CV-CUDA Release v0.12.0

v0.12.0-beta

Release Highlights

CV-CUDA v0.12.0 includes the following changes:

New Features​

• Increased functional test coverage of color conversions. ​
• Reintroduced from 24.07: Improved performance of color conversion operators (e.g., 2x faster RGB2YUV).

Bug Fixes

• Fixed bug in YUV(420) conversions: The CvtColor operator incorrectly computed the data location of the second chromaticity channel for conversions.​
• Fixed bug in YUV(422) conversions: The CvtColor operator incorrectly interpreted the interleaved YUV(422) data layout as a three-channel tensor.​
• Prevent CV_16F alpha addition: some color conversions in the CvtColor operator allowed for the addition of an alpha channel to the destination tensor, which is undefined for the CV_16F data type.

Compatibility and Known Limitations

For the full list, see the main README on CV-CUDA GitHub.

License

CV-CUDA is licensed under the Apache 2.0 license.

Resources

1. CV-CUDA GitHub
2. CV-CUDA Increasing Throughput and Reducing Costs for AI-Based Computer Vision with CV-CUDA
3. NVIDIA Announces Microsoft, Tencent, Baidu Adopting CV-CUDA for Computer Vision AI
4. CV-CUDA helps Tencent Cloud audio and video PaaS platform achieve full-process GPU acceleration for video enhancement AI

Acknowledgements

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