Merge pull request #6182 from Evezerest/dygraph

Update README of PPOCRLabel 

PPOCRLabel/README.md

@@ -8,9 +8,9 @@ PPOCRLabel is a semi-automatic graphic annotation tool suitable for OCR field, w
 
 ### Recent Update
 
-- 2022.02：（by [PeterH0323](https://github.com/peterh0323) ）
+- 2022.05: Add table annotations, follow `2.2 Table Annotations` for more information （by [whjdark](https://github.com/peterh0323); [Evezerest](https://github.com/Evezerest))
+- 2022.02:（by [PeterH0323](https://github.com/peterh0323) ）
   - Add KIE Mode by using `--kie`, for [detection + identification + keyword extraction] labeling.
-- 2022.01：（by [PeterH0323](https://github.com/peterh0323) ）
   - Improve user experience: prompt for the number of files and labels, optimize interaction, and fix bugs such as only use CPU when inference
   - New functions: Support using `C` or `X` to rotate box.
 - 2021.11.17:
@@ -115,7 +115,7 @@ pip3 install dist/PPOCRLabel-1.0.2-py2.py3-none-any.whl
 
 2. Click 'Open Dir' in Menu/File to select the folder of the picture.<sup>[1]</sup>
 
-3. Click 'Auto recognition', use PPOCR model to automatically annotate images which marked with 'X' <sup>[2]</sup>before the file name.
+3. Click 'Auto recognition', use PP-OCR model to automatically annotate images which marked with 'X' <sup>[2]</sup>before the file name.
 
 4. Create Box:
 
@@ -131,11 +131,27 @@ pip3 install dist/PPOCRLabel-1.0.2-py2.py3-none-any.whl
 
 8. **Click "Check", the image status will switch to "√",then the program automatically jump to the next.**
 
-9. Click "Delete Image" and the image will be deleted to the recycle bin.
+9. Click "Delete Image", and the image will be deleted to the recycle bin.
 
 10. Labeling result: the user can export the label result manually through the menu "File - Export Label", while the program will also export automatically if "File - Auto export Label Mode" is selected. The manually checked label will be stored in *Label.txt* under the opened picture folder. Click "File"-"Export Recognition Results" in the menu bar, the recognition training data of such pictures will be saved in the *crop_img* folder, and the recognition label will be saved in *rec_gt.txt*<sup>[4]</sup>.
 
-### 2.2 Note
+### 2.2 Table Annotation
+The table annotation is aimed at extracting the structure of the table in a picture and converting it to Excel format, 
+so the annotation needs to be done simultaneously with external software to edit Excel.
+In PPOCRLabel, complete the text information labeling (text and position), complete the table structure information 
+labeling in the Excel file, the recommended steps are:
+
+1. Table annotation: After opening the table picture, click on the `Table Recognition` button in the upper right corner of PPOCRLabel, which will call the table recognition model in PP-Structure to automatically label 
+the table and pop up Excel at the same time.
+   
+2. Change the recognition result: **label each cell** (i.e. the text in a cell is marked as a box). Right click on the box and click on `Cell Re-recognition`. 
+   You can use the model to automatically recognise the text within a cell.
+   
+3. Mark the table structure: for each cell contains the text, **mark as any identifier (such as `1`) in Excel**, to ensure that the merged cell structure is same as the original picture.
+
+4. Export JSON format annotation: close all Excel files corresponding to table images, click `File`-`Export table JSON annotation` to obtain JSON annotation results.
+
+### 2.3 Note
 
 [1] PPOCRLabel uses the opened folder as the project. After opening the image folder, the picture will not be displayed in the dialog. Instead, the pictures under the folder will be directly imported into the program after clicking "Open Dir".
 
@@ -147,10 +163,10 @@ pip3 install dist/PPOCRLabel-1.0.2-py2.py3-none-any.whl
 
 |   File name   |                         Description                          |
 | :-----------: | :----------------------------------------------------------: |
-|   Label.txt   | The detection label file can be directly used for PPOCR detection model training. After the user saves 5 label results, the file will be automatically exported. It will also be written when the user closes the application or changes the file folder. |
+|   Label.txt   | The detection label file can be directly used for PP-OCR detection model training. After the user saves 5 label results, the file will be automatically exported. It will also be written when the user closes the application or changes the file folder. |
 | fileState.txt | The picture status file save the image in the current folder that has been manually confirmed by the user. |
 |  Cache.cach   |    Cache files to save the results of model recognition.     |
-|  rec_gt.txt   | The recognition label file, which can be directly used for PPOCR identification model training, is generated after the user clicks on the menu bar "File"-"Export recognition result". |
+|  rec_gt.txt   | The recognition label file, which can be directly used for PP-OCR identification model training, is generated after the user clicks on the menu bar "File"-"Export recognition result". |
 |   crop_img    | The recognition data, generated at the same time with *rec_gt.txt* |
 
 
@@ -163,7 +179,7 @@ pip3 install dist/PPOCRLabel-1.0.2-py2.py3-none-any.whl
 |--------------------------|--------------------------------------------------|
 | Ctrl + Shift + R         | Re-recognize all the labels of the current image |
 | W                        | Create a rect box                                |
-| Q                        | Create a four-points box                         |
+| Q                        | Create a multi-points box                         |
 | X                        | Rotate the box anti-clockwise                    |
 | C                        | Rotate the box clockwise                         |
 | Ctrl + E                 | Edit label of the selected box                   |

