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Readme
.. image:: https://travis-ci.com/arraiyopensource/torchgeometry.svg?branch=master :target: https://travis-ci.com/arraiyopensource/torchgeometry
.. image:: https://codecov.io/github/arraiyopensource/torchgeometry/branch/master/graph/badge.svg :target: https://codecov.io/github/arraiyopensource/torchgeometry
.. image:: https://badge.fury.io/py/torchgeometry.svg :target: https://badge.fury.io/py/torchgeometry
.. image:: https://readthedocs.org/projects/torchgeometry/badge/?version=latest :target: https://torchgeometry.readthedocs.io/en/latest/?badge=latest :alt: Documentation Status
The PyTorch Geometry package is a geometric computer vision library for PyTorch <https://pytorch.org/>
_.
It consists of a set of routines and differentiable modules to solve generic geometry computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions.
From pip:
.. code:: bash
pip install torchgeometry
From source:
.. code:: bash
python setup.py install
From source using pip:
.. code:: bash
pip install git+https://github.com/arraiyopensource/torchgeometry
.. code:: python
import torch import torchgeometry as tgm
x_rad = tgm.pi * torch.rand(1, 3, 3) x_deg = tgm.rad2deg(x_rad)
torch.allclose(x_rad, tgm.deg2rad(x_deg)) # True
Run our Jupyter notebooks examples <https://github.com/arraiyopensource/torchgeometry/tree/master/examples/>
_ to learn to use the library.
If you are using torchgeometry in your research-related documents, it is recommended that you cite the poster.
.. code:: bash
@misc{Arraiy2018, author = {E. Riba, M. Fathollahi, W. Chaney, E. Rublee and G. Bradski} title = {torchgeometry: when PyTorch meets geometry}, booktitle = {PyTorch Developer Conference}, year = {2018}, url = {https://drive.google.com/file/d/1xiao1Xj9WzjJ08YY_nYwsthE-wxfyfhG/view?usp=sharing} }
We appreciate all contributions. If you are planning to contribute back bug-fixes, please do so without any further discussion. If you plan to contribute new features, utility functions or extensions, please first open an issue and discuss the feature with us. Please, consider to read the CONTRIBUTING <https://github.com/arraiyopensource/torchgeometry/blob/master/CONTRIBUTING.rst>
_ notes.
FAQs
differential geometric computer vision for deep learning
We found that torchgeometry demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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