v0.12.0-beta

Release Highlights

CV-CUDA v0.12.0 includes critical bug fixes alongside 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 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.