Merge pull request #47 from rflynn/refactor-README
refactor README for simplicity and clarity
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README.md
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README.md
@ -6,38 +6,47 @@ LabelImg is a graphical image annotation tool.
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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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Annotations are saved as XML files in PASCAL VOC format, the format used by [ImageNet](http://www.image-net.org/).
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[Watch a demo video by author tzutalin](https://youtu.be/p0nR2YsCY_U)
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[](https://www.youtube.com/watch?v=p0nR2YsCY_U&feature=youtu.be)
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## Get it
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## Build source and use it
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### Download prebuilt binaries
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* Windows
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* [Download LabelImg 1.2.1 for Windows](https://raw.githubusercontent.com/tzutalin/LabelImg/gh-pages/windows/windows_v1.2.1.zip)
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* [Download LabelImg 1.2 for Windows](https://raw.githubusercontent.com/tzutalin/LabelImg/gh-pages/windows/windows_v1.2.zip)
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* Linux
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* [Download LabelImg 1.2.1 for Linux](https://raw.githubusercontent.com/tzutalin/LabelImg/gh-pages/linux/linux_v1.2.1.zip)
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* [Download LabelImg 1.2 for Linux](https://raw.githubusercontent.com/tzutalin/LabelImg/gh-pages/linux/linux_v1.2.zip)
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* OS X
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* Binaries for OS X are not yet available. Help would be appreciated. At present it must be [built from source](#os-x).
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### Build from source
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Linux/Ubuntu/Mac 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 and lxml:
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### Ubuntu
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#### Ubuntu Linux
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sudo apt-get install pyqt4-dev-tools
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sudo pip install lxml
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make all
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./labelImg.py
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### OS X
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#### OS X
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brew install qt qt4
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brew install libxml2
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make all
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./labelImg.py
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### Windows
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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). Also, you need to install lxml.
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Download and setup [Python 2.6 or later](https://www.python.org/downloads/windows/), [PyQt4](https://www.riverbankcomputing.com/software/pyqt/download) and [install lxml](http://lxml.de/installation.html).
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Open cmd and go to [labelImg]
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@ -45,31 +54,16 @@ Open cmd and go to [labelImg]
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python labelImg.py
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## Download the prebuilt binary directly
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[http://tzutalin.github.io/labelImg/](http://tzutalin.github.io/labelImg/). However, there are only prebuilt binaries for Windows and Linux because I don't have Mac OS to do that. If someone can help me to write a script to build binary for Mac OS, I will appreciate that.
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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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### Steps
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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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1. Build and launch using the instructions above.
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2. Click 'Change default saved annotation folder' in Menu/File
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3. Click 'Open Dir'
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4. Click 'Create RectBox'
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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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### 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 specify
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The annotation will be saved to the folder you specify.
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### Create pre-defined classes
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@ -77,15 +71,13 @@ You can edit the [data/predefined_classes.txt](https://github.com/tzutalin/label
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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 + s : Save
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* w : Create a bounding box
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* d : Next image
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* a : Previous image
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| | |
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|----------|------------------------------------------|
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| Ctrl + r | Change the default annotation target dir |
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| Ctrl + s | Save |
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| w | Create a bounding box |
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| d | Next image |
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| a | Previous image |
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### How to contribute
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Send a pull request
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@ -93,3 +85,6 @@ Send a pull request
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### License
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[License](LICENSE.md)
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### Related
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1. [ImageNet Utils](https://github.com/tzutalin/ImageNet_Utils) to download image, create a label text for machine learning, etc
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demo/demo3.jpg
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demo/demo3.jpg
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