diff --git a/doc/doc_ch/algorithm_det_drrg.md b/doc/doc_ch/algorithm_det_drrg.md
index d89a16ae68b7024238a3982a342ef39764da9d16..8e08d01d1a7b672ae8d3dcce4b49f91f38a384bd 100644
--- a/doc/doc_ch/algorithm_det_drrg.md
+++ b/doc/doc_ch/algorithm_det_drrg.md
@@ -23,7 +23,7 @@
| 模型 |骨干网络|配置文件|precision|recall|Hmean|下载链接|
|-----| --- | --- | --- | --- | --- | --- |
-| DRRG | ResNet50_vd | [configs/det/det_r50_drrg_ctw.yml](../../configs/det/det_r50_drrg_ctw.yml)| 89.92%|80.91%|85.18%|[训练模型](https://paddleocr.bj.bcebos.com/contribution/det_r50_drrg_ctw.tar)|
+| DRRG | ResNet50_vd | [configs/det/det_r50_drrg_ctw.yml](../../configs/det/det_r50_drrg_ctw.yml)| 89.92%|80.91%|85.18%|[训练模型](https://paddleocr.bj.bcebos.com/contribution/det_r50_drrg_ctw_train.tar)|
## 2. 环境配置
diff --git a/doc/doc_ch/algorithm_overview.md b/doc/doc_ch/algorithm_overview.md
index 44c1e117ec0cdea33f3c2b74286eb58eb83e67a3..7de581c27e616ebba5a33bdad125f7ed3df9f489 100755
--- a/doc/doc_ch/algorithm_overview.md
+++ b/doc/doc_ch/algorithm_overview.md
@@ -55,7 +55,7 @@ PaddleOCR将**持续新增**支持OCR领域前沿算法与模型，**欢迎广
|模型|骨干网络|precision|recall|Hmean|下载链接|
| --- | --- | --- | --- | --- | --- |
|FCE|ResNet50_dcn|88.39%|82.18%|85.27%|[训练模型](https://paddleocr.bj.bcebos.com/contribution/det_r50_dcn_fce_ctw_v2.0_train.tar)|
-|DRRG|ResNet50_vd|89.92%|80.91%|85.18%|[训练模型](https://paddleocr.bj.bcebos.com/contribution/det_r50_drrg_ctw.tar)|
+|DRRG|ResNet50_vd|89.92%|80.91%|85.18%|[训练模型](https://paddleocr.bj.bcebos.com/contribution/det_r50_drrg_ctw_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)
diff --git a/doc/doc_ch/algorithm_rec_can.md b/doc/doc_ch/algorithm_rec_can.md
index 4f266cb33b800b446b88b507f3710d9c96db00a1..e4f4ba6f3a7e13d5d8baf1ce6b38a6f98681fb53 100644
--- a/doc/doc_ch/algorithm_rec_can.md
+++ b/doc/doc_ch/algorithm_rec_can.md
@@ -27,7 +27,7 @@
|模型 |骨干网络|配置文件|ExpRate|下载链接|
| ----- | ----- | ----- | ----- | ----- |
-|CAN|DenseNet|[rec_d28_can.yml](../../configs/rec/rec_d28_can.yml)|51.72|[训练模型](https://paddleocr.bj.bcebos.com/contribution/can_train.tar)|
+|CAN|DenseNet|[rec_d28_can.yml](../../configs/rec/rec_d28_can.yml)|51.72|[训练模型](https://paddleocr.bj.bcebos.com/contribution/rec_d28_can_train.tar)|
## 2. 环境配置
diff --git a/doc/doc_ch/algorithm_sr_telescope.md b/doc/doc_ch/algorithm_sr_telescope.md
index 9a21734b6e84c5e856940f5b2482032864d5ce27..e2351be72f2e4afa1a6c664c7dc352fce0428696 100644
--- a/doc/doc_ch/algorithm_sr_telescope.md
+++ b/doc/doc_ch/algorithm_sr_telescope.md
@@ -27,7 +27,7 @@
|模型|骨干网络|PSNR_Avg|SSIM_Avg|配置文件|下载链接|
|---|---|---|---|---|---|
-|Text Telescope|tbsrn|21.56|0.7411| [configs/sr/sr_telescope.yml](../../configs/sr/sr_telescope.yml)|[训练模型](https://paddleocr.bj.bcebos.com/contribution/Telescope_train.tar.gz)|
+|Text Telescope|tbsrn|21.56|0.7411| [configs/sr/sr_telescope.yml](../../configs/sr/sr_telescope.yml)|[训练模型](https://paddleocr.bj.bcebos.com/contribution/sr_telescope_train.tar)|
[TextZoom数据集](https://paddleocr.bj.bcebos.com/dataset/TextZoom.tar) 来自两个超分数据集RealSR和SR-RAW，两个数据集都包含LR-HR对，TextZoom有17367对训数据和4373对测试数据。
@@ -118,8 +118,8 @@ python3 tools/infer/predict_sr.py --sr_model_dir=./inference/sr_out --image_dir=
```bibtex
@INPROCEEDINGS{9578891,
author={Chen, Jingye and Li, Bin and Xue, Xiangyang},
- booktitle={2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
- title={Scene Text Telescope: Text-Focused Scene Image Super-Resolution},
+ booktitle={2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+ title={Scene Text Telescope: Text-Focused Scene Image Super-Resolution},
year={2021},
volume={},
number={},
diff --git a/doc/doc_en/algorithm_det_drrg_en.md b/doc/doc_en/algorithm_det_drrg_en.md
index 2bb7b5703dab89526345e3dcbbb55d6c90ed1c0c..8d6538a02d823d3b1382a2cbe543a9013dee974d 100644
--- a/doc/doc_en/algorithm_det_drrg_en.md
