Skip to main content

Featured Post

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
Post a Comment

Opencv 3.1 Visual Studio 2015 support

Opencv 3.1 Visual studio 2015

Share this for more tutorials and computer vision post from me.. Thanks best Vladimir

Opencv 3.1 Visual Studio 2015


Opencv 3.1 just released with prebuild VC14 libs for Visual Studio 2015. Installation is easy and you can follow standard tutorials on www.opencv.org

Quick start with Visual Studio 2015 Opencv 3.1

This process is exatly same as in other version with prebuild libs. 

Install opencv 3.1 in visual studio

Shortened procedure summary
  1. Download opencv 3.1 for windows
  2. extract to folder like c:/opencv
  3. Set enviroment varibales by setx -m
This depends on your path
setx -m OPENCV_DIR C:\opencv\build\x64\vc14
     4. In Path editor just set 
%OPENCV_DIR%\bin

This is important steps. If you include Opencv project without this Project in visual studio failed because the project can not find DLL library. 

 Set project in Visual Studio 2015

Just create your new opencv project in Visual Studio 2015 and follow this steps. 

  1. Under Project setting C/C++/General set Additional Include Directories and Additional #using Directories. For example C:\opencv\build\include
  2. Under Linker/general set Additional library directories you can use your system path set in installation process or simple include this path for 64 bit versin for example C:\opencv\build\x64\vc14\lib
  3. Under Linker/Input set Additional Dependencies as opencv_world310.lib, opencv_world310d.lib

Opencv 3.1 prebuild libs 

This  opencv 3.1 comes with many version. This is a list of released parts here Github Source

OpenCV-3.1.0-android-sdk.zip

Prebuild framework for android development 

opencv-3.1.0.exe

 for Windows development and Visual Studio 2015 support. 

opencv2.framework.zip

for iOS and Mac development prebuild framework


Opencv source code

Also there is a source code released of 3.1 opencv which is mainly for Linux and Arm development with many improvements in NEON arm platform. 

Important from Opencv 3.1 change logs

Taken from ChangeLog
  • The iOS framework (opencv2.framework) can now be configured to include both opencv and opencv_contrib functionality.
  • more efficient camera support on Android 5+
  • faster round() on ARM (it’s also applicable to iOS); big thanks to Manuele Tamburano and Stefano Fabri for this!
  • OpenCV 3.1 supports fresh OSes from Microsoft and Apple, as well as the newest development tools (VS2015 and Xcode 7, respectively).
  • IPPICV (a specially-for-opencv free-of-charge subset of IPP (https://software.intel.com/en-us/intel-ipp) that has been kindly provided by Intel Corporation) is now based on IPP 9.0.1, which should make OpenCV even faster on modern Intel chips.
  • There are multiple new features in the OpenCL layer, resulted from our collaboration with Intel Corporation
  • Improved/extended interoperability with DirectX 9, 10, 11


Selected contributed functionality of Opencv 3.1

  • 3x faster SimpleFlow – optflow 
  • Improved performance of haartraining 
  • Unscented Kalman Filter 
  • Efficient Graph-based image segmentation algorithm

Selected Improvements in Opencv 3.1 contrib modules

  • Improved Deformable Part-based Models – opencv_contrib/dpm
  • Real-time Multi-object Tracking using Kernelized Correlation Filter – opencv_contrib/tracking
  • Implementation of universal interface for deep neural network frameworks – opencv_contrib/dnn
  • Improved ICF detector, waldboost implementation – opencv_contrib/xobjdetect
  • Multi-target TLD tracking – opencv_contrib/tracking



Labels:

Comments

  1. YouLoseBellyFatSeptember 21, 2016 at 2:57 AM

    java codings with examples

    ReplyDelete
  2. Pavel K.October 12, 2016 at 2:41 AM

    Hello.. I had a problem with debug mode.
    I followed this tutorial and also tried this tutorial: http://funvision.blogspot.cz/2015/11/install-opencv-visual-studio-2015.html

    But older one doesn't work at all for OpenCV 3.1, and if I followed this one, during debug mode I get this error: https://dl.dropboxusercontent.com/u/30821905/ZScreen/2016-10/ano1.exe_-_Systmov_chyba-2016-10-12_10.50.47.png

    Can you help me please?

    ReplyDelete
    Replies
    1. VlNovember 7, 2016 at 12:12 PM

      Ahoj, tady zalezi na hodne vecech. Me to funguje.. Osobne uz jsem opencv pres rok nekompiloval ani neinstaloval. Uz si s tim jen hraju.. Vyzkousel NUGET PACKAGES. Popsal jsem to tady http://funvision.blogspot.com/2016/08/easy-opencv-31-opencv-2413-instalation.html Obecne staci najit ve visual studiu package nuget konzoli a dat tam jmeno balicku. Problem klasicke instalace je v nastaveni environmental variables. Navic se to muze zadrhnout na hodne vecech.. Treba haar kaskady, detectmultiscale atd. funguji v release ale ne v debug v hodne pripadech opencv..
      Opencv Default Build 3.1.0

      PM> Install-Package opencvdefault

      Delete
  3. UnknownOctober 27, 2016 at 9:23 PM

    I also have problem with it.
    I all followed the instructions here.
    But it has still errors.

