PaddleOCR/PPOCRLabel

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PPOCRLabel

PPOCRLabel is a semi-automatic graphic annotation tool suitable for OCR field. It is written in python3 and pyqt5, supporting rectangular box annotation and four-point annotation modes. Annotations can be directly used for the training of PPOCR detection and recognition models.

Recent Update

• 2020.12.18: Support re-recognition of a single label box (by ninetailskim ), perfect shortcut keys.

Installation

1. Install PaddleOCR

Refer to PaddleOCR installation document to prepare PaddleOCR

2. Install PPOCRLabel

Windows + Anaconda

Download and install Anaconda (Python 3+)

pip install pyqt5
cd ./PPOCRLabel # Change the directory to the PPOCRLabel folder
python PPOCRLabel.py

Ubuntu Linux

pip3 install pyqt5
pip3 install trash-cli
cd ./PPOCRLabel # Change the directory to the PPOCRLabel folder
python3 PPOCRLabel.py

macOS

pip3 install pyqt5
pip3 uninstall opencv-python # Uninstall opencv manually as it conflicts with pyqt
pip3 install opencv-contrib-python-headless # Install the headless version of opencv
cd ./PPOCRLabel # Change the directory to the PPOCRLabel folder
python3 PPOCRLabel.py

Usage

Steps

1. Build and launch using the instructions above.

2. Click 'Open Dir' in Menu/File to select the folder of the picture.^[1]

3. Click 'Auto recognition', use PPOCR model to automatically annotate images which marked with 'X' ^[2]before the file name.

4. Create Box:

   4.1 Click 'Create RectBox' or press 'W' in English keyboard mode to draw a new rectangle detection box. Click and release left mouse to select a region to annotate the text area.

   4.2 Press 'P' to enter four-point labeling mode which enables you to create any four-point shape by clicking four points with the left mouse button in succession and DOUBLE CLICK the left mouse as the signal of labeling completion.

5. After the marking frame is drawn, the user clicks "OK", and the detection frame will be pre-assigned a "TEMPORARY" label.

6. Click 're-Recognition', model will rewrite ALL recognition results in ALL detection box^[3].

7. Double click the result in 'recognition result' list to manually change inaccurate recognition results.

8. Click "Check", the image status will switch to "√",then the program automatically jump to the next(The results will not be written directly to the file at this time).

9. Click "Delete Image" and the image will be deleted to the recycle bin.

10. Labeling result: the user can save manually through the menu "File - Save Label", while the program will also save automatically after every 10 images confirmed by the user.the manually checked label will be stored in Label.txt under the opened picture folder. Click "PaddleOCR"-"Save 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^[4].

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".

[2] The image status indicates whether the user has saved the image manually. If it has not been saved manually it is "X", otherwise it is "√", PPOCRLabel will not relabel pictures with a status of "√".

[3] After clicking "Re-recognize", the model will overwrite ALL recognition results in the picture. Therefore, if the recognition result has been manually changed before, it may change after re-recognition.

[4] The files produced by PPOCRLabel can be found under the opened picture folder including the following, please do not manually change the contents, otherwise it will cause the program to be abnormal.

File name	Description
Label.txt	The detection label file can be directly used for PPOCR detection model training. After the user saves 10 label results, the file will be automatically saved. 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"-"Save recognition result".
crop_img	The recognition data, generated at the same time with rec_gt.txt

Explanation

Shortcut keys

Shortcut keys	Description
Ctrl + shift + A	Automatically label all unchecked images
Ctrl + shift + R	Re-recognize all the labels of the current image
W	Create a rect box
Q	Create a four-points box
Ctrl + E	Edit label of the selected box
Ctrl + R	Re-recognize the selected box
Backspace	Delete the selected box
Ctrl + V	Check image
Ctrl + Shift + d	Delete image
D	Next image
A	Previous image
Ctrl++	Zoom in
Ctrl--	Zoom out
↑→↓←	Move selected box

Built-in Model

• Default model: PPOCRLabel uses the Chinese and English ultra-lightweight OCR model in PaddleOCR by default, supports Chinese, English and number recognition, and multiple language detection.

• Model language switching: Changing the built-in model language is supportable by clicking "PaddleOCR"-"Choose OCR Model" in the menu bar. Currently supported languages​include French, German, Korean, and Japanese. For specific model download links, please refer to PaddleOCR Model List

• Custom model: The model trained by users can be replaced by modifying PPOCRLabel.py in PaddleOCR class instantiation referring Custom Model Code

Export partial recognition results

For some data that are difficult to recognize, the recognition results will not be exported by unchecking the corresponding tags in the recognition results checkbox.

Note: The status of the checkboxes in the recognition results still needs to be saved manually by clicking Save Button.

Error message

• If paddleocr is installed with whl, it has a higher priority than calling PaddleOCR class with paddleocr.py, which may cause an exception if whl package is not updated.

• For Linux users, if you get an error starting with objc[XXXXX] when opening the software, it proves that your opencv version is too high. It is recommended to install version 4.2:

  pip install opencv-python==4.2.0.32
  

• If you get an error starting with **Missing string id **,you need to recompile resources:

  pyrcc5 -o libs/resources.py resources.qrc
  

• If you get an error module 'cv2' has no attribute 'INTER_NEAREST', you need to delete all opencv related packages first, and then reinstall the headless version of opencv

  pip install opencv-contrib-python-headless
  

Related

1.Tzutalin. LabelImg. Git code (2015)