BEAR Applications

SoftRas f644279-fosscuda-2019b-Python-3.7.4-PyTorch-1.4.0

Unsupported: Use of this version of SoftRas is not supported. More information on our Applications Support and Retention Policy.

Soft Rasterizer (SoftRas) is a truly differentiable renderer framework with a novel formulation that views rendering as a differentiable aggregating process that fuses probabilistic contributions of all mesh triangles with respect to the rendered pixels. Thanks to such "soft" formulation, our framework is able to (1) directly render colorized mesh using differentiable functions and (2) back-propagate efficient supervision signals to mesh vertices and their attributes (color, normal, etc.) from various forms of image representations, including silhouette, shading and color images.

Accessing SoftRas f644279-fosscuda-2019b-Python-3.7.4-PyTorch-1.4.0

To load the module for SoftRas f644279-fosscuda-2019b-Python-3.7.4-PyTorch-1.4.0 please use this command on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs):

module load bear-apps-unsupported/handbuilt/2019
module load SoftRas/f644279-fosscuda-2019b-Python-3.7.4-PyTorch-1.4.0

BEAR Apps Version

2019h

More Information

For more information visit the SoftRas website.

Dependencies

This version of SoftRas has a direct dependency on: fosscuda/2019b Python/3.7.4-GCCcore-8.3.0 PyTorch/1.4.0-fosscuda-2019b-Python-3.7.4 scikit-image/0.16.2-fosscuda-2019b-Python-3.7.4 SciPy-bundle/2019.10-fosscuda-2019b-Python-3.7.4 torchvision/0.5.0-fosscuda-2019b-Python-3.7.4-PyTorch-1.4.0 tqdm/4.41.1-GCCcore-8.3.0

Required By

This version of SoftRas is a direct dependent of: BEAR-Python-DataScience/2019b-fosscuda-2019b-Python-3.7.4 BEAR-Python-DataScience/2019b-fosscuda-2019b-Python-3.7.4-ppc64le

Other Versions

These versions of SoftRas are available on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs). These will be retained in accordance with our Applications Support and Retention Policy.

Last modified on 5th March 2020