@@ -37,7 +37,7 @@ Please refer to [KIE tutorial](./kie_en.md)。PaddleOCR has modularized the code
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@@ -37,7 +37,7 @@ Please refer to [KIE tutorial](./kie_en.md)。PaddleOCR has modularized the code
### 4.1 Python Inference
### 4.1 Python Inference
-SER
-SER
First, we need to export the trained model into inference model. Take VI-LayoutXLM model trained on XFUND_zh as an example ([trained model download link](https://paddleocr.bj.bcebos.com/ppstructure/models/vi_layoutxlm/ser_vi_layoutxlm_xfund_pretrained.tar)). Use the following command to export.
First, we need to export the trained model into inference model. Take VI-LayoutXLM model trained on XFUND_zh as an example ([trained model download link](https://paddleocr.bj.bcebos.com/ppstructure/models/vi_layoutxlm/ser_vi_layoutxlm_xfund_pretrained.tar)). Use the following command to export.
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@@ -70,7 +70,7 @@ The SER visualization results are saved in the `./output` folder by default. The
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@@ -70,7 +70,7 @@ The SER visualization results are saved in the `./output` folder by default. The
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-RE
-RE
First, we need to export the trained model into inference model. Take VI-LayoutXLM model trained on XFUND_zh as an example ([trained model download link](https://paddleocr.bj.bcebos.com/ppstructure/models/vi_layoutxlm/re_vi_layoutxlm_xfund_pretrained.tar)). Use the following command to export.
First, we need to export the trained model into inference model. Take VI-LayoutXLM model trained on XFUND_zh as an example ([trained model download link](https://paddleocr.bj.bcebos.com/ppstructure/models/vi_layoutxlm/re_vi_layoutxlm_xfund_pretrained.tar)). Use the following command to export.