86 lines
3.1 KiB
Markdown
86 lines
3.1 KiB
Markdown
English | [简体中文](README_ch.md)
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- [Getting Started](#getting-started)
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- [1. Introduction](#1)
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- [2. Install](#2)
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- [2.1 Installation dependencies](#2.1)
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- [2.2 Install PaddleOCR](#2.2)
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- [3. Quick Start](#3)
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<a name="1"></a>
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## 1. Introduction
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Layout recovery means that after OCR recognition, the content is still arranged like the original document pictures, and the paragraphs are output to word document in the same order.
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Layout recovery combines [layout analysis](../layout/README.md)、[table recognition](../table/README.md) to better recover images, tables, titles, etc.
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The following figure shows the result：
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<div align="center">
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<img src="../docs/table/recovery.jpg" width = "700" />
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</div>
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<a name="2"></a>
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## 2. Install
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<a name="2.1"></a>
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### 2.1 Install dependencies
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- **(1) Install PaddlePaddle**
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```bash
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python3 -m pip install --upgrade pip
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# GPU installation
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python3 -m pip install "paddlepaddle-gpu>=2.2" -i https://mirror.baidu.com/pypi/simple
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# CPU installation
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python3 -m pip install "paddlepaddle>=2.2" -i https://mirror.baidu.com/pypi/simple
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````
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For more requirements, please refer to the instructions in [Installation Documentation](https://www.paddlepaddle.org.cn/install/quick).
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<a name="2.2"></a>
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### 2.2 Install PaddleOCR
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- **(1) Download source code**
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```bash
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[Recommended] git clone https://github.com/PaddlePaddle/PaddleOCR
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# If the pull cannot be successful due to network problems, you can also choose to use the hosting on the code cloud:
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git clone https://gitee.com/paddlepaddle/PaddleOCR
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# Note: Code cloud hosting code may not be able to synchronize the update of this github project in real time, there is a delay of 3 to 5 days, please use the recommended method first.
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````
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- **(2) Install recovery's `requirements`**
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```bash
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python3 -m pip install -r ppstructure/recovery/requirements.txt
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````
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<a name="3"></a>
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## 3. Quick Start
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```python
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cd PaddleOCR/ppstructure
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# download model
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mkdir inference && cd inference
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# Download the detection model of the ultra-lightweight English PP-OCRv3 model and unzip it
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wget https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar && tar xf ch_PP-OCRv3_det_infer.tar
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# Download the recognition model of the ultra-lightweight English PP-OCRv3 model and unzip it
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wget https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar && tar xf ch_PP-OCRv3_rec_infer.tar
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# Download the ultra-lightweight English table inch model and unzip it
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wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_structure_infer.tar && tar xf en_ppocr_mobile_v2.0_table_structure_infer.tar
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cd ..
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# run
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python3 predict_system.py --det_model_dir=inference/en_PP-OCRv3_det_infer --rec_model_dir=inference/en_PP-OCRv3_rec_infer --table_model_dir=inference/en_ppocr_mobile_v2.0_table_structure_infer --rec_char_dict_path=../ppocr/utils/en_dict.txt --table_char_dict_path=../ppocr/utils/dict/table_structure_dict.txt --output ./output/table --rec_image_shape=3,48,320 --vis_font_path=../doc/fonts/simfang.ttf --recovery=True --image_dir=./docs/table/1.png
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```
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After running, the docx of each picture will be saved in the directory specified by the output field |