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update docs and remove old docs #13662

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150 changes: 0 additions & 150 deletions doc/doc_ch/algorithm_rec_svtrv2.md
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111 changes: 0 additions & 111 deletions doc/doc_ch/algorithm_table_slanet.md
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10 changes: 5 additions & 5 deletions docs/algorithm/table_recognition/algorithm_table_slanet.md
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Expand Up @@ -6,7 +6,7 @@ comments: true

## 1. 算法简介

PaddleOCR 算法模型挑战赛 - 赛题二：通用表格识别任务排行榜第一算法。核心思路：
该算法由来自北京交通大学机器学习与认识计算研究团队的ocr识别队研发，其在PaddleOCR算法模型挑战赛 - 赛题二：通用表格识别任务中排行榜荣获一等奖，排行榜精度相比PP-Structure表格识别模型提升0.8%，推理速度提升3倍。优化思路如下：

- 1. 改善推理过程，至EOS停止，速度提升3倍
- 2. 升级Backbone为LCNetV2（SSLD版本）
Expand All @@ -16,9 +16,9 @@ PaddleOCR 算法模型挑战赛 - 赛题二：通用表格识别任务排行榜

在PubTabNet表格识别公开数据集上，算法复现效果如下：

|模型|骨干网络|配置文件|acc|
| --- | --- | --- | --- |
|SLANet|LCNetV2|[configs/table/SLANet_lcnetv2.yml](../../configs/table/SLANet_lcnetv2.yml)|76.67%|
|模型|骨干网络|配置文件|acc|下载链接|
| --- | --- | --- | --- | --- |
|SLANet|LCNetV2|[configs/table/SLANet_lcnetv2.yml](https://github.com/PaddlePaddle/PaddleOCR/tree/main/configs/table/SLANet_lcnetv2.yml)|76.67%| [训练模型](https://paddleocr.bj.bcebos.com/openatom/ch_ppstructure_openatom_SLANetv2_train.tar) /[推理模型](https://paddleocr.bj.bcebos.com/openatom/ch_ppstructure_openatom_SLANetv2_infer.tar) |

## 2. 环境配置

Expand Down Expand Up @@ -67,7 +67,7 @@ python3 tools/export_model.py -c configs/table/SLANet_lcnetv2.yml -o Global.pret

```bash linenums="1"
cd ppstructure/
python3.7 table/predict_structure.py --table_model_dir=../inference/slanet_lcnetv2_infer/ --table_char_dict_path=../ppocr/utils/dict/table_structure_dict.txt --image_dir=docs/table/table.jpg --output=../output/table_slanet_lcnetv2 --use_gpu=False --benchmark=True --enable_mkldnn=True
python table/predict_structure.py --table_model_dir=../inference/slanet_lcnetv2_infer/ --table_char_dict_path=../ppocr/utils/dict/table_structure_dict.txt --image_dir=docs/table/table.jpg --output=../output/table_slanet_lcnetv2 --use_gpu=False --benchmark=True --enable_mkldnn=True --table_max_len=512
# 预测文件夹下所有图像时，可修改image_dir为文件夹，如 --image_dir='docs/table'。
```

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16 changes: 12 additions & 4 deletions docs/algorithm/text_recognition/algorithm_rec_svtrv2.md
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### SVTRv2算法简介

[PaddleOCR 算法模型挑战赛 - 赛题一：OCR 端到端识别任务](https://aistudio.baidu.com/competition/detail/1131/0/introduction)排行榜第一算法。主要思路：1、检测和识别模型的Backbone升级为RepSVTR；2、识别教师模型升级为SVTRv2，可识别长文本。
🔥 该算法由来自复旦大学视觉与学习实验室([FVL](https://fvl.fudan.edu.cn))的[OpenOCR](https://github.com/Topdu/OpenOCR)团队研发，其在[PaddleOCR算法模型挑战赛 - 赛题一：OCR端到端识别任务](https://aistudio.baidu.com/competition/detail/1131/0/introduction)中荣获一等奖，B榜端到端识别精度相比PP-OCRv4提升2.5%，推理速度持平。主要思路：1、检测和识别模型的Backbone升级为RepSVTR；2、识别教师模型升级为SVTRv2，可识别长文本。

