initial commit
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Before Width: | Height: | Size: 21 KiB |
Before Width: | Height: | Size: 11 KiB |
@ -23,7 +23,7 @@ const char* keys =
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"{c camera | | use camera or not}"
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"{m method |mog2 | method (knn or mog2) }"
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"{s smooth | | smooth the mask }"
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"{fn file_name|tree.avi | movie file }"
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"{fn file_name|../data/tree.avi | movie file }"
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};
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//this is a sample for foreground detection functions
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@ -36,14 +36,14 @@ static void help()
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{
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cout << "\n This program demonstrates connected components and use of the trackbar\n"
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"Usage: \n"
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" ./connected_components <image(stuff.jpg as default)>\n"
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" ./connected_components <image(../data/stuff.jpg as default)>\n"
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"The image is converted to grayscale and displayed, another image has a trackbar\n"
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"that controls thresholding and thereby the extracted contours which are drawn in color\n";
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}
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const char* keys =
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{
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"{@image|stuff.jpg|image for converting to a grayscale}"
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"{@image|../data/stuff.jpg|image for converting to a grayscale}"
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};
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int main( int argc, const char** argv )
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@ -59,12 +59,12 @@ static void updateBrightnessContrast( int /*arg*/, void* )
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static void help()
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{
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std::cout << "\nThis program demonstrates the use of calcHist() -- histogram creation.\n"
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<< "Usage: \n" << "demhist [image_name -- Defaults to baboon.jpg]" << std::endl;
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<< "Usage: \n" << "demhist [image_name -- Defaults to ../data/baboon.jpg]" << std::endl;
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}
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const char* keys =
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{
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"{@image|baboon.jpg|input image file}"
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"{@image|../data/baboon.jpg|input image file}"
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};
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int main( int argc, const char** argv )
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@ -14,12 +14,12 @@ static void help()
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printf("\nThis program demonstrated the use of the discrete Fourier transform (dft)\n"
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"The dft of an image is taken and it's power spectrum is displayed.\n"
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"Usage:\n"
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"./dft [image_name -- default lena.jpg]\n");
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"./dft [image_name -- default ../data/lena.jpg]\n");
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}
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const char* keys =
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{
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"{@image|lena.jpg|input image file}"
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"{@image|../data/lena.jpg|input image file}"
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};
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int main(int argc, const char ** argv)
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@ -91,7 +91,7 @@ static void help()
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{
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printf("\nProgram to demonstrate the use of the distance transform function between edge images.\n"
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"Usage:\n"
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"./distrans [image_name -- default image is stuff.jpg]\n"
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"./distrans [image_name -- default image is ../data/stuff.jpg]\n"
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"\nHot keys: \n"
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"\tESC - quit the program\n"
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"\tC - use C/Inf metric\n"
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@ -107,7 +107,7 @@ static void help()
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const char* keys =
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{
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"{@image |stuff.jpg|input image file}"
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"{@image |../data/stuff.jpg|input image file}"
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};
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int main( int argc, const char** argv )
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@ -28,12 +28,12 @@ static void help()
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{
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printf("\nThis sample demonstrates Canny edge detection\n"
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"Call:\n"
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" /.edge [image_name -- Default is fruits.jpg]\n\n");
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" /.edge [image_name -- Default is ../data/fruits.jpg]\n\n");
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}
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const char* keys =
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{
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"{@image |fruits.jpg|input image name}"
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"{@image |../data/fruits.jpg|input image name}"
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};
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int main( int argc, const char** argv )
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@ -118,8 +118,8 @@ int main( int argc, const char** argv )
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}
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else
