文件列表:

Learning-OpenCV-3_examples (0, 2018-04-10)
Learning-OpenCV-3_examples\BlueCup.jpg (5237, 2018-04-10)
Learning-OpenCV-3_examples\CMakeLists.txt (8293, 2018-04-10)
Learning-OpenCV-3_examples\Dockerfile (4231, 2018-04-10)
Learning-OpenCV-3_examples\Exercises_11-1-2-5-6-7.cpp (6470, 2018-04-10)
Learning-OpenCV-3_examples\Exercises_13_1-2-11.cpp (6215, 2018-04-10)
Learning-OpenCV-3_examples\Exercises_13_9.cpp (9078, 2018-04-10)
Learning-OpenCV-3_examples\Exercises_5.cpp (6240, 2018-04-10)
Learning-OpenCV-3_examples\Exercises_7.cpp (4431, 2018-04-10)
Learning-OpenCV-3_examples\Exercises_8_1.cpp (3184, 2018-04-10)
Learning-OpenCV-3_examples\Exercises_9_1-2-10-11-12-15-16.cpp (10318, 2018-04-10)
Learning-OpenCV-3_examples\Exercises_9_4.cpp (2188, 2018-04-10)
Learning-OpenCV-3_examples\Exercises_9_5.cpp (2294, 2018-04-10)
Learning-OpenCV-3_examples\HandIndoorColor.jpg (97472, 2018-04-10)
Learning-OpenCV-3_examples\HandOutdoorColor.jpg (145318, 2018-04-10)
Learning-OpenCV-3_examples\HandOutdoorSunColor.jpg (106007, 2018-04-10)
Learning-OpenCV-3_examples\adrian.jpg (189623, 2018-04-10)
Learning-OpenCV-3_examples\birdseye (0, 2018-04-10)
Learning-OpenCV-3_examples\birdseye\.DS_Store (6148, 2018-04-10)
Learning-OpenCV-3_examples\birdseye\IMG_0214.jpg (317775, 2018-04-10)
Learning-OpenCV-3_examples\birdseye\IMG_0214L.jpg (317832, 2018-04-10)
Learning-OpenCV-3_examples\birdseye\IMG_0215.jpg (325383, 2018-04-10)
Learning-OpenCV-3_examples\birdseye\IMG_0215L.jpg (325446, 2018-04-10)
Learning-OpenCV-3_examples\birdseye\IMG_0217.jpg (302958, 2018-04-10)
Learning-OpenCV-3_examples\birdseye\IMG_0217L.jpg (302321, 2018-04-10)
Learning-OpenCV-3_examples\birdseye\IMG_0218.jpg (296209, 2018-04-10)
Learning-OpenCV-3_examples\birdseye\IMG_0218L.jpg (295342, 2018-04-10)
Learning-OpenCV-3_examples\birdseye\IMG_0219.jpg (297508, 2018-04-10)
Learning-OpenCV-3_examples\birdseye\IMG_0219L.jpg (297073, 2018-04-10)
Learning-OpenCV-3_examples\birdseye\IMG_0220.jpg (348274, 2018-04-10)
Learning-OpenCV-3_examples\birdseye\IMG_0220L.jpg (348262, 2018-04-10)
Learning-OpenCV-3_examples\birdseye\intrinsics.xml (563, 2018-04-10)
Learning-OpenCV-3_examples\box.png (50728, 2018-04-10)
Learning-OpenCV-3_examples\box_in_scene.png (122490, 2018-04-10)
Learning-OpenCV-3_examples\calibration (0, 2018-04-10)
Learning-OpenCV-3_examples\calibration\IMG_0191.jpg (463757, 2018-04-10)
Learning-OpenCV-3_examples\calibration\IMG_0192.jpg (407260, 2018-04-10)
Learning-OpenCV-3_examples\calibration\IMG_0193.jpg (447239, 2018-04-10)
Learning-OpenCV-3_examples\calibration\IMG_0194.jpg (451479, 2018-04-10)
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# Learning OpenCV 3 ## INTRO This is the example code that accompanies Learning OpenCV 3 by Adrian Kaehler and Gary Bradski ([9781491937990](http:*shop.oreilly.com/product/0636920044765.do)). Click the Download Zip button to the right to download example code. Visit the catalog page [here](http:*shop.oreilly.com/product/0636920044765.do). See an error? Report it [here](http:*oreilly.com/catalog/errata.csp?isbn=0636920044765), 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` ## CONTENTS: ### SPECIAL FILES: * README.md -- this readme file * Dockerfile -- complete self contained opencv environment using Ubuntu 16-04 * CMakeLists.txt -- how to buld everything here ### EXERCISES: * 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: Click the Download Zip button to the right to download example code. Visit the catalog page [here](http:*shop.oreilly.com/product/0636920044765.do). See an error? Report it [here](http:*oreilly.com/catalog/errata.csp?isbn=0636920044765), or simply fork and send us a pull request

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