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.. _v0.7.0-beta:

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 <https://github.com/CVCUDA/CV-CUDA>`_.

License
-------

CV-CUDA is licensed under the `Apache 2.0 <https://github.com/CVCUDA/CV-CUDA/blob/main/LICENSE.md>`_ license.

Resources
---------

1. `CV-CUDA GitHub <https://github.com/CVCUDA/CV-CUDA>`_
2. `CV-CUDA Increasing Throughput and Reducing Costs for AI-Based Computer Vision with CV-CUDA <https://developer.nvidia.com/blog/increasing-throughput-and-reducing-costs-for-computer-vision-with-cv-cuda/>`_
3. `NVIDIA Announces Microsoft, Tencent, Baidu Adopting CV-CUDA for Computer Vision AI <https://blogs.nvidia.com/blog/2023/03/21/cv-cuda-ai-computer-vision/>`_
4. `CV-CUDA helps Tencent Cloud audio and video PaaS platform achieve full-process GPU acceleration for video enhancement AI <https://developer.nvidia.com/zh-cn/blog/cv-cuda-high-performance-image-processing/>`_

Acknowledgements
----------------

CV-CUDA is developed jointly by NVIDIA and the ByteDance Machine Learning team.