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{
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image = imread( "lena.jpg", 1 );
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if(image.empty()) cout << "Couldn't read lena.jpg" << endl;
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image = imread( "../data/lena.jpg", 1 );
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if(image.empty()) cout << "Couldn't read ../data/lena.jpg" << endl;
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}
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cvNamedWindow( "result", 1 );
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@ -12,7 +12,7 @@ static void help()
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{
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cout << "\nThis program demonstrated the floodFill() function\n"
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"Call:\n"
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"./ffilldemo [image_name -- Default: fruits.jpg]\n" << endl;
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"./ffilldemo [image_name -- Default: ../data/fruits.jpg]\n" << endl;
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cout << "Hot keys: \n"
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"\tESC - quit the program\n"
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@ -73,7 +73,7 @@ static void onMouse( int event, int x, int y, int, void* )
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int main( int argc, char** argv )
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{
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char* filename = argc >= 2 ? argv[1] : (char*)"fruits.jpg";
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char* filename = argc >= 2 ? argv[1] : (char*)"../data/fruits.jpg";
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image0 = imread(filename, 1);
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if( image0.empty() )
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@ -85,8 +85,8 @@ int main(int ac, char** av)
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cout << "writing images\n";
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fs << "images" << "[";
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fs << "image1.jpg" << "myfi.png" << "baboon.jpg";
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cout << "image1.jpg" << " myfi.png" << " baboon.jpg" << endl;
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fs << "image1.jpg" << "myfi.png" << "../data/baboon.jpg";
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cout << "image1.jpg" << " myfi.png" << " ../data/baboon.jpg" << endl;
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fs << "]";
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@ -27,7 +27,7 @@ using namespace std;
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// "\nThis program is demonstration for ellipse fitting. The program finds\n"
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// "contours and approximate it by ellipses.\n"
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// "Call:\n"
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// "./fitellipse [image_name -- Default stuff.jpg]\n" << endl;
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// "./fitellipse [image_name -- Default ../data/stuff.jpg]\n" << endl;
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// }
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int sliderPos = 70;
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@ -38,7 +38,7 @@ void processImage(int, void*);
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int main( int argc, char** argv )
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{
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const char* filename = argc == 2 ? argv[1] : (char*)"stuff.jpg";
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const char* filename = argc == 2 ? argv[1] : (char*)"../data/stuff.jpg";
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image = imread(filename, 0);
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if( image.empty() )
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{
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@ -11,12 +11,12 @@ static void help()
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{
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cout << "\nThis program demonstrates circle finding with the Hough transform.\n"
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"Usage:\n"
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"./houghcircles <image_name>, Default is pic1.png\n" << endl;
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"./houghcircles <image_name>, Default is ../data/board.jpg\n" << endl;
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}
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int main(int argc, char** argv)
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{
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const char* filename = argc >= 2 ? argv[1] : "board.jpg";
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const char* filename = argc >= 2 ? argv[1] : "../data/board.jpg";
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Mat img = imread(filename, 0);
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if(img.empty())
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@ -11,12 +11,12 @@ static void help()
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{
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cout << "\nThis program demonstrates line finding with the Hough transform.\n"
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"Usage:\n"
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"./houghlines <image_name>, Default is pic1.png\n" << endl;
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"./houghlines <image_name>, Default is ../data/pic1.png\n" << endl;
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}
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int main(int argc, char** argv)
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{
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const char* filename = argc >= 2 ? argv[1] : "pic1.png";
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const char* filename = argc >= 2 ? argv[1] : "../data/pic1.png";
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Mat src = imread(filename, 0);
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if(src.empty())
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@ -14,7 +14,7 @@ static void help()
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"It shows reading of images, converting to planes and merging back, color conversion\n"
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"and also iterating through pixels.\n"
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"Call:\n"
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"./image [image-name Default: lena.jpg]\n" << endl;
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"./image [image-name Default: ../data/lena.jpg]\n" << endl;
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}
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// enable/disable use of mixed API in the code below.
