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LabelImg is a graphical image annotation tool.
It is written in Python and uses Qt for its graphical interface.
Annotations are saved as XML files in PASCAL VOC format, the format usedby ImageNet. Besides, it also supports YOLO format
InstallationBuild from source
Linux/Ubuntu/Mac requires at least Python2.6 and has been tested with PyQt4.8. However, Python3 or above and PyQt5 are strongly recommended.
Ubuntu Linux
Python 2 + Qt4
Python 3 + Qt5 (Recommended) Best defrag tool for mac.
macOS
Python 2 + Qt4
Python 3 + Qt5 (Recommended)
Python 3 Virtualenv (Recommended)
Virtualenv can avoid a lot of the QT / Python version issues
Note: The Last command gives you a nice .app file with a new SVG Icon in your /Applications folder. You can consider using the script: build-tools/build-for-macos.sh
Windows
Install Python,PyQt5and install lxml.
Open cmd and go to the labelImg directory
Windows + Anaconda
Download and install Anaconda (Python 3+)
Open the Anaconda Prompt and go to the labelImg directory
Get from PyPI but only python3.0 or aboveUse Docker
You can pull the image which has all of the installed and required dependencies. Watch a demo video
UsageSteps (PascalVOC)
The annotation will be saved to the folder you specify.
You can refer to the below hotkeys to speed up your workflow.
Steps (YOLO)
A txt file of YOLO format will be saved in the same folder as your image with same name. A file named 'classes.txt' is saved to that folder too. 'classes.txt' defines the list of class names that your YOLO label refers to.
Note:
Create pre-defined classes
You can edit thedata/predefined_classes.txtto load pre-defined classes
Hotkeys
Verify Image:
When pressing space, the user can flag the image as verified, a green background will appear.This is used when creating a dataset automatically, the user can then through all the pictures and flag them instead of annotate them.
Difficult:
The difficult field is set to 1 indicates that the object has been annotated as 'difficult', for example, an object which is clearly visible but difficult to recognize without substantial use of context.According to your deep neural network implementation, you can include or exclude difficult objects during training.
How to contribute
Send a pull request
License
Citation: Tzutalin. LabelImg. Git code (2015). https://github.com/tzutalin/labelImg
Related
Newer versionsOffice 2010macOSWeb
Chrome Cleanup Tool For MacCreate and print a page of identical labels
Create and print a page of the same label
Set up and print a page of the same label
For info about merging data with labels, see Create mailing labels in Word by using mail merge or Mail merge in Word for Mac.
If you want to make return address labels, see Create return address labels.
Word for the web doesn't support directly creating labels. However you can create labels from a template. For label templates, select More templates when you create a new document in Word for the web.
You can also go to templates.office.com, and search for label.
Tip: Print your labels to a sheet of paper before loading labels into the printer to make sure the text aligns with the labels.
See alsoTo create a page of different labels, see Create a sheet of nametags or address labels To create a page of labels with graphics, see Add graphics to labels Snipping Tool For MacTo print one label on a partially used sheet, see Print one label on a partially used sheet Itool For MacTo create labels with a mailing list, see Print labels for your mailing list Comments are closed.
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