v0.6.0-beta

CV-CUDA 0.6.0 is a comprehensive update introducing new packaging and documentation enhancements, along with bug fixes and new features.

Release Highlights

CV-CUDA v0.6.0 includes significant improvements:

  • New Operator:

    • HQResize: Advanced resize operator supporting 2D and 3D data, tensors, tensor batches, and varshape image batches (2D only). Supports nearest neighbor, linear, cubic, Gaussian and Lanczos interpolation, with optional antialiasing when down-sampling.

  • New Features:

    • Standalone Python Wheels, including tooling and documentation to generate them. Prebuilt binaries for selected configurations.

    • Homogenized package naming

    • Improved documentation of hardware/software compatibility, build and test tutorials

    • Added Python Operator benchmarking application

    • Samples updated to new codec libraries, PyNvVideoCodec and NvImageCodec

    • Support of rank 2 tensors in MedianBlur

    • Additional tests for various operators

  • Bug Fixes:

    • Fix name clashes with NVTX

    • Fix workspace memory allocation of complex filters

    • Fix memory fault in MinAreaRect

Compatibility and Known Limitations

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.