Learning OpenCV 3

INTRO

This is the example code that accompanies Learning OpenCV 3 by Adrian Kaehler and Gary Bradski (9781491937990).

Click the Download Zip button to the right to download example code.

Visit the catalog page here.

See an error? Report it here, or simply fork and send us a pull request

NOTES

For default suggestions of how the run the code, it assumes you put your build directory under Learning-OpenCV-3_examples directory.

Thus, from the Learning-OpenCV-3_examples directory:

  mkdir build
  cd build
  cmake ..
  make -j

Docker

For your interest, included here is an Ubuntu Docker file that

Shares a directory with the host operating system
Shares the first camera between both systems
Loads Ubuntu 16.04
Loads all dependencies for OpenCV 3.2 and opencv_contrib
Loads and builds OpenCV 3.2 and opencv_contrib into a build directory
- executable files end up in opencv-3.2.0/build/bin
Next, it git clones the code (and Docker file) for Learning OpenCV 3 and builds it
- executable files end up in Learning_OpenCV-3_examples/build
To get to the top level directory, just type: cd

Exercises at end of Chapter 5
Exercises at end of Chapter 7
Exercises_8_1.cpp Exercises at end of Chapter 8
Exercises_9_1-2-10-11-12-15-16.cpp Exercises at end of Chapter 8
Exercises_9_4.cpp Exercises at end of Chapter 9
Exercises_9_5.cpp Exercises at end of Chapter 9
Exercises at end of Chapter 11
Exercises_13_1-2-11.cpp Exercises for Chapter 13
Exercises_13_9.cpp

EXAMPLES:

Example 2-1. A simple OpenCV program that loads an image from disk and displays it
Example 2-2. Same as Example 2-1 but employing the “using namespace” directive
Example 2-3. A simple OpenCV program for playing a video file from disk
Example 2-4. Adding a trackbar slider to the basic viewer window for moving around
Example 2-5. Loading and then smoothing an image before it is displayed on the screen
Example 2-6. Using cv::pyrDown() to create a new image that is half the width and
Example 2-7. The Canny edge detector writes its output to a single-channel (grayscale) image
Example 2-8. Combining the pyramid down operator (twice) and the Canny
Example 2-9. Getting and setting pixels in Example 2-8
Example 2-10. The same object can load videos from a camera or a file
Example 2-11. A complete program to read in a color video and write out the log-polar-
Example 4-1. Summation of a multidimensional array, done plane by plane
Example 4-2. Summation of two arrays using the N-ary operator
Example 4-3. Printing all of the nonzero elements of a sparse array
Example 4-4. A better way to print a matrix
Example 5-1. Complete program to alpha-blend the ROI starting at (0,0) in src2 with the ROI starting at (x,y) in src1
Example 7-1. Using the default random number generator to generate a pair of integers
Example 8-1. Unpacking a four-character code to identify a video codec
Example 8-2. Using cv::FileStorage to create a .yml data file
Example 8-3. Using cv::FileStorage to read a .yml file
Example 9-1. Creating a window and displaying an image in that window
Example 9-2. Toy program for using a mouse to draw boxes on the screen
Example 9-3. Using a trackbar to create a “switch” tha t the user can turn on and off;
Example 9-4. Slightly modified code from the OpenCV documentation that draws a
Example 9-5. An example program ch4_qt.cpp, which takes a single argument
Example 9-6. The QMoviePlayer object header file QMoviePlayer.hpp
Example 9-7. The QMoviePlayer object source file: QMoviePlayer.cpp
Example 9-8. An example program which takes a single argument
Example 9-9. The WxMoviePlayer object header file WxMoviePlayer.hpp
Example 9-10. The WxMoviePlayer object source file WxMoviePlayer.cpp
Example 9-11. An example header file for our custom View class
Example 10-1. Using cv::threshold() to sum three channels of an image
Example 10-2. Alternative method to combine and threshold image planes
Example 10-3. Threshold versus adaptive threshold
Example 11-1. An affine transformation.
Example 11-2. Code for perspective transformation
Example 11-3. Log-polar transform example
Example 12-1. Using cv::dft() and cv::idft() to accelerate the computation of
Example 12-2. Using cv::HoughCircles() to return a sequence of circles found in a
EXTRA Example 12-3. Using GrabCut for background removal
EXTRA Example 12-4. Using GrabCut for background removal
Example 13-1. Histogram computation and display
Example 13-2. Creating signatures from histograms for EMD; note that this code is the
Example 13-3. Template matching
Example 14-1. Finding contours based on a trackbar’s location; the contours are
Example 14-2. Finding and drawing contours on an input image
Example 14-3. Drawing labeled connected components
Example 14-4. Using the shape context distance extractor
Example 15-1. Reading out the RGB values of all pixels in one row of a video and
Example 15-2. Learning a background model to identify foreground pixels
Example 15-3. Computing the on and off-diagonal elements of a variance/covariance model
Example 15-4. Codebook algorithm implementation
Example 15-5. Cleanup using connected components
EXTRA Example 15-6, using OpenCV's background subtractor class. Modified by Gary Bradski, 6/4/2017
Example 16-1. Pyramid L-K optical flow
EXTRA Example 16-2. 2D Feature detectors and 2D Extra Features framework
Example 17-1. Kalman filter example code
Example 17-2. Farneback optical flow example code
Example 18-1. Reading a chessboard’s width and height, reading them and calibrating
EXTRA Example 18-1. From disk. Reading a chessboard’s width and height, reading them and calibrating
Example 19-1. Bird’s - eye view
Example 19-2. Computing the fundamental matrix using RANSAC
Example 19-3. Stereo calibration, rectification, and correspondence
Example 19-4. Two-dimensional line fitting
Example 20-01. Using K-means
Example 20-02. Using the Mahalanobis distance for classification
Example 21-1. Creating and training a decision tree
Example 22-1. Detecting and drawing faces

IMAGES:

box.png
box_in_scene.png
checkerboard9x6.png
example_16-01-imgA.png
example_16-01-imgB.png
faces.png
BlueCup.jpg
HandIndoorColor.jpg
HandOutdoorColor.jpg
HandOutdoorSunColor.jpg
adrian.jpg
faceScene.jpg
faceTemplate.jpg
fruits.jpg
stuff.jpg

MOVIES:

test.avi
tree.avi

CLASSIFIERS:

haarcascade_frontalcatface.xml #Cat faces!
haarcascade_frontalcatface_extended.xml
haarcascade_frontalface_alt.xml

DIRECTORIES:

birdseye -- where the images are of checkerboards on the floor
build -- you will make and build things in this directory
calibration -- checkerboard images to calibrate on
muchroom -- machine learning database
shape_sample -- silhoette shapes to recognize
stereoData -- left, right image pairs of checkboards to calibrate and view on

LINKS: