OpenCV is the best open source solution for computer vision and image recognition applications. It exists for all the major platforms. In this post, we are going to see how to set it up in Ubuntu Linux or Linux Mint.
We are looking at OpenCV 3.0.x which is the latest version as of now. Though you can obtain the source using apt-get , it is better to directly download it from the main site, as that is where the latest version is always available.
Step 1. Install Dependencies
We will need cmake to build the OpenCV as its in C++ so we need to update cmake first.
sudo apt-get install build-essential cmake
Next, we install the Qt library
sudo apt-get install qt5-default libvtk6-dev
Install image manipulation libraries
sudo apt-get install zlib1g-dev libjpeg-dev libwebp-dev libpng-dev libtiff5-dev libjasper-dev libopenexr-dev libgdal-dev
Install video manipulation libraries
sudo apt-get install libdc1394-22-dev libavcodec-dev libavformat-dev libswscale-dev libtheora-dev libvorbis-dev libxvidcore-dev libx264-dev yasm libopencore-amrnb-dev libopencore-amrwb-dev libv4l-dev libxine2-dev
Install supporting math libraries
sudo apt-get install libtbb-dev libeigen3-dev
Step 2. Update languages
We need to update python and Java.
sudo apt-get install python-dev python-tk python-numpy python3-dev python3-tk python3-numpy sudo apt-get install
sudo apt-get install ant default-jdk
Step 3: Compile OpenCV
Download the latest source zip from here . On this page click on OpenCV for Linux/Mac which will start the download of the zip file.
Unzip the zip into a directory of your choice. eg. /var/projects/opencv
Make that directory your current directory and type mkdir build so you end up with /var/projects/opencv/build . Go into the build directory cd build
Setup Cmake configuration and run the build.
cmake -DWITH_QT=ON -DWITH_OPENGL=ON -DFORCE_VTK=ON -DWITH_TBB=ON -DWITH_GDAL=ON -DWITH_XINE=ON -DBUILD_EXAMPLES=ON .. make -j4 sudo make install
Run configure with
This completes the setup of OpenCV.
Step 4: Running the Python Samples
Got into the samples folder eg. cd /var/projects/opencv/samples/python2
You will find a lot of samples here.
If you have a cam attached then do python video.py
To run a simple example, try python floodfill.py
You can get a list and explanation of all the samples by running python demo.py
Here is a video of me running the Canny Edge detection sample. python edge.py