    ReplyDelete
    Replies
    1. VlNovember 7, 2016 at 12:13 PM

      Try nugets packages in Visual studio 2015. Best options for less skilled people.. Install under 2 minutes on any project. http://funvision.blogspot.com/2016/08/easy-opencv-31-opencv-2413-instalation.html

      Delete
  4. VlNovember 7, 2016 at 12:14 PM

    Try nugets packages in Visual studio 2015. Best options for less skilled people.. Install under 2 minutes on any project. Works. I am using only this approach right now. All my staff works without aby problems and setting projects again and again. http://funvision.blogspot.com/2016/08/easy-opencv-31-opencv-2413-instalation.html

    ReplyDelete
  5. bashaMarch 23, 2019 at 4:47 AM

    Excellent blog I visit this blog it's really awesome. The important thing is that in this blog content written clearly and understandable. The content of information is very informative.
    Oracle Fusion HCM Online Training
    Oracle Fusion SCM Online Training
    Oracle Fusion Financials Online Training
    Big Data and Hadoop Training In Hyderabad
    oracle fusion financials classroom training
    Workday HCM Online Training
    Oracle Fusion HCM Classroom Training
    Workday HCM Online Training

    ReplyDelete

Post a Comment

Popular

Opencv GStreamer (windows) video streaming tutorial + full source code for RTSP HLS streaming

Opencv C++ simple tutorial to use GStreamer to send video to Server that converts RTSP to HLS video stream. The source code and all needed configurations are included.  O pencv is a powerful computer vision library. You can use it in production and use it for image and video processing and modern machine learning. In some applications, You may want to stream your processed video results from your C++ OpenCV app outside and not just use a simple OpenCV graphical interface. The video streaming of your results is what you are looking for. Do you want to stream processed video from your IoT device? Yes, This is mainly for Linux. Do you want to stream processed video to the Web player, broadcast the video or just use VLC to play video processed by OpenCV? You may be interested in reading the next lines.  Opencv video stream to VLC or WEB There are basically two main options with OpenCV. The first one is to write a streaming application using FFMPEG. This is a little bit more advanced appro
Post a Comment
Read more

Opencv Web camera and Video streams in Windows subsystem for Linux WSL, by FFmpeg and GStreamer

Opencv in Windows Subsystem for Linux (WSL) is a compatibility layer designed to running Linux binary executables (in ELF format) natively on Windows 10. I love it. There are some limitations to mention. The first biggest is the lack of support of CUDA, which could be a limitation for deep learning application and learning in WSL. The second trouble for Opencv development is the lack of Web camera support. This suspends WSL almost on a useless level for me until now.  VideoCapture cap;   is not working in WSL for now cap.open(0);  FFMPEG to WSL opencv program and back to WEB browser in windows This Video capture is right now not possible at in Ubuntu running under Windows (WSL). I will hit this limitation in this article. I will show you how to reach a video camera and learn something more about video streaming. Yes, the opencv processed frames will be stream to the web player on simple web site. Check the goal of this opencv tutorial on this video What you will learn
1 comment
Read more

Compile Opencv with GStreamer for Visual Studio 2019 on windows 10 with and contribution modules

The goal of this tutorial is a simple step by step compilation of Opencv 4.2 with contribution extra modules with GStreamer as a bonus. The environment is Windows 10, Visual Studio 2019 C++ application. This took me almost one day of correcting of CMake setting. The goal of this tutorial is: compiled a set of OpenCV libraries with GStreamer and FFmpeg on Windows. I focus mainly on GStreamer. It is a little bit more tricky. You will reach the following information about your Opencv environment by compile and run this simple code. The Opencv GStreamer is turned as YES. GStreamer gives you a great opportunity to stream OpenCV output video outside of your program, for example, web application. I recently compiled with opencv 4.4. The update at the end of the post.  It is working!! wow, The working app and configuration in future tutorials. #include   <opencv2/opencv.hpp> #include   <iostream> using namespace cv; int   main () {      std ::cout <<  &q
6 comments
Read more

Opencv HSL video stream to web

This tutorial will show you all components, configuration, and code needed to steam video output results from Opencv C++ to your Web player. The C++ program will take any video input and process this video. The processed video will be stream outside of OpenCV using the GStreamer pipeline (Windows part). The HLS video produces one Playlist file and several MPEG-TS segments of videos. This several HLS outputs are stored in the Windows file system. I am using WSL 2, windows subsystem for Linux to run Ubuntu distribution. Here the NGINX is installed with the RTMP module. NGINX is distributing a video stream from the windows file system to the web.  Let's have a look at this in more detail.  What is covered? Opencv C++ part + GStreamer pipeline NGINX configuration Architecture Web Player for your HLS stream What is not covered? Detailed instalation of Opencv + Gstreamer more here  GStreamer installation  ,  GStreamer Installation 2  on windows Detailed installation of NGINX + RTMP modul
Post a Comment
Read more

