mirror of
https://github.com/PaddlePaddle/PaddleOCR.git
synced 2026-09-24 23:33:08 +08:00
update doc
This commit is contained in:
WenmuZhou
+15
-12
@@ -2,14 +2,15 @@ English | [简体中文](README_ch.md)
|
||||
|
||||
# Table Recognition
|
||||
|
||||
- [1. pipeline](#1-pipeline)
|
||||
- [2. Performance](#2-performance)
|
||||
- [3. Result](#3-result)
|
||||
- [4. How to use](#4-how-to-use)
|
||||
- [4.1 Quick start](#41-quick-start)
|
||||
- [4.2 Train](#42-train)
|
||||
- [4.3 Calculate TEDS](#43-calculate-teds)
|
||||
- [5. Reference](#5-reference)
|
||||
- [Table Recognition](#table-recognition)
|
||||
- [1. pipeline](#1-pipeline)
|
||||
- [2. Performance](#2-performance)
|
||||
- [3. Result](#3-result)
|
||||
- [4. How to use](#4-how-to-use)
|
||||
- [4.1 Quick start](#41-quick-start)
|
||||
- [4.2 Training, Evaluation and Inference](#42-training-evaluation-and-inference)
|
||||
- [4.3 Calculate TEDS](#43-calculate-teds)
|
||||
- [5. Reference](#5-reference)
|
||||
|
||||
|
||||
## 1. pipeline
|
||||
@@ -51,6 +52,8 @@ The performance indicators are explained as follows:
|
||||
|
||||
### 4.1 Quick start
|
||||
|
||||
PP-Structure currently provides table recognition models in both Chinese and English. For the model link, see [models_list](../docs/models_list.md). The following takes the Chinese table recognition model as an example to introduce how to recognize a table.
|
||||
|
||||
Use the following commands to quickly complete the identification of a table.
|
||||
|
||||
```python
|
||||
@@ -83,7 +86,7 @@ After the operation is completed, the excel table of each image will be saved to
|
||||
1. If you want to use the English table recognition model, you need to download the English text detection and recognition model and the English table recognition model in [models_list](../docs/models_list_en.md), and replace `table_structure_dict_ch.txt` with `table_structure_dict.txt`.
|
||||
2. To use the TableRec-RARE model, you need to replace `table_structure_dict_ch.txt` with `table_structure_dict.txt`, and add parameter `--merge_no_span_structure=False`
|
||||
|
||||
### 4.2 Train
|
||||
### 4.2 Training, Evaluation and Inference
|
||||
|
||||
The training, evaluation and inference process of the text detection model can be referred to [detection](../../doc/doc_en/detection_en.md)
|
||||
|
||||
@@ -124,11 +127,11 @@ Evaluate on the PubLatNet dataset using the English model
|
||||
cd PaddleOCR/ppstructure
|
||||
# Download the model
|
||||
mkdir inference && cd inference
|
||||
# Download the detection model of the ultra-lightweight table English OCR model and unzip it
|
||||
# Download the text detection model trained on the PubTabNet dataset and unzip it
|
||||
wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_det_infer.tar && tar xf en_ppocr_mobile_v2.0_table_det_infer.tar
|
||||
# Download the recognition model of the ultra-lightweight table English OCR model and unzip it
|
||||
# Download the text recognition model trained on the PubTabNet dataset and unzip it
|
||||
wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_rec_infer.tar && tar xf en_ppocr_mobile_v2.0_table_rec_infer.tar
|
||||
# Download the PP-Structurev2 English table recognition model and unzip it
|
||||
# Download the table recognition model trained on the PubTabNet dataset and unzip it
|
||||
wget https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/en_ppstructure_mobile_v2.0_SLANet_infer.tar && tar xf en_ppstructure_mobile_v2.0_SLANet_infer.tar
|
||||
cd ..
|
||||
|
||||
|
||||
@@ -7,7 +7,7 @@
|
||||
- [3. 效果演示](#3-效果演示)
|
||||
- [4. 使用](#4-使用)
|
||||
- [4.1 快速开始](#41-快速开始)
|
||||
- [4.2 训练](#42-训练)
|
||||
- [4.2 模型训练、评估与推理](#42-模型训练评估与推理)
|
||||
- [4.3 计算TEDS](#43-计算teds)
|
||||
- [5. Reference](#5-reference)
|
||||
|
||||
@@ -57,6 +57,8 @@
|
||||
|
||||
### 4.1 快速开始
|
||||
|
||||
PP-Structure目前提供了中英文两种语言的表格识别模型，模型链接见 [models_list](../docs/models_list.md)。下面以中文表格识别模型为例，介绍如何识别一张表格。
|
||||
|
||||
使用如下命令即可快速完成一张表格的识别。
|
||||
```python
|
||||
cd PaddleOCR/ppstructure
|
||||
@@ -83,10 +85,10 @@ python table/predict_table.py \
|
||||
运行完成后，每张图片的excel表格会保存到output字段指定的目录下，同时在该目录下回生产一个html文件，用于可视化查看单元格坐标和识别的表格。
|
||||
|
||||
**NOTE**
|
||||
1. 如果想使用英文模型，需要在[models_list](../docs/models_list.md)中下载英文文字检测识别模型和英文表格识别模型，同时替换`table_structure_dict_ch.txt`为`table_structure_dict.txt`即可。
|
||||
1. 如果想使用英文模型，需要在 [models_list](../docs/models_list.md) 中下载英文文字检测识别模型和英文表格识别模型，同时替换`table_structure_dict_ch.txt`为`table_structure_dict.txt`即可。
|
||||
2. 如需使用TableRec-RARE模型，需要替换`table_structure_dict_ch.txt`为`table_structure_dict.txt`，同时参数`--merge_no_span_structure=False`
|
||||
|
||||
### 4.2 训练
|
||||
### 4.2 模型训练、评估与推理
|
||||
|
||||
文本检测模型的训练、评估和推理流程可参考 [detection](../../doc/doc_ch/detection.md)
|
||||
|
||||
@@ -128,11 +130,11 @@ python3 table/eval_table.py \
|
||||
cd PaddleOCR/ppstructure
|
||||
# 下载模型
|
||||
mkdir inference && cd inference
|
||||
# 下载超轻量级表格英文OCR模型的检测模型并解压
|
||||
# 下载基于PubTabNet数据集训练的文本检测模型并解压
|
||||
wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_det_infer.tar && tar xf en_ppocr_mobile_v2.0_table_det_infer.tar
|
||||
# 下载超轻量级表格英文OCR模型的识别模型并解压
|
||||
# 下载基于PubTabNet数据集训练的文本识别模型并解压
|
||||
wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_rec_infer.tar && tar xf en_ppocr_mobile_v2.0_table_rec_infer.tar
|
||||
# 下载PP-Structurev2英文表格识别模型并解压
|
||||
# 下载基于PubTabNet数据集训练的表格识别模型并解压
|
||||
wget https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/en_ppstructure_mobile_v2.0_SLANet_infer.tar && tar xf en_ppstructure_mobile_v2.0_SLANet_infer.tar
|
||||
cd ..
|
||||
|
||||
|
||||
Reference in New Issue
Block a user