AugmentedAutoencoder 0c8100f-fosscuda-2019b-Python-3.7.4

Implicit 3D Orientation Learning for 6D Object Detection from RGB Images

Accessing AugmentedAutoencoder 0c8100f-fosscuda-2019b-Python-3.7.4

To load the module for AugmentedAutoencoder 0c8100f-fosscuda-2019b-Python-3.7.4 please use this command on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs):

module load AugmentedAutoencoder/0c8100f-fosscuda-2019b-Python-3.7.4

BEAR Apps Version



EL8-haswell (GPUs: NVIDIA P100)

The listed architectures consist of two part: OS-CPU.

  • BlueBEAR: The OS used on BlueBEAR is represented by EL and there are several different processor (CPU) types available on BlueBEAR. More information about the processor types on BlueBEAR is available on the BlueBEAR Job Submission page.
  • BEAR and CaStLeS Cloud VMs: These VMs can have one of two OSes. Those with access to a BEAR Cloud or CaStLeS VM should check that the listed architectures for an application include the OS of VM being used. The VMs, irrespective of OS, will use the haswell CPU type.


  • AugmentedAutoencoder 0c8100f
  • cyglfw3
  • progressbar 2.5
  • pyassimp 3.3
  • PyOpenGL-accelerate-3.1.5

More Information

For more information visit the AugmentedAutoencoder website.


This version of AugmentedAutoencoder has a direct dependency on: assimp/5.0.1-GCCcore-8.3.0 fosscuda/2019b GLFW/3.3.2-GCCcore-8.3.0 imgaug/0.4.0-fosscuda-2019b-Python-3.7.4 OpenCV/4.2.0-fosscuda-2019b-Python-3.7.4 PyOpenGL/3.1.5-GCCcore-8.3.0 Python/3.7.4-GCCcore-8.3.0 TensorFlow/1.15.0-fosscuda-2019b-Python-3.7.4

Last modified on 19th August 2020