CV-CUDA Release v0.4.0

CV-CUDA 0.4.0 is a major release of the library providing multiple new operators, Jetson Orin support, and updated API documentation.

Release Highlights

CV-CUDA v0.4.0 includes the following key features:

• 14 new image processing and computer vision operators
  • Advanced Color Format Conversion
  • Brightness_Contrast
  • Color_Twist
  • FindContours
  • GaussianNoise
  • Histogram
  • Histogram Equalizer
  • Inpainting
  • MinAreaRect
  • MinMaxLoc
  • Morphology (Open, Close)
  • On-screen display (Polyline, Point, Line, Text, Rotated Rectangle, Segmented Mask)
  • RandomResizedCrop
  • SIFT
• Updated sample application
  • Streamed Triton-based Video Segmentation Sample using CV-CUDA and VPF (Video Processing Framework) optimized for performance with video decode/encode on server-side
• Added Jetson Orin support for core library
• Updated API documentation

Compatibility

CV-CUDA has been tested on the following compute stack:

• GPU Compute Capability: 7+.x
• Ubuntu x86_64: 20.04, 22.04
• CUDA Toolkit: 11.7+ (11.2+ for library build and run)
• GCC: 11.0+ (9.0 and 10.0 for APIs, with pre-built binary and run)
• Python: 3.7, 3.8, 3.10

Refer to documentation of the sample applications for dependencies.

Known Issues/Limitations

• Samples fails for encoding surfaces on T4 with CUDA 11.8 and display driver 520. Suggested workaround is to upgrade to a newer driver 525+.
• For GCC versions lower than 11.0, C++17 support needs to be enabled when compiling CV-CUDA.

License

CV-CUDA operates 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.