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CV-CUDA Release v0.5.0
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@milesp-nvidia milesp-nvidia released this 15 Dec 19:29
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v0.5.0-beta
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CV-CUDA 0.5.0 Release Notes

CV-CUDA 0.5.0 is a major release of the library providing multiple new operators, features, and fixes to multiple customer-reported issues.

Release Highlights

CV-CUDA v0.5.0 includes the following key changes:

  • New Operators:

    • FindHomography: Calculates a perspective transform from four pairs of the corresponding points
    • Label: Labels connected regions in an image using 4-way connectivity for foreground and 8-way for background pixels
    • PairwiseMatcher: Matches features computed separately (e.g. via the SIFT operator) in two images using the brute force method
    • Stack: Concatenates two input tensors into a single output tensor

  • New Features:

    • Added TensorBatch in C++ and Python, a container type that can hold a list of non-uniformly shaped tensors
    • Added Workspace in C++ and Python, an abstraction of memory and asynchronous resources for CV-CUDA operators
    • Added better color format support in nvcv_types
    • New sample application for the Label operator
    • JetPack 5.1.2 support for L4T (Jetson Orin, L4T 35.4.1, CUDA 11.4)
    • Enhanced documentation

  • Bug Fixes:

    • Resolved memory leak in NvBlurBoxes
    • Fixed segmentation fault issue in Python with certain imports
    • Corrected typestr format issue in __cuda_array_interface__
    • Addressed occasional hanging in OpBoxBlur on RGBA images

Compatibility

  • GPU Compute Capability: 7+.x
  • Ubuntu x86_64: 20.04, 22.04
  • CUDA Toolkit: 11.7+ (11.2+ for library build and run)
  • L4T: 35.4.1, JetPack 5.1.2 aarch64
  • GCC: 11.0+ (9.x and 10.x for APIs with pre-built binary)
  • Python: 3.8, 3.10

Known Issues/Limitations

  • For GCC versions lower than 11.0, C++17 support needs to be enabled when compiling CV-CUDA.

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.

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