) > 0 and len(bbox_list[0]) == 4:
-                img = draw_rectangle(image_file, pred_res['cell_bbox'])
+                img = draw_rectangle(image_file, bbox_list)
             else:
                 img = utility.draw_boxes(img, bbox_list)
             img_save_path = os.path.join(args.output,