Metadata-Version: 2.1
Name: wale-net
Version: 3.0.2
Summary: Prediction module for CommonRoad
Home-page: https://github.com/TUMFTM/Wale-Net
Author: Maximilian Geisslinger, Phillip Karle
Author-email: maximilian.geisslinger@tum.de, karle@ftm.mw.tum.de
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: torch (>=1.4.0)
Requires-Dist: scipy
Requires-Dist: progressbar2
Requires-Dist: numpy
Requires-Dist: opencv-python
Requires-Dist: tensorboard (>=2.0.0)
Requires-Dist: IPython
Requires-Dist: gitpython
Requires-Dist: matplotlib
Requires-Dist: Pillow
Requires-Dist: commonroad-io (==2023.1)
Requires-Dist: joblib
Requires-Dist: tqdm
Requires-Dist: bayesian-optimization
Requires-Dist: names
Requires-Dist: pkbar
Requires-Dist: protobuf


This package provides a Recurrent Neural Network (RNN) for vehicle trajectory prediction with uncertainties.
It builds up on the work of [Convolutional Social Pooling](https://github.com/nachiket92/conv-social-pooling).
It has been adapted to CommonRoad and extended by the ability of scene understanding and online learning.

For further information see the Readme here:
https://github.com/TUMFTM/Wale-Net