+++ b/doc/doc_en/algorithm_det_drrg_en.md
@@ -25,7 +25,7 @@ On the CTW1500 dataset, the text detection result is as follows:
|Model|Backbone|Configuration|Precision|Recall|Hmean|Download|
| --- | --- | --- | --- | --- | --- | --- |
-| DRRG | ResNet50_vd | [configs/det/det_r50_drrg_ctw.yml](../../configs/det/det_r50_drrg_ctw.yml)| 89.92%|80.91%|85.18%|[trained model](https://paddleocr.bj.bcebos.com/contribution/det_r50_drrg_ctw.tar)|
+| DRRG | ResNet50_vd | [configs/det/det_r50_drrg_ctw.yml](../../configs/det/det_r50_drrg_ctw.yml)| 89.92%|80.91%|85.18%|[trained model](https://paddleocr.bj.bcebos.com/contribution/det_r50_drrg_ctw_train.tar)|
## 2. Environment
diff --git a/doc/doc_en/algorithm_overview_en.md b/doc/doc_en/algorithm_overview_en.md
index 2614226e001b84d7316c9497de1a74bd548a64f6..09ff407916751cfa52fb72b14bacf763afbda3a7 100755
--- a/doc/doc_en/algorithm_overview_en.md
+++ b/doc/doc_en/algorithm_overview_en.md
@@ -53,7 +53,7 @@ On CTW1500 dataset, the text detection result is as follows:
|Model|Backbone|Precision|Recall|Hmean| Download link|
| --- | --- | --- | --- | --- |---|
|FCE|ResNet50_dcn|88.39%|82.18%|85.27%| [trained model](https://paddleocr.bj.bcebos.com/contribution/det_r50_dcn_fce_ctw_v2.0_train.tar) |
-|DRRG|ResNet50_vd|89.92%|80.91%|85.18%|[trained model](https://paddleocr.bj.bcebos.com/contribution/det_r50_drrg_ctw.tar)|
+|DRRG|ResNet50_vd|89.92%|80.91%|85.18%|[trained model](https://paddleocr.bj.bcebos.com/contribution/det_r50_drrg_ctw_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).
diff --git a/doc/doc_en/algorithm_rec_can_en.md b/doc/doc_en/algorithm_rec_can_en.md
index da6c9c6096fa7170b108012165b7c69862671e1a..e65bb2aa8d37b316b005c2bd9dbeffa4b7124dcf 100644
--- a/doc/doc_en/algorithm_rec_can_en.md
+++ b/doc/doc_en/algorithm_rec_can_en.md
@@ -25,7 +25,7 @@ Using CROHME handwrittem mathematical expression recognition datasets for traini
|Model|Backbone|config|exprate|Download link|
| --- | --- | --- | --- | --- |
-|CAN|DenseNet|[rec_d28_can.yml](../../configs/rec/rec_d28_can.yml)|51.72|[trained model](https://paddleocr.bj.bcebos.com/contribution/can_train.tar)|
+|CAN|DenseNet|[rec_d28_can.yml](../../configs/rec/rec_d28_can.yml)|51.72|[trained model](https://paddleocr.bj.bcebos.com/contribution/rec_d28_can_train.tar)|
## 2. Environment
diff --git a/doc/doc_en/algorithm_sr_telescope_en.md b/doc/doc_en/algorithm_sr_telescope_en.md
index 89f3b373ea041aee33841c86727913c5523bc054..9acb524312fc037bfc48b3c16e6f66024eb132b7 100644
--- a/doc/doc_en/algorithm_sr_telescope_en.md
+++ b/doc/doc_en/algorithm_sr_telescope_en.md
@@ -28,7 +28,7 @@ Referring to the [FudanOCR](https://github.com/FudanVI/FudanOCR/tree/main/scene-
|Model|Backbone|config|Acc|Download link|
|---|---|---|---|---|---|
-|Text Gestalt|tsrn|21.56|0.7411| [configs/sr/sr_telescope.yml](../../configs/sr/sr_telescope.yml)|[train model](https://paddleocr.bj.bcebos.com/contribution/Telescope_train.tar.gz)|
+|Text Gestalt|tsrn|21.56|0.7411| [configs/sr/sr_telescope.yml](../../configs/sr/sr_telescope.yml)|[train model](https://paddleocr.bj.bcebos.com/contribution/sr_telescope_train.tar)|
The [TextZoom dataset](https://paddleocr.bj.bcebos.com/dataset/TextZoom.tar) comes from two superfraction data sets, RealSR and SR-RAW, both of which contain LR-HR pairs. TextZoom has 17367 pairs of training data and 4373 pairs of test data.
@@ -127,8 +127,8 @@ Not supported
```bibtex
@INPROCEEDINGS{9578891,
author={Chen, Jingye and Li, Bin and Xue, Xiangyang},
- booktitle={2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
- title={Scene Text Telescope: Text-Focused Scene Image Super-Resolution},
+ booktitle={2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+ title={Scene Text Telescope: Text-Focused Scene Image Super-Resolution},
year={2021},
volume={},
number={},