diff --git a/ppstructure/docs/models_list.md b/ppstructure/docs/models_list.md
index 71d0566bb0e70dc907416cf426ce88acac538e79..dabce3a5149a88833d38a4395e31ac1f82306c4f 100644
--- a/ppstructure/docs/models_list.md
+++ b/ppstructure/docs/models_list.md
@@ -1,12 +1,11 @@
# PP-Structure 系列模型列表
-- [PP-Structure 系列模型列表](#pp-structure-系列模型列表)
- - [1. 版面分析模型](#1-版面分析模型)
- - [2. OCR和表格识别模型](#2-ocr和表格识别模型)
- - [2.1 OCR](#21-ocr)
- - [2.2 表格识别模型](#22-表格识别模型)
- - [3. VQA模型](#3-vqa模型)
- - [4. KIE模型](#4-kie模型)
+- [1. 版面分析模型](#1-版面分析模型)
+- [2. OCR和表格识别模型](#2-ocr和表格识别模型)
+ - [2.1 OCR](#21-ocr)
+ - [2.2 表格识别模型](#22-表格识别模型)
+- [3. VQA模型](#3-vqa模型)
+- [4. KIE模型](#4-kie模型)
diff --git a/ppstructure/docs/models_list_en.md b/ppstructure/docs/models_list_en.md
index b3a07555051ef08495019ef3c40d2ca4bfbad03c..e133a0bb2a9b017207b5e92ea444aba4633a7457 100644
--- a/ppstructure/docs/models_list_en.md
+++ b/ppstructure/docs/models_list_en.md
@@ -1,12 +1,11 @@
# PP-Structure Model list
-- [PP-Structure Model list](#pp-structure-model-list)
- - [1. Layout Analysis](#1-layout-analysis)
- - [2. OCR and Table Recognition](#2-ocr-and-table-recognition)
- - [2.1 OCR](#21-ocr)
- - [2.2 Table Recognition](#22-table-recognition)
- - [3. VQA](#3-vqa)
- - [4. KIE](#4-kie)
+- [1. Layout Analysis](#1-layout-analysis)
+- [2. OCR and Table Recognition](#2-ocr-and-table-recognition)
+ - [2.1 OCR](#21-ocr)
+ - [2.2 Table Recognition](#22-table-recognition)
+- [3. VQA](#3-vqa)
+- [4. KIE](#4-kie)
diff --git a/ppstructure/infer.sh b/ppstructure/infer.sh
new file mode 100644
index 0000000000000000000000000000000000000000..a08cbadf09d5f813308125ba52897a9379e7915d
--- /dev/null
+++ b/ppstructure/infer.sh
@@ -0,0 +1,4 @@
+python3.7 vqa/predict_vqa_token_ser.py --vqa_algorithm=LayoutXLM --ser_model_dir=../models/ser_LayoutXLM_xfun_zh/infer --ser_dict_path=../train_data/XFUND/class_list_xfun.txt --image_dir=docs/vqa/input/zh_val_42.jpg
+
+
+python3.7 tools/infer_vqa_token_ser_re.py -c configs/vqa/re/layoutxlm.yml -o Architecture.Backbone.checkpoints=models/re_LayoutXLM_xfun_zh/ Global.infer_img=ppstructure/docs/vqa/input/zh_val_21.jpg -c_ser configs/vqa/ser/layoutxlm.yml -o_ser Architecture.Backbone.checkpoints=models/ser_LayoutXLM_xfun_zh/
\ No newline at end of file
diff --git a/ppstructure/vqa/README.md b/ppstructure/vqa/README.md
index cfb421005062de46a6d4ff4a093c657017847d46..05635265b5e5eff18429e2d595fc4195381299f5 100644
--- a/ppstructure/vqa/README.md
+++ b/ppstructure/vqa/README.md
@@ -1,16 +1,15 @@
English | [简体中文](README_ch.md)
-- [Document Visual Question Answering](#document-visual-question-answering)
- - [1 Introduction](#1-introduction)
- - [2. Performance](#2-performance)
- - [3. Effect demo](#3-effect-demo)
- - [3.1 SER](#31-ser)
- - [3.2 RE](#32-re)
- - [4. Install](#4-install)
- - [4.1 Install dependencies](#41-install-dependencies)
- - [5.3 RE](#53-re)
- - [6. Reference Links](#6-reference-links)
- - [License](#license)
+- [1 Introduction](#1-introduction)
+- [2. Performance](#2-performance)
+- [3. Effect demo](#3-effect-demo)
+ - [3.1 SER](#31-ser)
+ - [3.2 RE](#32-re)
+- [4. Install](#4-install)
+ - [4.1 Install dependencies](#41-install-dependencies)
+ - [5.3 RE](#53-re)
+- [6. Reference Links](#6-reference-links)
+- [License](#license)
# Document Visual Question Answering
@@ -212,7 +211,7 @@ python3.7 tools/export_model.py -c configs/vqa/ser/layoutxlm.yml -o Architecture
The converted model will be stored in the directory specified by the `Global.save_inference_dir` field.
