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labelmeWithAI
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Michael Pitidis fc8fecd81f Update usage instructions, add links 13 anni fa
icons 50bdb49d92 Add latest icons 13 anni fa
.gitignore 2dffe04535 Refactor image code to use resource files 13 anni fa
COPYING 0b472517c1 Add GPL v3 license and headers 13 anni fa
Makefile 2dffe04535 Refactor image code to use resource files 13 anni fa
README.md fc8fecd81f Update usage instructions, add links 13 anni fa
canvas.py 0b472517c1 Add GPL v3 license and headers 13 anni fa
colorDialog.py 0b472517c1 Add GPL v3 license and headers 13 anni fa
labelDialog.py 0b472517c1 Add GPL v3 license and headers 13 anni fa
labelFile.py 0b472517c1 Add GPL v3 license and headers 13 anni fa
labelme.py 0b472517c1 Add GPL v3 license and headers 13 anni fa
lib.py 0b472517c1 Add GPL v3 license and headers 13 anni fa
resources.qrc 92096a6124 Switch to PNG files 13 anni fa
shape.py 0b472517c1 Add GPL v3 license and headers 13 anni fa
test.py 572689ad15 Initial commit 13 anni fa
toolBar.py 0b472517c1 Add GPL v3 license and headers 13 anni fa
zoomWidget.py 0b472517c1 Add GPL v3 license and headers 13 anni fa

README.md

Labelme

Labelme is a graphical image annotation tool inspired by http://labelme.csail.mit.edu.

It is written in Python and uses Qt for its graphical interface.

Dependencies

Labelme requires at least Python 2.6 and has been tested with PyQt 4.8.

Usage

After cloning the code you should first run make to generate the resource file (a Python module containing all the icons).

You can then start annotating by running ./labelme.py. For usage instructions you can view the screencast tutorial from the Help menu.

At the moment annotations are saved as a JSON file. The file includes the image itself. In the feature support for XML output or possibly even SVG will be added.

TODO

  • Refactor into a Python package.
  • Add installation script.