imgaug 0.4.0-foss-2022a-CUDA-11.7.0This python library helps you with augmenting images for your machine learning projects. It converts a set of input images into a new, much larger set of slightly altered images.
Accessing imgaug 0.4.0-foss-2022a-CUDA-11.7.0
To load the module for imgaug 0.4.0-foss-2022a-CUDA-11.7.0 please use this command on the BEAR systems (BlueBEAR, BEAR Cloud VMs, and CaStLeS VMs):
module load bear-apps/2022a
module load imgaug/0.4.0-foss-2022a-CUDA-11.7.0
BEAR Apps Version
EL8-icelake (GPUs: NVIDIA A100, NVIDIA A30)
The listed architectures consist of two part: OS-CPU. The OS used 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.
For more information visit the imgaug website.
This version of imgaug has a direct dependency on: CUDA/11.7.0 foss/2022a imageio/2.22.2-foss-2022a matplotlib/3.5.2-foss-2022a OpenCV/4.6.0-foss-2022a-CUDA-11.7.0-contrib Pillow/9.1.1-GCCcore-11.3.0 Python/3.10.4-GCCcore-11.3.0 scikit-image/0.19.3-foss-2022a Shapely/1.8.2-foss-2022a
This version of imgaug is a direct dependent of: DeepLabCut/2.3.6-foss-2022a-CUDA-11.7.0
Last modified on 6th December 2023