Package: ppocrlabel-japan
English |简体中文PPOCRLabelv2PPOCRLabelv2 is a semi-automatic graphic annotation tool suitable for OCR field, with built-in PP-OCR model to automatically detect and re-recognize data. It is written in Python3 and PyQT5, supporting rectangular box, table, irregular text and key information annotation modes. Annotations can be directly used for the training of PP-OCR detection and recognition models.regular text annotationtable annotationirregular text annotationkey information annotationRecent Update2022.05: Add table annotations, follow2.2 Table Annotationsfor more information （bywhjdark;Evezerest)2022.02:（byPeterH0323）Add KIE Mode by using--kie, for [detection + identification + keyword extraction] labeling.Improve user experience: prompt for the number of files and labels, optimize interaction, and fix bugs such as only use CPU when inferenceNew functions: Support usingCorXto rotate box.2021.11.17:Support install and start PPOCRLabel through the whl package (byd2623587501)Dataset segmentation: Divide the annotation file into training, verification and testing parts (refer to section 3.5 below, byMrCuiHao)2021.8.11:New functions: Open the dataset folder, image rotation (Note: Please delete the label box before rotating the image) (byWei-JL)Added shortcut key description (Help-Shortcut Key), repaired the direction shortcut key movement function under batch processing (byd2623587501)2021.2.5: New batch processing and undo functions (byEvezerest):Batch processing function: Press and hold the Ctrl key to select the box, you can move, copy, and delete in batches.Undo function: In the process of drawing a four-point label box or after editing the box, press Ctrl+Z to undo the previous operation.Fix image rotation and size problems, optimize the process of editing the mark frame (byninetailskim、edencfc).2021.1.11: Optimize the labeling experience (byedencfc),Users can choose whether to pop up the label input dialog after drawing the detection box in "View - Pop-up Label Input Dialog".The recognition result scrolls synchronously when users click related detection box.Click to modify the recognition result.(If you can't change the result, please switch to the system default input method, or switch back to the original input method again)2020.12.18: Support re-recognition of a single label box (byninetailskim), perfect shortcut keys.1. Installation and Run1.1 Install PaddlePaddlepip3install--upgradepip# If you have cuda9 or cuda10 installed on your machine, please run the following command to installpython3-mpipinstallpaddlepaddle-gpu-ihttps://mirror.baidu.com/pypi/simple# If you only have cpu on your machine, please run the following command to installpython3-mpipinstallpaddlepaddle-ihttps://mirror.baidu.com/pypi/simpleFor more software version requirements, please refer to the instructions inInstallation Documentfor operation.1.2 Install and Run PPOCRLabelPPOCRLabel can be started in two ways: whl package and Python script. The whl package form is more convenient to start, and the python script to start is convenient for secondary development.WindowspipinstallPPOCRLabel# install# Select label mode and runPPOCRLabel# [Normal mode] for [detection + recognition] labelingPPOCRLabel--kieTrue# [KIE mode] for [detection + recognition + keyword extraction] labelingIf you getting this errorOSError: [WinError 126] The specified module could not be foundwhen you install shapely on windows. Please try to download Shapely whl file usinghttp://www.lfd.uci.edu/~gohlke/pythonlibs/#shapely.Reference:Solve shapely installation on windowsUbuntu Linuxpip3installPPOCRLabel
pip3installtrash-cli# Select label mode and runPPOCRLabel# [Normal mode] for [detection + recognition] labelingPPOCRLabel--kieTrue# [KIE mode] for [detection + recognition + keyword extraction] labelingMacOSpip3installPPOCRLabel
pip3installopencv-contrib-python-headless==4.2.0.32# Select label mode and runPPOCRLabel# [Normal mode] for [detection + recognition] labelingPPOCRLabel--kieTrue# [KIE mode] for [detection + recognition + keyword extraction] labeling1.2.2 Run PPOCRLabel by Python ScriptIf you modify the PPOCRLabel file (for example, specifying a new built-in model), it will be more convenient to see the results by running the Python script. If you still want to start with the whl package, you need to uninstall the whl package in the current environment and then recompile it according to the next section.cd./PPOCRLabel# Switch to the PPOCRLabel directory# Select label mode and runpythonPPOCRLabel.py# [Normal mode] for [detection + recognition] labelingpythonPPOCRLabel.py--kieTrue# [KIE mode] for [detection + recognition + keyword extraction] labeling1.2.3 Build and Install the Whl Package LocallyCompile and install a new whl package, where 0.0.0 is the version number, you can specify the new version in 'setup.py'.cd./PPOCRLabel
python3setup.pybdist_wheel
pip3installdist/PPOCRLabel-0.0.0-py2.py3-none-any.whl2. Usage2.1 StepsBuild and launch using the instructions above.Click 'Open Dir' in Menu/File to select the folder of the picture.[1]Click 'Auto recognition', use PP-OCR model to automatically annotate images which marked with 'X'[2]before the file name.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 'Q' 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.After the marking frame is drawn, the user clicks "OK", and the detection frame will be pre-assigned a "TEMPORARY" label.Click 're-Recognition', model will rewrite ALL recognition results in ALL detection box[3].Single click the result in 'recognition result' list to manually change inaccurate recognition results.Click "Check", the image status will switch to "√",then the program automatically jump to the next.Click "Delete Image", and the image will be deleted to the recycle bin.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 inLabel.txtunder the opened picture folder. Click "File"-"Export Recognition Results" in the menu bar, the recognition training data of such pictures will be saved in thecrop_imgfolder, and the recognition label will be saved inrec_gt.txt[4].2.2 Table AnnotationThe 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:Table annotation: After opening the table picture, click on theTable Recognitionbutton 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.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 onCell Re-recognition.
