What is Computer Vision ?
Computer vision is an interdisciplinary field that deals with how computers can be made to gain high-level understanding from digital images or videos.
From the perspective of engineering, it seeks to automate tasks that the human visual system can do.
Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g., in the forms of decisions.
What is Digital Image Processing ?
Computer vision relies heavily upon and Venn-diagrams with digital image processing, which is also what it sounds like, but it’s different. The following tasks could be said to fall under the scope of digital image processing:
- Pattern recognition: Self-explanatory. Find the regularities.
- Feature Extraction: Breaking down an image into distinct features.
- Classification: Does this cluster of edges/shapes seem like a car? A dog?
- Multi-scale signal analysis: What are some other ways to see this image?
- Graphical Projection: How do we represent a 3d object in 2d?
Prerequisites
- Preferrably Ubuntu with python3.
- Knowledge of Python and it's numpy library.
- Passion for problem solving.
- Basic maths.
Installion of OpenCV
In this tutorial We will learn to setup OpenCV-Python in Ubuntu System. Below steps are tested for Ubuntu 16.04 (64-bit) and Ubuntu 14.04 (32-bit).
OpenCV-Python can be installed in Ubuntu in two ways:
- Install from pre-built binaries available in Ubuntu repositories
- Compile from the source. In this section, we will see both.
Another important thing is the additional libraries required. OpenCV-Python requires only Numpy (in addition to other dependencies, which we will see later). But in this tutorials, we also use Matplotlib for some easy and nice plotting purposes (which I feel much better compared to OpenCV). Matplotlib is optional, but highly recommended. Similarly we will also see IPython, an Interactive Python Terminal, which is also highly recommended.
Installing OpenCV-Python from Pre-built Binaries
This method serves best when using just for programming and developing OpenCV applications.
Install package python-opencv with following command in terminal (as root user).
$ sudo apt-get install python-opencv
Open Python IDLE (or IPython) and type following codes in Python terminal.
import cv2 as cv
print(cv.__version__)
If the results are printed out without any errors, congratulations !!! You have installed OpenCV-Python successfully.
It is quite easy. But there is a problem with this. Apt repositories may not contain the latest version of OpenCV always. For example, at the time of writing this tutorial, apt repository contains 2.4.8 while latest OpenCV version is 3.x. With respect to Python API, latest version will always contain much better support and latest bug fixes.
So for getting latest source codes preference is next method, i.e. compiling from source. Also at some point in time, if you want to contribute to OpenCV, you will need this.
Building OpenCV from source
Compiling from source may seem a little complicated at first, but once you succeeded in it, there is nothing complicated.
First we will install some dependencies. Some are required, some are optional. You can skip optional dependencies if you don't want.
Required build dependencies
We need CMake to configure the installation, GCC for compilation, Python-devel and Numpy for building Python bindings etc.
$ sudo apt-get install cmake
$ sudo apt-get install python-devel numpy
$ sudo apt-get install gcc gcc-c++
Next we need GTK support for GUI features, Camera support (libv4l), Media Support (ffmpeg, gstreamer) etc.
$ sudo apt-get install gtk2-devel
$ sudo apt-get install libv4l-devel
$ sudo apt-get install ffmpeg-devel
$ sudo apt-get install gstreamer-plugins-base-devel
Optional Dependencies
Above dependencies are sufficient to install OpenCV in your Ubuntu machine. But depending upon your requirements, you may need some extra dependencies. A list of such optional dependencies are given below. You can either leave it or install it, your call :)
OpenCV comes with supporting files for image formats like PNG, JPEG, JPEG2000, TIFF, WebP etc. But it may be a little old. If you want to get latest libraries, you can install development files for system libraries of these formats.
$ sudo apt-get install libpng-devel
$ sudo apt-get install libjpeg-turbo-devel
$ sudo apt-get install jasper-devel
$ sudo apt-get install openexr-devel
$ sudo apt-get install libtiff-devel
$ sudo apt-get install libwebp-devel
Downloading OpenCV
To download the latest source from OpenCV's GitHub Repository. (If you want to contribute to OpenCV choose this. For that, you need to install Git first)
$ sudo apt-get install git
$ git clone https://github.com/opencv/opencv.git
It will create a folder "opencv" in current directory. The cloning may take some time depending upon your internet connection.
Now open a terminal window and navigate to the downloaded "opencv" folder. Create a new "build" folder and navigate to it.
$ mkdir build
$ cd build
Configuring and Installing
Now we have all the required dependencies, let's install OpenCV. Installation has to be configured with CMake. It specifies which modules are to be installed, installation path, which additional libraries to be used, whether documentation and examples to be compiled etc. Most of this work are done automatically with well configured default parameters.
Below command is normally used for configuration of OpenCV library build (executed from build folder):
$ cmake ../
OpenCV defaults assume "Release" build type and installation path is "/usr/local". For additional information about CMake options refer to OpenCV C++ compilation guide:
You should see these lines in your CMake output (they mean that Python is properly found):
-- Python 2:
-- Interpreter: /usr/bin/python2.7 (ver 2.7.6)
-- Libraries: /usr/lib/x86_64-linux-gnu/libpython2.7.so (ver 2.7.6)
-- numpy: /usr/lib/python2.7/dist-packages/numpy/core/include (ver 1.8.2)
-- packages path: lib/python2.7/dist-packages
--
-- Python 3:
-- Interpreter: /usr/bin/python3.4 (ver 3.4.3)
-- Libraries: /usr/lib/x86_64-linux-gnu/libpython3.4m.so (ver 3.4.3)
-- numpy: /usr/lib/python3/dist-packages/numpy/core/include (ver 1.8.2)
-- packages path: lib/python3.4/dist-packages
Now you build the files using "make" command and install it using "make install" command.
$ make
# sudo make install
Installation is over. All files are installed in "/usr/local/" folder. Open a Python terminal and try import "cv2".
import cv2 as cv
print(cv.__version__)