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@ -28,7 +28,7 @@ static void help()
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int main( int argc, char** argv )
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{
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help();
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const char* imagename = argc > 1 ? argv[1] : "lena.jpg";
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const char* imagename = argc > 1 ? argv[1] : "../data/lena.jpg";
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#if DEMO_MIXED_API_USE
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Ptr<IplImage> iplimg(cvLoadImage(imagename)); // Ptr<T> is safe ref-counting pointer class
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if(!iplimg)
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@ -3,7 +3,7 @@
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* findTransformECC that implements the image alignment ECC algorithm
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*
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*
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* The demo loads an image (defaults to fruits.jpg) and it artificially creates
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* The demo loads an image (defaults to ../data/fruits.jpg) and it artificially creates
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* a template image based on the given motion type. When two images are given,
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* the first image is the input image and the second one defines the template image.
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* In the latter case, you can also parse the warp's initialization.
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@ -44,7 +44,7 @@ static void draw_warped_roi(Mat& image, const int width, const int height, Mat&
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const std::string keys =
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"{@inputImage | fruits.jpg | input image filename }"
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"{@inputImage | ../data/fruits.jpg | input image filename }"
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"{@templateImage | | template image filename (optional)}"
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"{@inputWarp | | input warp (matrix) filename (optional)}"
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"{n numOfIter | 50 | ECC's iterations }"
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@ -64,7 +64,7 @@ static void help(void)
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" are given, the initialization of the warp by command line parsing is possible. "
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"If inputWarp is missing, the identity transformation initializes the algorithm. \n" << endl;
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cout << "\nUsage example (one image): \n./ecc fruits.jpg -o=outWarp.ecc "
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cout << "\nUsage example (one image): \n./ecc ../data/fruits.jpg -o=outWarp.ecc "
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"-m=euclidean -e=1e-6 -N=70 -v=1 \n" << endl;
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cout << "\nUsage example (two images with initialization): \n./ecc yourInput.png yourTemplate.png "
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@ -14,7 +14,7 @@ static void help()
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<< "with surrounding image areas.\n"
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"Using OpenCV version %s\n" << CV_VERSION << "\n"
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"Usage:\n"
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"./inpaint [image_name -- Default fruits.jpg]\n" << endl;
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"./inpaint [image_name -- Default ../data/fruits.jpg]\n" << endl;
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cout << "Hot keys: \n"
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"\tESC - quit the program\n"
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@ -47,7 +47,7 @@ static void onMouse( int event, int x, int y, int flags, void* )
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int main( int argc, char** argv )
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{
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char* filename = argc >= 2 ? argv[1] : (char*)"fruits.jpg";
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char* filename = argc >= 2 ? argv[1] : (char*)"../data/fruits.jpg";
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Mat img0 = imread(filename, -1);
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if(img0.empty())
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{
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@ -489,7 +489,7 @@ int main( int argc, char *argv[] )
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{
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string filename_to_save = "";
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string filename_to_load = "";
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string data_filename = "./letter-recognition.data";
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string data_filename = "../data/letter-recognition.data";
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int method = 0;
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int i;
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@ -83,7 +83,7 @@ static float calculateAccuracyPercent(const Mat &original, const Mat &predicted)
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int main()
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{
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const String filename = "data01.xml";
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const String filename = "../data/data01.xml";
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cout << "**********************************************************************" << endl;
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cout << filename
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<< " contains digits 0 and 1 of 20 samples each, collected on an Android device" << endl;
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Before Width: | Height: | Size: 939 B |
Before Width: | Height: | Size: 94 KiB |
@ -15,8 +15,8 @@ int main(int argc, char** argv)
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std::string in;
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if (argc != 2)
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{
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std::cout << "Usage: lsd_lines [input image]. Now loading building.jpg" << std::endl;
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in = "building.jpg";
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std::cout << "Usage: lsd_lines [input image]. Now loading ../data/building.jpg" << std::endl;
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in = "../data/building.jpg";
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}
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else
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{
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@ -58,7 +58,7 @@ static void ErodeDilate(int, void*)
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int main( int argc, char** argv )
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{
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char* filename = argc == 2 ? argv[1] : (char*)"baboon.jpg";
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char* filename = argc == 2 ? argv[1] : (char*)"../data/baboon.jpg";
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if( (src = imread(filename,1)).empty() )
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return -1;
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Before Width: | Height: | Size: 631 KiB |
Before Width: | Height: | Size: 109 KiB |
Before Width: | Height: | Size: 109 KiB |
@ -17,7 +17,7 @@ static void help()
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{
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printf("\n"
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"This program demonstrates a method for shape comparisson based on Shape Context\n"
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"You should run the program providing a number between 1 and 20 for selecting an image in the folder shape_sample.\n"
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"You should run the program providing a number between 1 and 20 for selecting an image in the folder ../data/shape_sample.\n"
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"Call\n"
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"./shape_example [number between 1 and 20]\n\n");
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}
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@ -55,7 +55,7 @@ static vector<Point> simpleContour( const Mat& currentQuery, int n=300 )
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int main(int argc, char** argv)
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{
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help();
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string path = "./shape_sample/";
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string path = "../data/shape_sample/";
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int indexQuery = 1;
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if( argc < 2 )
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{
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@ -142,8 +142,8 @@ static void drawSquares( Mat& image, const vector<vector<Point> >& squares )
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int main(int /*argc*/, char** /*argv*/)
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{
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static const char* names[] = { "pic1.png", "pic2.png", "pic3.png",
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"pic4.png", "pic5.png", "pic6.png", 0 };
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static const char* names[] = { "../data/pic1.png", "../data/pic2.png", "../data/pic3.png",
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"../data/pic4.png", "../data/pic5.png", "../data/pic6.png", 0 };
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help();
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namedWindow( wndname, 1 );
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vector<vector<Point> > squares;
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@ -212,7 +212,7 @@ StereoCalib(const vector<string>& imagelist, Size boardSize, bool useCalibrated=
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cout << "average reprojection err = " << err/npoints << endl;
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// save intrinsic parameters
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FileStorage fs("intrinsics.yml", FileStorage::WRITE);
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FileStorage fs("../data/intrinsics.yml", FileStorage::WRITE);
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if( fs.isOpened() )
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{
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fs << "M1" << cameraMatrix[0] << "D1" << distCoeffs[0] <<
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@ -382,7 +382,7 @@ int main(int argc, char** argv)
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if( imagelistfn == "" )
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{
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imagelistfn = "stereo_calib.xml";
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imagelistfn = "../data/stereo_calib.xml";
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boardSize = Size(9, 6);
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}
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else if( boardSize.width <= 0 || boardSize.height <= 0 )
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Before Width: | Height: | Size: 83 KiB |
Before Width: | Height: | Size: 83 KiB |
@ -14,14 +14,14 @@ static void help(char* progName)
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<< "This program demonstrated the use of the discrete Fourier transform (DFT). " << endl
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<< "The dft of an image is taken and it's power spectrum is displayed." << endl
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<< "Usage:" << endl
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<< progName << " [image_name -- default lena.jpg] " << endl << endl;
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<< progName << " [image_name -- default ../data/lena.jpg] " << endl << endl;
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}
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int main(int argc, char ** argv)
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{
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help(argv[0]);
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const char* filename = argc >=2 ? argv[1] : "lena.jpg";
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const char* filename = argc >=2 ? argv[1] : "../data/lena.jpg";
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Mat I = imread(filename, IMREAD_GRAYSCALE);
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if( I.empty())
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|
@ -80,7 +80,7 @@ int main(int ac, char** av)
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fs << "iterationNr" << 100;
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fs << "strings" << "["; // text - string sequence
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fs << "image1.jpg" << "Awesomeness" << "baboon.jpg";
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fs << "image1.jpg" << "Awesomeness" << "../data/baboon.jpg";
