..
  # SPDX-FileCopyrightText: Copyright (c) 2022-2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
  # SPDX-License-Identifier: Apache-2.0
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  # http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.

.. _v0.4.0-beta:

Beta.2
======

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 <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.