From 605eb5d51e10eee79311697eff6918803531df67 Mon Sep 17 00:00:00 2001 From: LDOUBLEV Date: Tue, 21 Dec 2021 13:17:25 +0800 Subject: [PATCH] add kie doc --- ppstructure/README.md | 8 +++- ppstructure/README_ch.md | 8 ++++ ppstructure/docs/imgs/0.png | Bin 0 -> 211370 bytes ppstructure/docs/kie.md | 71 +++++++++++++++++++++++++++++++++ ppstructure/docs/model_list.md | 6 +++ 5 files changed, 92 insertions(+), 1 deletion(-) create mode 100644 ppstructure/docs/imgs/0.png create mode 100644 ppstructure/docs/kie.md diff --git a/ppstructure/README.md b/ppstructure/README.md index 8994cdd4..a02a53c6 100644 --- a/ppstructure/README.md +++ b/ppstructure/README.md @@ -159,7 +159,6 @@ After running, each image will have a directory with the same name under the dir **Model List** - |model name|description|config|model size|download| | --- | --- | --- | --- | --- | |en_ppocr_mobile_v2.0_table_structure|Table structure prediction for English table scenarios|[table_mv3.yml](../configs/table/table_mv3.yml)|18.6M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_structure_infer.tar) | @@ -184,4 +183,11 @@ OCR and table recognition model |en_ppocr_mobile_v2.0_table_rec|Text recognition of English table scene trained on PubLayNet dataset|6.9M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_rec_infer.tar) [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.1/table/en_ppocr_mobile_v2.0_table_rec_train.tar) | |en_ppocr_mobile_v2.0_table_structure|Table structure prediction of English table scene trained on PubLayNet dataset|18.6M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_structure_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.1/table/en_ppocr_mobile_v2.0_table_structure_train.tar) | + +KIE model + +|model name|description|model size|download| +| --- | --- | --- | --- | +|SDMGR| Key Information Extraction|-|inference model / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.1/kie/kie_vgg16.tar)| + If you need to use other models, you can download the model in [model_list](../doc/doc_en/models_list_en.md) or use your own trained model to configure it to the three fields of `det_model_dir`, `rec_model_dir`, `table_model_dir` . diff --git a/ppstructure/README_ch.md b/ppstructure/README_ch.md index 607efac1..9ce244e0 100644 --- a/ppstructure/README_ch.md +++ b/ppstructure/README_ch.md @@ -98,4 +98,12 @@ PP-Structure系列模型列表(更新中) |PP-Layout_v1.0_re_pretrained|基于LayoutXLM在xfun中文数据集上训练的RE模型|1.4G|[推理模型 coming soon]() / [训练模型](https://paddleocr.bj.bcebos.com/pplayout/PP-Layout_v1.0_re_pretrained.tar) | +* KIE模型 + +|模型名称|模型简介|模型大小|下载地址| +| --- | --- | --- | --- | +|SDMGR|关键信息提取模型|-|[推理模型 coming soon]() / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.1/kie/kie_vgg16.tar)| + + + 更多模型下载,可以参考 [模型库](./docs/model_list.md) diff --git 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00000000..67424a46 --- /dev/null +++ b/ppstructure/docs/kie.md @@ -0,0 +1,71 @@ + + +# 关键信息提取(Key Information Extraction) + +本节介绍PaddleOCR中关键信息提取SDMGR方法的快速使用和训练方法。 + +SDMGR是一个关键信息提取算法,将每个检测到的文本区域分类为预定义的类别,如订单ID、发票号码,金额等。 + + +* [1. 快速使用](#1-----) +* [2. 执行训练](#2-----) +* [3. 执行评估](#3-----) + + +## 1. 快速使用 + +训练和测试的数据采用wildreceipt数据集,通过如下指令下载数据集: + +``` +wget https://paddleocr.bj.bcebos.com/dygraph_v2.1/kie/wildreceipt.tar && tar xf wildreceipt.tar +``` + +执行预测: + +``` +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 +``` + +执行预测后的结果保存在`./output/sdmgr_kie/predicts_kie.txt`文件中,可视化结果保存在`/output/sdmgr_kie/kie_results/`目录下。 + +可视化结果如下图所示: +[img](./imgs/0.png) + + +## 2. 执行训练 + +创建数据集软链到PaddleOCR/train_data目录下: +``` +cd PaddleOCR/ && mkdir train_data && cd train_data + +ln -s ../../wildreceipt ./ +``` + +训练采用的配置文件是configs/kie/kie_unet_sdmgr.yml,配置文件中默认训练数据路径是`train_data/wildreceipt`,准备好数据后,可以通过如下指令执行训练: +``` +python3.7 tools/train.py -c configs/kie/kie_unet_sdmgr.yml -o Global.save_model_dir=./output/kie/ +``` + +## 3. 执行评估 + +``` +python3.7 tools/eval.py -c configs/kie/kie_unet_sdmgr.yml -o Global.checkpoints=./output/kie/best_accuracy +``` + + +**参考文献:** + + + +```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} +} +``` diff --git a/ppstructure/docs/model_list.md b/ppstructure/docs/model_list.md index 835d39a7..45004490 100644 --- a/ppstructure/docs/model_list.md +++ b/ppstructure/docs/model_list.md @@ -26,3 +26,9 @@ | --- | --- | --- | --- | |PP-Layout_v1.0_ser_pretrained|基于LayoutXLM在xfun中文数据集上训练的SER模型|1.4G|[推理模型 coming soon]() / [训练模型](https://paddleocr.bj.bcebos.com/pplayout/PP-Layout_v1.0_ser_pretrained.tar) | |PP-Layout_v1.0_re_pretrained|基于LayoutXLM在xfun中文数据集上训练的RE模型|1.4G|[推理模型 coming soon]() / [训练模型](https://paddleocr.bj.bcebos.com/pplayout/PP-Layout_v1.0_re_pretrained.tar) | + +## 3. KIE模型 + +|模型名称|模型简介|模型大小|下载地址| +| --- | --- | --- | --- | +|SDMGR|关键信息提取模型|-|[推理模型 coming soon]() / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.1/kie/kie_vgg16.tar)| -- GitLab