Merge branch 'release/2.2' of https://github.com/PaddlePaddle/PaddleOCR into fix_cpp_22
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@ -101,11 +101,13 @@ For a new language request, please refer to [Guideline for new language_requests
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- [Installation](./doc/doc_en/installation_en.md)
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- [Quick Start(Chinese)](./doc/doc_en/quickstart_en.md)
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- [Quick Start(English&Multi-languages)](./doc/doc_en/multi_languages_en.md)
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- [Quick Start(PP-Structure)](./ppstructure/README.md)
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- [Code Structure](./doc/doc_en/tree_en.md)
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- Algorithm Introduction
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- [Text Detection Algorithm](./doc/doc_en/algorithm_overview_en.md)
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- [Text Recognition Algorithm](./doc/doc_en/algorithm_overview_en.md)
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- [PP-OCR Pipeline](#PP-OCR-Pipeline)
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- [PP-Structure Pipeline](./ppstructure/README.md)
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- Model Training/Evaluation
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- [Text Detection](./doc/doc_en/detection_en.md)
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- [Text Recognition](./doc/doc_en/recognition_en.md)
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@ -91,11 +91,13 @@ PaddleOCR同时支持动态图与静态图两种编程范式
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- [快速安装](./doc/doc_ch/installation.md)
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- [中文OCR模型快速使用](./doc/doc_ch/quickstart.md)
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- [多语言OCR模型快速使用](./doc/doc_ch/multi_languages.md)
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- [版面分析与表格识别快速使用](./ppstructure/README_ch.md)
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- [代码组织结构](./doc/doc_ch/tree.md)
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- 算法介绍
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- [文本检测](./doc/doc_ch/algorithm_overview.md)
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- [文本识别](./doc/doc_ch/algorithm_overview.md)
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- [PP-OCR Pipeline](#PP-OCR)
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- [PP-Structure Pipeline](./ppstructure/README_ch.md)
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- [端到端PGNet算法](./doc/doc_ch/pgnet.md)
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- 模型训练/评估
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- [文本检测](./doc/doc_ch/detection.md)
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@ -106,7 +108,7 @@ PaddleOCR同时支持动态图与静态图两种编程范式
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- [基于pip安装whl包快速推理](./doc/doc_ch/whl.md)
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- [基于Python脚本预测引擎推理](./doc/doc_ch/inference.md)
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- [基于C++预测引擎推理](./deploy/cpp_infer/readme.md)
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- [服务化部署](./deploy/hubserving/readme.md)
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- [服务化部署](./deploy/pdserving/README_CN.md)
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- [端侧部署](./deploy/lite/readme.md)
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- [Benchmark](./doc/doc_ch/benchmark.md)
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- 数据集
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@ -127,7 +127,7 @@ dict 里各个字段说明如下
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大部分参数和paddleocr whl包保持一致,见 [whl包文档](../doc/doc_ch/whl.md)
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运行完成后,每张图片会在`output`字段指定的目录下有一个同名目录,图片里的每个表格会存储为一个excel,图片区域会被裁剪之后保存下来,excel文件和图片名名为表格在图片里的坐标。
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运行完成后,每张图片会在`output`字段指定的目录下有一个同名目录,图片里的每个表格会存储为一个excel,图片区域会被裁剪之后保存下来,excel文件和图片名为表格在图片里的坐标。
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## 4. PP-Structure Pipeline介绍
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@ -74,7 +74,7 @@ class TextE2E(object):
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self.preprocess_op = create_operators(pre_process_list)
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self.postprocess_op = build_post_process(postprocess_params)
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self.predictor, self.input_tensor, self.output_tensors = utility.create_predictor(
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self.predictor, self.input_tensor, self.output_tensors, _ = utility.create_predictor(
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args, 'e2e', logger) # paddle.jit.load(args.det_model_dir)
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# self.predictor.eval()
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