You can use the model to automatically recognise the text within a cell.Mark the table structure: for each cell contains the text,mark as any identifier (such as1) in Excel, to ensure that the merged cell structure is same as the original picture.Note: If there are blank cells in the table, you also need to mark them with a bounding box so that the total number of cells is the same as in the image.Adjust cell order:Click on the menuView-Show Box Numberto show the box ordinal numbers, and drag all the results under the 'Recognition Results' column on the right side of the software interface to make the box numbers are arranged from left to right, top to bottomExport JSON format annotation: close all Excel files corresponding to table images, clickFile-Export Table Labelto obtaingt.txtannotation 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".[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 nameDescriptionLabel.txtThe 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.txtThe picture status file save the image in the current folder that has been manually confirmed by the user.Cache.cachCache files to save the results of model recognition.rec_gt.txtThe 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_imgThe recognition data, generated at the same time withrec_gt.txt3. Explanation3.1 Shortcut keysShortcut keysDescriptionCtrl + Shift + RRe-recognize all the labels of the current imageWCreate a rect boxQCreate a multi-points boxXRotate the box anti-clockwiseCRotate the box clockwiseCtrl + EEdit label of the selected boxCtrl + XChange key class of the box when enable--kieCtrl + RRe-recognize the selected boxCtrl + CCopy and paste the selected boxCtrl + Left Mouse ButtonMulti select the label boxBackspaceDelete the selected boxCtrl + VCheck imageCtrl + Shift + dDelete imageDNext imageAPrevious imageCtrl++Zoom inCtrl--Zoom out↑→↓←Move selected box3.2 Built-in ModelDefault 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 toPaddleOCR Model ListCustom Model: If users want to replace the built-in model with their own inference model, they can follow theCustom Model Code Usageby modifying PPOCRLabel.py forInstantiation of PaddleOCR class:add parameterdet_model_dirinself.ocr = PaddleOCR(use_pdserving=False, use_angle_cls=True, det=True, cls=True, use_gpu=gpu, lang=lang)3.3 Export Label ResultPPOCRLabel supports three ways to export Label.txtAutomatically export: After selecting "File - Auto Export Label Mode", the program will automatically write the annotations into Label.txt every time the user confirms an image. If this option is not turned on, it will be automatically exported after detecting that the user has manually checked 5 images.The automatically export mode is turned off by defaultManual export: Click "File-Export Marking Results" to manually export the label.Close application export3.4 Dataset divisionEnter the following command in the terminal to execute the dataset division script:cd ./PPOCRLabel # Change the directory to the PPOCRLabel folder
python gen_ocr_train_val_test.py --trainValTestRatio 6:2:2 --datasetRootPath ../train_dataParameter Description:trainValTestRatiois the division ratio of the number of images in the training set, validation set, and test set, set according to your actual situation, the default is6:2:2datasetRootPathis the storage path of the complete dataset labeled by PPOCRLabel. The default path isPaddleOCR/train_data.|-train_data
  |-crop_img
    |- word_001_crop_0.png
    |- word_002_crop_0.jpg
    |- word_003_crop_0.jpg
    | ...
  | Label.txt
  | rec_gt.txt
  |- word_001.png
  |- word_002.jpg
  |- word_003.jpg
  | ...3.5 Error messageIf 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 withobjc[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==4.2.0.32If you get an error starting with **Missing string id **,you need to recompile resources:pyrcc5 -o libs/resources.py resources.qrcIf you get an errormodule 'cv2' has no attribute 'INTER_NEAREST', you need to delete all opencv related packages first, and then reinstall the 4.2.0.32  version of headless opencvpip install opencv-contrib-python-headless==4.2.0.324. Related1.Tzutalin. LabelImg. Git code (2015)