LabelImg2

LabelImg2 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 used by ImageNet <http://www.image-net.org/>__.

.. image:: img/screen0.jpg :alt: labelImg2 with rotated box and extra label

Installation

Build from source

Linux/Ubuntu/Mac requires at least `Python
2.6 <https://www.python.org/getit/>`__ and has been tested with `PyQt
4.8 <https://www.riverbankcomputing.com/software/pyqt/intro>`__.


Ubuntu Linux
^^^^^^^^^^^^
Python 2 + Qt4

.. code::

    sudo apt-get install pyqt4-dev-tools
    sudo pip install lxml
    python labelImg.py
    python labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]

Python 3 + Qt5

.. code::

    sudo apt-get install pyqt5-dev-tools
    sudo pip3 install lxml
    python3 labelImg.py
    python3 labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]

Windows
^^^^^^^

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>`__.

Open cmd and go to the `labelImg <#labelimg>`__ directory

.. code::

    python labelImg.py
    python labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]
    
Windows + Anaconda
^^^^^^^

Download and install `Anaconda <https://www.anaconda.com/download/#download>`__ (Python 3+)

Open the Anaconda Prompt and go to the `labelImg <#labelimg>`__ directory

.. code::

    conda install pyqt=5
    python labelImg.py
    python labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]

Usage
-----

Steps (PascalVOC)
~~~~~

1. Build and launch using the instructions above.
2. Click 'Change default saved annotation folder' in Menu/File
3. Click 'Open Dir'
4. Click 'Create RectBox'
5. Click and release left mouse to select a region to annotate the rect
   box
6. You can use right mouse to drag the rect box to copy or move it

The annotation will be saved to the folder you specify.

You can refer to the below hotkeys to speed up your workflow.

Create pre-defined classes

You can edit the data/predefined\_classes.txt <https://github.com/chinakook/labelImg2/blob/master/data/predefined_classes.txt>__ to load pre-defined classes

Hotkeys

+------------+--------------------------------------------+
| Ctrl + u   | Load all of the images from a directory    |
+------------+--------------------------------------------+
| Ctrl + r   | Change the default annotation target dir   |
+------------+--------------------------------------------+
| Ctrl + s   | Save                                       |
+------------+--------------------------------------------+
| Ctrl + d   | Copy the current label and rect box        |
+------------+--------------------------------------------+
| Space      | Flag the current image as verified         |
+------------+--------------------------------------------+
| w          | Create a rect box                          |
+------------+--------------------------------------------+
| d          | Next image                                 |
+------------+--------------------------------------------+
| a          | Previous image                             |
+------------+--------------------------------------------+
| del        | Delete the selected rect box               |
+------------+--------------------------------------------+
| Enter      | Select a rect box                          |
+------------+--------------------------------------------+
| Ctrl++     | Zoom in                                    |
+------------+--------------------------------------------+
| Ctrl--     | Zoom out                                   |
+------------+--------------------------------------------+
| ↑→↓←       | Keyboard arrows to move selected rect box  |
+------------+--------------------------------------------+

How to contribute

Send a pull request

License

`Free software: MIT license <https://github.com/chinakook/labelImg2/blob/master/LICENSE>`_

Citation: Chinakook. LabelImg2. Git code (2018). https://github.com/chinakook/labelImg2