This repository contains image classes to perform transformations on images with landmarks (similar to menpo but with much less dependencies). It also provides some basic Datasets for delira
This package can be installed via pip install shapedata
To load a single image with landmarks you can simply do
import shapedata
img = shapedata.SingleShapeSingleImage2D.from_files("./example_files/lenna.png")
and to view this image do
from matplotlib import pyplot as plt
img.view(view_landmarks=True)
plt.show()
To augment the image you can use img.transform()
to transform the image with the origin as transformation base or img.transform_about_centre()
to use the images's center as transformation base.
Transformations as img.translate()
, img.rotate()
, img.rescale()
or img.resize()
are also implemented and will fall back on img.transform()
or img.transform_about_centre()
To access the image itself you can do img.img
and accessing the landmarks works with img.lmk
for instances of SingleShapeSingleImage
For further usage have a look at the datasets and docstrings.
Copyright (C) 2020 by RWTH Aachen University
http://www.rwth-aachen.de
License:
This software is dual-licensed under:
• Commercial license (please contact: lfb@lfb.rwth-aachen.de)
• AGPL (GNU Affero General Public License) open source license