|模型|配置文件|端到端|下载链接|
| --- | --- | --- | --- |
|PP-OCRv4| |A榜 62.77% <br> B榜 62.51%| [Model List](../../ppocr/model_list.md) |
|SVTRv2(Rec Sever)|[configs/rec/SVTRv2/rec_svtrv2_ch.yml](https://github.com/PaddlePaddle/PaddleOCR/tree/main/configs/rec/SVTRv2/rec_svtrv2_ch.yml)|A榜 68.81% (使用PP-OCRv4检测模型)| [训练模型](https://paddleocr.bj.bcebos.com/openatom/openatom_rec_svtrv2_ch_train.tar) / [推理模型](https://paddleocr.bj.bcebos.com/openatom/openatom_rec_svtrv2_ch_infer.tar) |
|RepSVTR(Mobile)|[识别](https://github.com/PaddlePaddle/PaddleOCR/tree/main/configs/rec/SVTRv2/rec_repsvtr_ch.yml) <br> [识别蒸馏](https://github.com/PaddlePaddle/PaddleOCR/tree/main/configs/rec/SVTRv2/rec_svtrv2_ch_distillation.yml) <br> [检测](https://github.com/PaddlePaddle/PaddleOCR/tree/main/configs/det/det_repsvtr_db.yml)|B榜 65.07%| 识别: [训练模型](https://paddleocr.bj.bcebos.com/openatom/openatom_rec_repsvtr_ch_train.tar) / [推理模型](https://paddleocr.bj.bcebos.com/openatom/openatom_rec_repsvtr_ch_infer.tar) <br> 识别蒸馏: [训练模型](https://paddleocr.bj.bcebos.com/openatom/openatom_rec_svtrv2_distill_ch_train.tar) / [推理模型](https://paddleocr.bj.bcebos.com/openatom/openatom_rec_svtrv2_distill_ch_infer.tar) <br> 检测: [训练模型](https://paddleocr.bj.bcebos.com/openatom/openatom_det_repsvtr_ch_train.tar) / [推理模型](https://paddleocr.bj.bcebos.com/openatom/openatom_det_repsvtr_ch_infer.tar) |

🚀 快速使用：参考PP-OCR推理[说明文档](https://github.com/PaddlePaddle/PaddleOCR/blob/main/doc/doc_ch/inference_ppocr.md)，将检测和识别模型替换为上表中对应的RepSVTR或SVTRv2推理模型即可使用。

## 2. 环境配置

Expand Down Expand Up @@ -79,7 +87,7 @@ python3 tools/infer/predict_rec.py --image_dir='./doc/imgs_words_en/word_10.png'
# 预测文件夹下所有图像时，可修改image_dir为文件夹，如 --image_dir='./doc/imgs_words_en/'。
```

![](../imgs_words_en/word_10.png)
![](../../ppocr/infer_deploy/images/word_10.png)

执行命令后，上面图像的预测结果（识别的文本和得分）会打印到屏幕上，示例如下：
结果如下：
Expand All @@ -96,15 +104,15 @@ Predicts of ./doc/imgs_words_en/word_10.png:('pain', 0.9999998807907104)

### 4.2 C++推理部署

由于C++预处理后处理还未支持SVTRv2
准备好推理模型后，参考[cpp infer](https://github.com/PaddlePaddle/PaddleOCR/tree/main/deploy/cpp_infer)教程进行操作即可。

### 4.3 Serving服务化部署

暂不支持

### 4.4 更多推理部署

暂不支持
- Paddle2ONNX推理：准备好推理模型后，参考[paddle2onnx](https://github.com/PaddlePaddle/PaddleOCR/tree/main/deploy/paddle2onnx)教程操作。

## 5. FAQ

Expand Down