CV-CUDA Release v0.3.0

[milesp-nvidia]

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

1. CV-CUDA GitHub
2. CV-CUDA Corporate Blog Announcement
3. CV-CUDA High Performance Image Process Acceleration Library TechBlog

Acknowledgements

CV-CUDA is developed jointly by NVIDIA and the ByteDance Machine Learning team.

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This discussion was created from the release CV-CUDA Release v0.3.0.