Add KIE_En file

ppstructure/docs/kie_en.md

@@ -0,0 +1,75 @@
+
+
+# Key Information Extraction
+
+This section will introduce a quickly use and train keynotes extraction(KIE)  using SDMGR in PaddleOCR.
+
+SDMGR is a Key Information Extraction algorithm that is classifies each detected text area into predefined categories, such as order ID, invoice number, amount etc.
+
+
+
+* [1. Quick Start](#1-----)
+* [2. Execution Training](#2-----)
+* [3. Execution Evaluation](#3-----)
+
+<a name="1-----"></a>
+## 1. Quick Start
+
+The Training and Evaluation data using wildreceipt dataset, It using as below commnad download:
+
+```
+wget https://paddleocr.bj.bcebos.com/dygraph_v2.1/kie/wildreceipt.tar && tar xf wildreceipt.tar
+```
+
+Evaluation：
+
+```
+cd PaddleOCR/
+wget https://paddleocr.bj.bcebos.com/dygraph_v2.1/kie/kie_vgg16.tar && tar xf kie_vgg16.tar
+python3.7 tools/infer_kie.py -c configs/kie/kie_unet_sdmgr.yml -o Global.checkpoints=kie_vgg16/best_accuracy  Global.infer_img=../wildreceipt/1.txt
+```
+
+The prediction result is saved as the folder`./output/sdmgr_kie/predicts_kie.txt`，the visualization result is saved as the folder`/output/sdmgr_kie/kie_results/`。
+
+Visualization Result Figures：
+
+<div align="center">
+    <img src="./imgs/0.png" width="800">
+</div>
+
+<a name="2-----"></a>
+## 2. Execution Training
+
+Building dataset link to PaddleOCR/train_data:
+
+```
+cd PaddleOCR/ && mkdir train_data && cd train_data
+ ln -s ../../wildreceipt ./
+```
+The training using configure file is configs/kie/kie_unet_sdmgr.yml，configure file default train path is `train_data/wildreceipt`， when prepare train data using as below command execute
+training:
+```
+python3.7 tools/train.py -c configs/kie/kie_unet_sdmgr.yml -o Global.save_model_dir=./output/kie/
+```
+<a name="3-----"></a>
+## 3. Execution Evaluation
+
+```
+python3.7 tools/eval.py -c configs/kie/kie_unet_sdmgr.yml -o Global.checkpoints=./output/kie/best_accuracy
+```
+
+
+**Reference Documents：**
+
+<!-- [ALGORITHM] -->
+
+```bibtex
+@misc{sun2021spatial,
+      title={Spatial Dual-Modality Graph Reasoning for Key Information Extraction},
+      author={Hongbin Sun and Zhanghui Kuang and Xiaoyu Yue and Chenhao Lin and Wayne Zhang},
+      year={2021},
+      eprint={2103.14470},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV}
+}
+```