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fs << "]"; // close sequence
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fs << "Mapping"; // text - mapping
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|
@ -17,7 +17,7 @@ static void help( char* progName)
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<< "Also contains example for image read, spliting the planes, merging back and " << endl
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<< " color conversion, plus iterating through pixels. " << endl
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<< "Usage:" << endl
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<< progName << " [image-name Default: lena.jpg]" << endl << endl;
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<< progName << " [image-name Default: ../data/lena.jpg]" << endl << endl;
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}
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// comment out the define to use only the latest C++ API
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@ -31,7 +31,7 @@ static void help( char* progName)
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int main( int argc, char** argv )
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{
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help(argv[0]);
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const char* imagename = argc > 1 ? argv[1] : "lena.jpg";
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const char* imagename = argc > 1 ? argv[1] : "../data/lena.jpg";
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#ifdef DEMO_MIXED_API_USE
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Ptr<IplImage> IplI(cvLoadImage(imagename)); // Ptr<T> is a safe ref-counting pointer class
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|
@ -36,7 +36,7 @@ static void help()
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const char* keys =
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{
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"{c camera | | use camera or not}"
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"{fn file_name|baboon.jpg | image file }"
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"{fn file_name|../data/baboon.jpg | image file }"
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"{a accel |auto | accelerator type: auto (default), cpu, gpu}"
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};
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|
@ -14,7 +14,7 @@ static void help(char* progName)
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<< "This program shows how to filter images with mask: the write it yourself and the"
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<< "filter2d way. " << endl
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<< "Usage:" << endl
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<< progName << " [image_name -- default lena.jpg] [G -- grayscale] " << endl << endl;
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<< progName << " [image_name -- default ../data/lena.jpg] [G -- grayscale] " << endl << endl;
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}
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@ -23,7 +23,7 @@ void Sharpen(const Mat& myImage,Mat& Result);
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int main( int argc, char* argv[])
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{
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help(argv[0]);
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const char* filename = argc >=2 ? argv[1] : "lena.jpg";
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const char* filename = argc >=2 ? argv[1] : "../data/lena.jpg";
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Mat I, J, K;
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|
@ -12,11 +12,11 @@ const float nn_match_ratio = 0.8f; // Nearest neighbor matching ratio
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int main(void)
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{
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Mat img1 = imread("graf1.png", IMREAD_GRAYSCALE);
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Mat img2 = imread("graf3.png", IMREAD_GRAYSCALE);
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Mat img1 = imread("../data/graf1.png", IMREAD_GRAYSCALE);
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Mat img2 = imread("../data/graf3.png", IMREAD_GRAYSCALE);
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Mat homography;
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FileStorage fs("H1to3p.xml", FileStorage::READ);
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FileStorage fs("../data/H1to3p.xml", FileStorage::READ);
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fs.getFirstTopLevelNode() >> homography;
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vector<KeyPoint> kpts1, kpts2;
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@ -111,7 +111,7 @@ int main( int argc, const char** argv )
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else
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{
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if( inputName.empty() )
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inputName = "lena.jpg";
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inputName = "../data/lena.jpg";
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image = imread( inputName, 1 ).getUMat(ACCESS_READ);
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if( image.empty() )
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{
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@ -13,7 +13,7 @@ static void help()
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{
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cout << "\nThis program demonstrates the famous watershed segmentation algorithm in OpenCV: watershed()\n"
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"Usage:\n"
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"./watershed [image_name -- default is fruits.jpg]\n" << endl;
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"./watershed [image_name -- default is ../data/fruits.jpg]\n" << endl;
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cout << "Hot keys: \n"
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@ -48,7 +48,7 @@ static void onMouse( int event, int x, int y, int flags, void* )
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int main( int argc, char** argv )
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{
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char* filename = argc >= 2 ? argv[1] : (char*)"fruits.jpg";
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char* filename = argc >= 2 ? argv[1] : (char*)"../data/fruits.jpg";
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Mat img0 = imread(filename, 1), imgGray;
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if( img0.empty() )
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