PPOCRLabel/README_ch.md

@@ -7,10 +7,9 @@ PPOCRLabel是一款适用于OCR领域的半自动化图形标注工具，内置P
 <img src="./data/gif/steps.gif" width="100%"/>
 
 #### 近期更新
-
-- 2022.02：（by [PeterH0323](https://github.com/peterh0323) ）
+- 2022.05：新增表格标注，使用方法见下方`2.2 表格标注`（by [whjdark](https://github.com/peterh0323); [Evezerest](https://github.com/Evezerest))
+- 2022.02：新增关键信息标注、优化标注体验（by [PeterH0323](https://github.com/peterh0323) ）
   - 新增：使用 `--kie` 进入 KIE 功能，用于打【检测+识别+关键字提取】的标签
-- 2022.01：（by [PeterH0323](https://github.com/peterh0323) ）
   - 提升用户体验：新增文件与标记数目提示、优化交互、修复gpu使用等问题。
   - 新增功能：使用 `C` 和 `X` 对标记框进行旋转。
 - 2021.11.17：
@@ -110,6 +109,7 @@ pip3 install dist/PPOCRLabel-1.0.2-py2.py3-none-any.whl -i https://mirror.baidu.
 ## 2. 使用
 
 ### 2.1 操作步骤
+> 如果您只需要标注文字信息和位置，推荐按照以下步骤展开：
 
 1. 安装与运行：使用上述命令安装与运行程序。
 2. 打开文件夹：在菜单栏点击 “文件” - "打开目录" 选择待标记图片的文件夹<sup>[1]</sup>.
@@ -122,9 +122,18 @@ pip3 install dist/PPOCRLabel-1.0.2-py2.py3-none-any.whl -i https://mirror.baidu.
 9. 删除：点击 “删除图像”，图片将会被删除至回收站。
 10. 导出结果：用户可以通过菜单中“文件-导出标记结果”手动导出，同时也可以点击“文件 - 自动导出标记结果”开启自动导出。手动确认过的标记将会被存放在所打开图片文件夹下的*Label.txt*中。在菜单栏点击 “文件” - "导出识别结果"后，会将此类图片的识别训练数据保存在*crop_img*文件夹下，识别标签保存在*rec_gt.txt*中<sup>[4]</sup>。
 
-### 2.2 注意
+### 2.2 表格标注
+表格标注针对表格的结构化提取，将图片中的表格转换为Excel格式，因此标注时需要配合外部软件打开Excel同时完成。
+在PPOCRLabel软件中完成表格中的文字信息标注（文字与位置）、在Excel文件中完成表格结构信息标注，推荐的步骤为：
+1. 表格识别：打开表格图片后，点击软件右上角 `表格识别` 按钮，软件调用PP-Structure中的表格识别模型，自动为表格打标签，同时弹出Excel
+2. 更改识别结果：**以表格中的单元格为单位增加标注框**（即一个单元格内的文字都标记为一个框）。标注框上鼠标右键后点击 `单元格重识别` 
+   可利用模型自动识别单元格内的文字。
+3. 标注表格结构：将表格图像中有文字的单元格，**在Excel中标记为任意标识符（如`1`）**，保证Excel中的单元格合并情况与原图相同即可。
+4. 导出JSON格式：关闭所有表格图像对应的Excel，点击 `文件`-`导出表格JSON标注` 获得JSON标注结果。
+
+### 2.3 注意
 
-[1] PPOCRLabel以文件夹为基本标记单位，打开待标记的图片文件夹后，不会在窗口栏中显示图片，而是在点击 "选择文件夹" 之后直接将文件夹下的图片导入到程序中。
+[1] PPOCRLabel以**文件夹**为基本标记单位，打开待标记的图片文件夹后，不会在窗口栏中显示图片，而是在点击 "选择文件夹" 之后直接将文件夹下的图片导入到程序中。
 
 [2] 图片状态表示本张图片用户是否手动保存过，未手动保存过即为 “X”，手动保存过为 “√”。点击 “自动标注”按钮后，PPOCRLabel不会对状态为 “√” 的图片重新标注。
 
@@ -150,13 +159,13 @@ pip3 install dist/PPOCRLabel-1.0.2-py2.py3-none-any.whl -i https://mirror.baidu.
 |------------------|---------------------------------|
 | Ctrl + shift + R | 对当前图片的所有标记重新识别                  |
 | W                | 新建矩形框                           |
-| Q                | 新建四点框                           |
+| Q                | 新建多点框                           |
 | X                | 框逆时针旋转                          |
 | C                | 框顺时针旋转                          |
 | Ctrl + E         | 编辑所选框标签                         |
 | Ctrl + X         |  `--kie` 模式下，修改 Box 的关键字种类 |
 | Ctrl + R         | 重新识别所选标记                        |
-| Ctrl + C         | 复制并粘贴选中的标记框                     |
+| Ctrl + C         | 【复制并粘贴】选中的标记框                     |
 | Ctrl + 鼠标左键    | 多选标记框                           |
 | Backspace         | 删除所选框                           |
 | Ctrl + V         | 确认本张图片标记                        |

PPOCRLabel/requirements.txt

 pyqt5
 paddleocr
+xlrd==1.2.0
\ No newline at end of file