v0.3.0-beta
CV-CUDA 0.3.0 is the next open-source release of the project.
Release Highlights
CV-CUDA 0.3.0 includes the following key features:
6 new computer vision operators
Adaptive Thresholding, Bounding Box, Bounding Box Blur, Non-Maximum Suppression, Remap, and Thresholding.
Additional compiler support for GCC 9+ (unit tests build with GCC 11+)
Compatibility with CUDA Toolkit 11.2+ (unit tests build with Toolkit 11.7+)
New sample applications
Object Detection - This pipeline is based on Peoplenet Tao model which detects Persons, Bags and Face - Supports TensorRT Inference Backend
Segmentation with NVIDIA Triton Backend - Uses VPF decoder/encoder on client side and runs segmentation pipeline on Triton server
Improved testing
Compatibility
CV-CUDA has been tested on the following compute stack
Ubuntu x86_64: 18.04, 20.04, 22.04
CUDA Toolkit: 11.7+ (11.2+ for library build and run)
GCC: 11.0+ (9.0 for library build and run)
Python: 3.7, 3.8, 3.10
Refer to documentation of the sample applications for dependencies.
Known Issues/Limitations
Open compilation issue with CUDA Toolkit 11.2 + GCC 10.3
License
CV-CUDA operates under the Apache 2.0 license.
Resources
Acknowledgements
CV-CUDA is developed jointly by NVIDIA and the ByteDance Machine Learning team.