Beta.5

CV-CUDA 0.7.0 introduces performance and support enhancements, along with bug fixes and new features.

Release Highlights

CV-CUDA v0.7.0 includes the following improvements:

• New Features:

  • Optimized Python bindings: near-zero overhead compared to C++ calls​

  • Added masking option to Label operator: conditional island removal

  • Added IGX Orin support (with dGPU, Ampere or Ada RTX6000)​

  • Added support of signed 32bits output datatype for Label operator​

• Removed Operator:​

  • Removed Find Contours operator for troubleshooting of major limitations

• Bug Fixes:

  • Fixed constraint on installation directory for Python tests​: tar test packages can now be used from any directory​

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.