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// Example 13-1. Histogram computation and display | ||
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#include <opencv2/opencv.hpp> | ||
#include <iostream> | ||
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using namespace std; | ||
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int main( int argc, char** argv ){ | ||
if(argc != 2) { | ||
cout << "Computer Color Histogram\nUsage: " <<argv[0] <<" <imagename>" << endl; | ||
return -1; | ||
} | ||
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cv::Mat src = cv::imread( argv[1],1 ); | ||
if( src.empty() ) { cout << "Cannot load " << argv[1] << endl; return -1; } | ||
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// Compute the HSV image, and decompose it into separate planes. | ||
// | ||
cv::Mat hsv; | ||
cv::cvtColor(src, hsv, cv::COLOR_BGR2HSV); | ||
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float h_ranges[] = {0, 180}; // hue is [0, 180] | ||
float s_ranges[] = {0, 256}; | ||
const float* ranges[] = {h_ranges, s_ranges}; | ||
int histSize[] = {30, 32}, ch[] = {0, 1}; | ||
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cv::Mat hist; | ||
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// Compute the histogram | ||
// | ||
cv::calcHist(&hsv, 1, ch, cv::noArray(), hist, 2, histSize, ranges, true); | ||
cv::normalize(hist, hist, 0, 255, cv::NORM_MINMAX); | ||
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int scale = 10; | ||
cv::Mat hist_img(histSize[0]*scale, histSize[1]*scale, CV_8UC3); | ||
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// Draw our histogram. | ||
// | ||
for( int h = 0; h < histSize[0]; h++ ) { | ||
for( int s = 0; s < histSize[1]; s++ ){ | ||
float hval = hist.at<float>(h, s); | ||
cv::rectangle( | ||
hist_img, | ||
cv::Rect(h*scale,s*scale,scale,scale), | ||
cv::Scalar::all(hval), | ||
-1 | ||
); | ||
} | ||
} | ||
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cv::imshow("image", src); | ||
cv::imshow("H-S histogram", hist_img); | ||
cv::waitKey(); | ||
return 0; | ||
} |
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// Example 13-2. Creating signatures from histograms for EMD; note that this code is the | ||
// source of the data in Table 13-1, in which the hand histogram is compared in different | ||
// lighting conditions | ||
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#include <opencv2/opencv.hpp> | ||
#include <iostream> | ||
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using namespace std; | ||
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void help( char** argv ){ | ||
cout << "\nCall is:\n" | ||
<< argv[0] <<" modelImage0 testImage1 testImage2 badImage3\n\n" | ||
<< "for example: " << argv[0] | ||
<< " HandIndoorColor.jpg HandOutdoorColor.jpg " | ||
<< "HandOutdoorSunColor.jpg fruits.jpg\n" | ||
<< "\n"; | ||
} | ||
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// Compare 3 images' histograms | ||
int main( int argc, char** argv ) { | ||
if( argc != 5 ) { help( argv ); return -1; } | ||
vector<cv::Mat> src(5); | ||
cv::Mat tmp; | ||
int i; | ||
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tmp = cv::imread( argv[1], 1); | ||
if( tmp.empty() ) { | ||
cerr << "Error on reading image 1," << argv[1] << "\n" << endl; | ||
help( argv ); | ||
return(-1); | ||
} | ||
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// Parse the first image into two image halves divided halfway on y | ||
// | ||
cv::Size size = tmp.size(); | ||
int width = size.width; | ||
int height = size.height; | ||
int halfheight = height >> 1; | ||
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cout <<"Getting size [[" <<tmp.cols <<"] [" <<tmp.rows <<"]]\n" <<endl; | ||
cout <<"Got size (w,h): (" <<size.width <<"," <<size.height <<")" <<endl; | ||
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src[0] = cv::Mat(cv::Size(width,halfheight), CV_8UC3); | ||
src[1] = cv::Mat(cv::Size(width,halfheight), CV_8UC3); | ||
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// Divide the first image into top and bottom halves into src[0] and src[1] | ||
// | ||
cv::Mat_<cv::Vec3b>::iterator tmpit = tmp.begin<cv::Vec3b>(); | ||
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// top half | ||
// | ||
cv::Mat_<cv::Vec3b>::iterator s0it = src[0].begin<cv::Vec3b>(); | ||
for(i = 0; i < width*halfheight; ++i, ++tmpit, ++s0it) *s0it = *tmpit; | ||
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// Bottom half | ||
// | ||