* `OCR + SER` tandem prediction based on prediction engine
-
+
Use the following command to complete the tandem prediction of `OCR + SER` based on the prediction engine, taking the SER model based on LayoutXLM as an example:
```shell
@@ -268,7 +267,7 @@ python3 tools/infer_vqa_token_ser_re.py -c configs/vqa/re/layoutxlm.yml -o Archi
Finally, the prediction result visualization image and the prediction result text file will be saved in the directory configured by the `config.Global.save_res_path` field. The prediction result text file is named `infer_results.txt`.
* export model
-
+
cooming soon
* `OCR + SER + RE` tandem prediction based on prediction engine
diff --git a/ppstructure/vqa/README_ch.md b/ppstructure/vqa/README_ch.md
index 52113b80b52b216dad4d7654863944b639eacbfc..b421a82d3a1cbe39f5c740bea486ec26593ab20f 100644
--- a/ppstructure/vqa/README_ch.md
+++ b/ppstructure/vqa/README_ch.md
@@ -1,20 +1,19 @@
[English](README.md) | 简体中文
-- [文档视觉问答（DOC-VQA）](#文档视觉问答doc-vqa)
- - [1. 简介](#1-简介)
- - [2. 性能](#2-性能)
- - [3. 效果演示](#3-效果演示)
- - [3.1 SER](#31-ser)
- - [3.2 RE](#32-re)
- - [4. 安装](#4-安装)
- - [4.1 安装依赖](#41-安装依赖)
- - [4.2 安装PaddleOCR（包含 PP-OCR 和 VQA）](#42-安装paddleocr包含-pp-ocr-和-vqa)
- - [5. 使用](#5-使用)
- - [5.1 数据和预训练模型准备](#51-数据和预训练模型准备)
- - [5.2 SER](#52-ser)
- - [5.3 RE](#53-re)
- - [6. 参考链接](#6-参考链接)
- - [License](#license)
+- [1. 简介](#1-简介)
+- [2. 性能](#2-性能)
+- [3. 效果演示](#3-效果演示)
+ - [3.1 SER](#31-ser)
+ - [3.2 RE](#32-re)
+- [4. 安装](#4-安装)
+ - [4.1 安装依赖](#41-安装依赖)
+ - [4.2 安装PaddleOCR（包含 PP-OCR 和 VQA）](#42-安装paddleocr包含-pp-ocr-和-vqa)
+- [5. 使用](#5-使用)
+ - [5.1 数据和预训练模型准备](#51-数据和预训练模型准备)
+ - [5.2 SER](#52-ser)
+ - [5.3 RE](#53-re)
+- [6. 参考链接](#6-参考链接)
+- [License](#license)
# 文档视觉问答（DOC-VQA）
@@ -211,7 +210,7 @@ python3.7 tools/export_model.py -c configs/vqa/ser/layoutxlm.yml -o Architecture
转换后的模型会存放在`Global.save_inference_dir`字段指定的目录下。
* 基于预测引擎的`OCR + SER`串联预测
-
+
使用如下命令即可完成基于预测引擎的`OCR + SER`的串联预测, 以基于LayoutXLM的SER模型为例:
```shell
@@ -266,7 +265,7 @@ python3 tools/infer_vqa_token_ser_re.py -c configs/vqa/re/layoutxlm.yml -o Archi
最终会在`config.Global.save_res_path`字段所配置的目录下保存预测结果可视化图像以及预测结果文本文件，预测结果文本文件名为`infer_results.txt`。
* 模型导出
-
+
cooming soon
* 基于预测引擎的`OCR + SER + RE`串联预测