75 lines
2.3 KiB
Markdown
75 lines
2.3 KiB
Markdown
# LabelImg
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LabelImg is a graphical image annotation tool. The source mainly comes from [labelme](labelme.csail.mit.edu).
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It is written in Python and uses Qt for its graphical interface.
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The annotation file will be saved as an XML file. The annotation format is PASCAL VOC format, and the format is the same as [ImageNet](http://www.image-net.org/)
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## Dependencies
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* Linux/Ubuntu/Mac
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Requires at least [Python 2.6](http://www.python.org/getit/) and has been tested with [PyQt
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4.8](http://www.riverbankcomputing.co.uk/software/pyqt/intro).
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In order to build the resource and assets, you need to install pyqt4-dev-tools:
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`$ sudo apt-get install pyqt4-dev-tools`
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`$ make all`
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`$ ./labelImg.py`
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* Windows
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Need to download and setup [Python 2.6](https://www.python.org/downloads/windows/) or later and [PyQt4](https://www.riverbankcomputing.com/software/pyqt/download). You can also try to download the whole neccessary executable files from [my drive](https://copy.com/oyYjFzJwPb4tKl93) and install them.
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Open cmd and go to $labelImg,
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`$ pyrcc4 -o resources.py resources.qrc`
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`$ python labelImg.py`
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## Usage
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After cloning the code, you should run `make all` to generate the resource file.
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You can then start annotating by running `./labelImg.py`. For usage
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instructions you can see [Here](https://youtu.be/p0nR2YsCY_U)
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At the moment annotations are saved as an XML file. The format is PASCAL VOC format, and the format is the same as [ImageNet](http://www.image-net.org/)
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You can also see [ImageNet Utils](https://github.com/tzutalin/ImageNet_Utils) to download image, create a label text for machine learning, etc
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### Create pre-defined classes
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You can edit the [data/predefined_classes.txt](https://github.com/tzutalin/labelImg/blob/master/data/predefined_classes.txt) to load pre-defined classes
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### General steps from scratch
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* Build and launch. `make all; python labelImg.py`
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* Click 'Change default saved annotation folder' in Menu/File
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* Click 'Open Dir'
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* Click 'Create RectBox'
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The annotation will be saved to the folder you specifiy
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### Hotkeys
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* Ctrl + r : Change the defult target dir which saving annotation files
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* Ctrl + n : Create a bounding box
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* Ctrl + s : Save
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* n : Next image
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* p : Previous image
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### How to contribute
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Send a pull request
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