cv::Mat_<cv::Vec3b>::iterator s1it = src[1].begin<cv::Vec3b>(); | ||
for(i = 0; i < width*halfheight; ++i, ++tmpit, ++s1it) *s1it = *tmpit; | ||
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// Load the other three images | ||
// | ||
for(i = 2; i<5; ++i){ | ||
src[i] = cv::imread(argv[i], 1); | ||
if(src[i].empty()) { | ||
cerr << "Error on reading image " << i << ": " << argv[i] << "\n" << endl; | ||
help( argv ); | ||
return(-1); | ||
} | ||
} | ||
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// Compute the HSV image, and decompose it into separate planes. | ||
// | ||
vector<cv::Mat> hsv(5), hist(5), hist_img(5); | ||
int h_bins = 8; | ||
int s_bins = 8; | ||
int hist_size[] = { h_bins, s_bins }, ch[] = {0, 1}; | ||
float h_ranges[] = { 0, 180 }; // hue range is [0,180] | ||
float s_ranges[] = { 0, 255 }; | ||
const float* ranges[] = { h_ranges, s_ranges }; | ||
int scale = 10; | ||
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for(i = 0; i<5; ++i) { | ||
cv::cvtColor( src[i], hsv[i], cv::COLOR_BGR2HSV ); | ||
cv::calcHist( &hsv[i], 1, ch, cv::noArray(), hist[i], 2, hist_size, ranges, true ); | ||
cv::normalize( hist[i], hist[i], 0, 255, cv::NORM_MINMAX ); | ||
hist_img[i] = cv::Mat::zeros( hist_size[0]*scale, hist_size[1]*scale, CV_8UC3 ); | ||
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// Draw our histogram For the 5 images | ||
// | ||
for( int h = 0; h < hist_size[0]; h++ ) | ||
for( int s = 0; s < hist_size[1]; s++ ) { | ||
float hval = hist[i].at<float>(h, s); | ||
cv::rectangle( | ||
hist_img[i], | ||
cv::Rect(h*scale, s*scale, scale, scale), | ||
cv::Scalar::all(hval), | ||
-1 | ||
); | ||
} | ||
} | ||
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// Display | ||
// | ||
cv::namedWindow( "Source0", 1 );cv::imshow( "Source0", src[0] ); | ||
cv::namedWindow( "HS Histogram0", 1 );cv::imshow( "HS Histogram0", hist_img[0] ); | ||
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cv::namedWindow( "Source1", 1 );cv::imshow( "Source1", src[1] ); | ||
cv::namedWindow( "HS Histogram1", 1 ); cv::imshow( "HS Histogram1", hist_img[1] ); | ||
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cv::namedWindow( "Source2", 1 ); cv::imshow( "Source2", src[2] ); | ||
cv::namedWindow( "HS Histogram2", 1 ); cv::imshow( "HS Histogram2", hist_img[2] ); | ||
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cv::namedWindow( "Source3", 1 ); cv::imshow( "Source3", src[3] ); | ||
cv::namedWindow( "HS Histogram3", 1 ); cv::imshow( "HS Histogram3", hist_img[3] ); | ||
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cv::namedWindow( "Source4", 1 ); cv::imshow( "Source4", src[4] ); | ||
cv::namedWindow( "HS Histogram4", 1 ); cv::imshow( "HS Histogram4", hist_img[4] ); | ||
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// Compare the histogram src0 vs 1, vs 2, vs 3, vs 4 | ||
cout << "Comparison:\n" | ||
<< "Corr Chi Intersect Bhat\n"<< endl; | ||
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for(i=1; i<5; ++i) { // For each histogram | ||
cout << "Hist[0] vs Hist[" << i << "]: " << endl;; | ||
for(int j=0; j<4; ++j) { // For each comparison type | ||
cout << "method[" << j << "]: " << cv::compareHist(hist[0],hist[i],j) << " "; | ||
} | ||
cout << endl; | ||
} | ||
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//Do EMD and report | ||
// | ||
vector<cv::Mat> sig(5); | ||
cout << "\nEMD: " << endl; | ||
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// Oi Vey, parse histograms to earth movers signatures | ||
// | ||
for( i=0; i<5; ++i) { | ||
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vector<cv::Vec3f> sigv; | ||
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// (re)normalize histogram to make the bin weights sum to 1. | ||
// | ||
cv::normalize(hist[i], hist[i], 1, 0, cv::NORM_L1); | ||
for( int h = 0; h < h_bins; h++ ) | ||
for( int s = 0; s < s_bins; s++ ) { | ||
float bin_val = hist[i].at<float>(h, s); | ||
if( bin_val != 0 ) | ||
sigv.push_back( cv::Vec3f(bin_val, (float)h, (float)s)); | ||
} | ||
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// make Nx3 32fC1 matrix, where N is the number of nonzero histogram bins | ||
// | ||
sig[i] = cv::Mat(sigv).clone().reshape(1); | ||
if( i > 0 ) | ||
cout << "Hist[0] vs Hist[" << i << "]: " | ||
<< EMD(sig[0], sig[i], cv::DIST_L2) << endl; | ||
} | ||
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cv::waitKey(0); | ||
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} |
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