text: # NV12toBGRandResize - NV12toBGRandResize
  
  ## Description
  
  This code shows two ways to convert and resize NV12 frames to BGR 3 planars frames using CUDA in batch. Way-1, Convert NV12 Input to BGR @ Input Resolution-1, then Resize to Resolution#2. Way-2, resize NV12 Input to Resolution#2 then convert it to BGR Output. NVIDIA HW Decoder, both dGPU and Tegra, normally outputs NV12 pitch format frames. For the inference using TensorRT, the input frame needs to be BGR planar format with possibly different size. So, conversion and resizing from NV12 to BGR planar is usually required for the inference following decoding. This CUDA code provides a reference implementation for conversion and resizing.
  
  ## Key Concepts
  
  Graphics Interop, Image Processing, Video Processing
  
  ## Supported SM Architectures
  
  [SM 3.5 ](https://developer.nvidia.com/cuda-gpus)  [SM 3.7 ](https://developer.nvidia.com/cuda-gpus)  [SM 5.0 ](https://developer.nvidia.com/cuda-gpus)  [SM 5.2 ](https://developer.nvidia.com/cuda-gpus)  [SM 6.0 ](https://developer.nvidia.com/cuda-gpus)  [SM 6.1 ](https://developer.nvidia.com/cuda-gpus)  [SM 7.0 ](https://developer.nvidia.com/cuda-gpus)  [SM 7.2 ](https://developer.nvidia.com/cuda-gpus)  [SM 7.5 ](https://developer.nvidia.com/cuda-gpus)  [SM 8.0 ](https://developer.nvidia.com/cuda-gpus)  [SM 8.6 ](https://developer.nvidia.com/cuda-gpus)
  
  ## Supported OSes
  
  Linux, Windows
  
  ## Supported CPU Architecture
  
  x86_64, ppc64le, aarch64
  
  ## CUDA APIs involved
  
  ### [CUDA Runtime API](http://docs.nvidia.com/cuda/cuda-runtime-api/index.html)
  cudaMemcpy2D, cudaMallocManaged
  
  ## Prerequisites
  
  Download and install the [CUDA Toolkit 11.1](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
  
  ## Build and Run
  
  ### Windows
  The Windows samples are built using the Visual Studio IDE. Solution files (.sln) are provided for each supported version of Visual Studio, using the format:
  ```
  *_vs<version>.sln - for Visual Studio <version>
  ```
  Each individual sample has its own set of solution files in its directory:
  
  To build/examine all the samples at once, the complete solution files should be used. To build/examine a single sample, the individual sample solution files should be used.
  > **Note:** Some samples require that the Microsoft DirectX SDK (June 2010 or newer) be installed and that the VC++ directory paths are properly set up (**Tools > Options...**). Check DirectX Dependencies section for details."
  
  ### Linux
  The Linux samples are built using makefiles. To use the makefiles, change the current directory to the sample directory you wish to build, and run make:
  ```
  $ cd <sample_dir>
  $ make
  ```
  The samples makefiles can take advantage of certain options:
  *  **TARGET_ARCH=<arch>** - cross-compile targeting a specific architecture. Allowed architectures are x86_64, ppc64le, aarch64.
      By default, TARGET_ARCH is set to HOST_ARCH. On a x86_64 machine, not setting TARGET_ARCH is the equivalent of setting TARGET_ARCH=x86_64.<br/>
  `$ make TARGET_ARCH=x86_64` <br/> `$ make TARGET_ARCH=ppc64le` <br/> `$ make TARGET_ARCH=aarch64` <br/>
      See [here](http://docs.nvidia.com/cuda/cuda-samples/index.html#cross-samples) for more details.
  *   **dbg=1** - build with debug symbols
      ```
      $ make dbg=1
      ```
  *   **SMS="A B ..."** - override the SM architectures for which the sample will be built, where `"A B ..."` is a space-delimited list of SM architectures. For example, to generate SASS for SM 50 and SM 60, use `SMS="50 60"`.
      ```
      $ make SMS="50 60"
      ```
  
  *  **HOST_COMPILER=<host_compiler>** - override the default g++ host compiler. See the [Linux Installation Guide](http://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#system-requirements) for a list of supported host compilers.
  ```
      $ make HOST_COMPILER=g++
  ```
  
  ## References (for more details)
  
  