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
Post a Comment
Read more

Opencv C++ Tutorial Mat resize

Opencv Mat Resize   Resize the Mat or Image in the Opencv C++ tutorial. It is obviously simple task and important to learn. This tutorial is visualized step by step and well-described each of them. The main trick is in that simple code. Mat Input; Mat Resized; int ColumnOfNewImage = 60; int RowsOfNewImage = 60; resize(Input, Resized, Size( ColumnOfNewImage , RowsOfNewImage )); This code just takes an Input image and resized save to output Mat. How big is the resized image is based on the Size? Size just contains two parameters. Simple numbers of how the result should be big. The simple number of columns (width) and rows (height). That is basically it. Enjoy                                                 Boring same face again and again.  Load Image, resize and save Opencv C++ #include <Windows.h> #include "opencv2\highgui.hpp" #include "opencv2\imgproc.hpp" #include "opencv2\video\background_segm.hpp" #include &qu
12 comments
Read more

Opencv C++ tutorial : Smoothing, blur, noise reduction / canceling

Smooth or blur, gaussian blur, and noise-canceling, This tutorial will learn OpenCV blur, GaussianBlur, median blur functions in C++. Additionally, the advanced technique for noise reduction  fastNlMeansDenoising family  will be introduced with a code example for each method.   You can use blurring of the image to hide identity or reduce the noise of the image.  Blur can be a very useful operation and it is a very common operation as well. For example, the anonymization of pedestrians, face or is one possible target for blue operation. The blur is the most common task to perform over the image to reduce noise. The noise reduction is more task for Gaussian blur than for simple blur operation. The various blur operations are very common for image processing on mobile devices.  The more important is the robustness issues of the data in pre-processing for machine learning. Sometimes, by blurring the images of the dataset can have a positive effect on the robustness of the achieved de
Post a Comment
Read more

Opencv tutorial RTMP video streaming to NGINX restream as HLS

Video streaming Tutorial of sending processed Opencv video to NGINX and distributing video from NGINX (broadcast) by HLS stream for a wider audience, like multiple web players, VLC, or any other video stream receiver. Opencv application HLS streaming by GStreamer and NGINX  We will use GStreamer to send video from the Opencv application by rtmp2sink to an RTMP module in NGINX. In our example, the server is a widely used NGINX server with an Nginx-RTMP-module. The NGINX will receive RTMP video from Opencv and restream as an HLS video stream considered for multiple end consumers. This is a follow-up to the previous article about Video streaming from Opencv to RtspSimpleServer by rtsp protocol.   The goal is the same. Send video from Opencv to the server and restream the video for a wider audience. The difference is that RtspSimpleServer running on windows, NGINX is running in docker (WSL2). The one-to-one communication between Opencv and RtspSimpleServer was established by RTSP protocol
Post a Comment
Read more

Opencv 4 C++ Tutorial simple Background Subtraction

This method is used to learn what belongs to the background of the image and what belongs to the foreground. The static cameras that monitor the area can very easily recognize, what is part of the image that is always here or there is something that is new and moving over the background.  Background subtraction Visual studio 2019 project setup If you have Opencv 4+ compiled or installed only steps you need to do is set the include directory with OpenCV header files. Set the Additional library Directories that point to \lib folder. Just note that Visual Studio 2019 should use VC16 \lib. Finally, As additional dependencies, specify the libs used to resolve the function implementation in the code. The list for Opencv 420 is here. The different version of opencv is using different numbering for example opencv 440 will use opencv_core440.lib.  opencv_bgsegm420.lib opencv_core420.lib opencv_videoio420.lib opencv_imgproc420.lib opencv_highgui420.lib opencv_video420.lib  Background sustract
23 comments
Read more

Opencv VideoCapture File, Web Camera, RTSP stream

Opencv VideoCapture File, Camera and stream Opencv tutorial simple code in C++ to capture video from File, Ip camera stream and also the web camera plug into the computer. The key is to have installed the FFMPEG especially in case of reading the stream of IP cameras. In windows just use Opencv Installation by Nugets packages  Here . Simple easy under 2 minutes of installation. In Linux, you need to follow the instruction below. If you are on Debian Like package system. Under Fedora Red hat dist just use a different approach. Code is simple and installation is the key..  Windows use nugets packages Linux you have to install and build Opencv With FFMPEG. Also simple.  It is easy to capture video in OpenCV Video capture  in OpenCV is a really easy task, but for a little bit experienced user.  What is the problem? The problem is the installation of Opencv without recommended dependencies. Just install all basic libs that are recommended on the website. # Basic packa
27 comments
Read more