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OpenCV 4.5 simple optical flow GPU tutorial cuda::FarnebackOpticalFlow

This OpenCV tutorial is a very simple code example of GPU Cuda optical flow in OpenCV written in c++. The configuration of the project, code, and explanation are included for farneback Optical Flow method. Farneback algorithm is a dense method that is used to process all the pixels in the given image. The dense methods are slower but more accurate as all the pixels of the image are processed. In the following example, I am displaying just a few pixes based on a grid. I am not displaying all the pixes. In the opposite to dense method the sparse method like Lucas Kanade using just a selected subset of pixels. They are faster. Both methods have specific applications. Lucas-Kanade is widely used in tracking. The farneback can be used for the analysis of more complex movement in image scene and furder segmentation based on these changes. As dense methods are slightly slower, the GPU and Cuda implementation can lead to great performance improvements to calculate optical flow for all pixels o

Compile opencv 4 with Cuda and GStreamer on windows

Compile OpenCV with Cuda is an easy task. All you need is the right HW from NVIDIA, drivers, and software. Additionally, the processed output video should be stream out from the OpenCV using the GStreamer. I am putting the GStreamer now as the standard option of my installation of OpenCV on the Windows machine.  Let's go through step by step compilation of OpenCV from source, including Cuda, Gstreamer, and contribution modules. It is just a small increment to my previous tutorial that focuses just on the GStreamer setting in the Windows CMAKE project.  This is a simplified version, verified on a different machine than the previous tutorials.  You can found some details in this tutorial Install Opencv Gstreamer on windows step by step

Software prerequisites

  • Install cuda, This is my version of network installer cuda_11.0.2_win10_network 
  • Visual Studio 2019 community 
  • Cmake 3.17.4 
  • Opencv 4.4
  • Opencv_contrib

Opencv Compilation in windows steps by step with GStreamer

Extract or get through git opencv-4.4
Extract or get through git opencv_contrib-master
Create empty folder build_cuda
Opencv

Get and install GStreamer (optional step)

Download both 1.16.2 runtime and development installer
Gstreamer installer opencv
Install both into the same directory
GStreamer windows opencv
You will need to set up an environmental variable for runtime GStreamer to be able to open pipeline in OpenCV program. This is not required to build OpenCV with GStreamer.

Opencv Cmake setting

Open Cmake and set basic path, where the source is located and where to build the result
opencv cmake path setting

Tip: Use all path specified in CMake as with this / slash. (when you copy the path from explorer C:\gstreamer\1.0\x86_64 \ causing problems)
  • Hit configure
  • Set the Visual studio 2019 compiler
  • Set extra modules from contrib (/)

  • Set WITH_GSTREMER to yes
  • Set WITH_FFMPEG to yes
  • Set GStremer concrete lib location and header folder, The name of CMAKE Variables is equal to the concrete .lib file
  • INCLUDE_DIR refers to a directory. opencv gstreamer windows cmake
  • HIT configure again
  • Set WITH_CUDA to yes
  • Optionally specify CUDA_TOOLKIT_ROOT_DIR (usually founded automatically)
  • Specify opencv_cuda modules you want to build
    opencv cmake configuration
  • Hit configure
  • Read the messages, if cmake is red and correct the settings. Not all your combination are posible for your HW and SW environment

Check OpenCV CMAKE configuration

I am looking in the CMAKE General configuration for the following information:
 FFMPEG is YES, GSTremer is YES, NVIDIA CUDA is YES, I got all I want.

General configuration for OpenCV 4.4.0 =====================================
  Extra modules:
    Location (extra):            C:/opencv/opencv_contrib-master/opencv_contrib-master/modules
    Version control (extra):     unknown
  Video I/O:
    DC1394:                      NO
    FFMPEG:                      YES (prebuilt binaries)
      avcodec:                   YES (58.54.100)
      avformat:                  YES (58.29.100)
      avutil:                       YES (56.31.100)
      swscale:                    YES (5.5.100)
      avresample:              YES (4.0.0)
    GStreamer:                 YES (1.16.2)
    DirectShow:               YES
    Media Foundation:            YES
      DXVA:                      YES

  NVIDIA CUDA:                   YES (ver 11.0, CUFFT CUBLAS)
  NVIDIA GPU arch:             35 37 50 52 60 61 70 75 80
  NVIDIA PTX archs:

Configuring done

HiT generate and open project in CMAKE and jump to Visual Studio 

  • Hit Generate in CMAKE
  • Hit Open Project in CMAKE

Compile OpenCV, CUDA with GStreamer in Visual Studio

  • Change setting of Visual Studio to Release, x64
  • Right-click on Project ALL_BUILD -> hit build option
  • This will take a lot of time since the CUDA is compiling 
  • IF you compile the project without errors (warnings are ok)
  • Right-click on Project INSTALL -> hit build option

Use your custom Opencv library

Your OpenCV after successfully build of INSTALL project is located here:
Set up your first Visual Studio Project in a standard way. Your library is installed in build_cuda/install. 
Headers are located under include and libs under x64. Enjoy your custom Opencv Library. 

Opencv GStreamer Windows APP tutorial

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