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merge with Itseez/opencv

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This commit is contained in:
Ozan Tonkal
2013-09-15 16:32:56 +02:00
parent c31fb8ffff eff21788a8
commit 3165b526f2
2634 changed files with 198260 additions and 141747 deletions
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20
samples/cpp/tutorial_code/HighGUI/video-input-psnr-ssim/video-input-psnr-ssim.cpp
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@@ -60,10 +60,10 @@ int main(int argc, char *argv[])
return -1;
}
Size refS = Size((int) captRefrnc.get(CV_CAP_PROP_FRAME_WIDTH),
(int) captRefrnc.get(CV_CAP_PROP_FRAME_HEIGHT)),
uTSi = Size((int) captUndTst.get(CV_CAP_PROP_FRAME_WIDTH),
(int) captUndTst.get(CV_CAP_PROP_FRAME_HEIGHT));
Size refS = Size((int) captRefrnc.get(CAP_PROP_FRAME_WIDTH),
(int) captRefrnc.get(CAP_PROP_FRAME_HEIGHT)),
uTSi = Size((int) captUndTst.get(CAP_PROP_FRAME_WIDTH),
(int) captUndTst.get(CAP_PROP_FRAME_HEIGHT));
if (refS != uTSi)
{
@@ -75,13 +75,13 @@ int main(int argc, char *argv[])
const char* WIN_RF = "Reference";
// Windows
namedWindow(WIN_RF, CV_WINDOW_AUTOSIZE);
namedWindow(WIN_UT, CV_WINDOW_AUTOSIZE);
cvMoveWindow(WIN_RF, 400 , 0); //750, 2 (bernat =0)
cvMoveWindow(WIN_UT, refS.width, 0); //1500, 2
namedWindow(WIN_RF, WINDOW_AUTOSIZE);
namedWindow(WIN_UT, WINDOW_AUTOSIZE);
moveWindow(WIN_RF, 400 , 0); //750, 2 (bernat =0)
moveWindow(WIN_UT, refS.width, 0); //1500, 2
cout << "Reference frame resolution: Width=" << refS.width << " Height=" << refS.height
<< " of nr#: " << captRefrnc.get(CV_CAP_PROP_FRAME_COUNT) << endl;
<< " of nr#: " << captRefrnc.get(CAP_PROP_FRAME_COUNT) << endl;
cout << "PSNR trigger value " << setiosflags(ios::fixed) << setprecision(3)
<< psnrTriggerValue << endl;
@@ -125,7 +125,7 @@ int main(int argc, char *argv[])
imshow(WIN_RF, frameReference);
imshow(WIN_UT, frameUnderTest);
c = (char)cvWaitKey(delay);
c = (char)waitKey(delay);
if (c == 27) break;
}

12
samples/cpp/tutorial_code/HighGUI/video-write/video-write.cpp
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@@ -41,19 +41,19 @@ int main(int argc, char *argv[])
string::size_type pAt = source.find_last_of('.'); // Find extension point
const string NAME = source.substr(0, pAt) + argv[2][0] + ".avi"; // Form the new name with container
int ex = static_cast<int>(inputVideo.get(CV_CAP_PROP_FOURCC)); // Get Codec Type- Int form
int ex = static_cast<int>(inputVideo.get(CAP_PROP_FOURCC)); // Get Codec Type- Int form
// Transform from int to char via Bitwise operators
char EXT[] = {(char)(ex & 0XFF) , (char)((ex & 0XFF00) >> 8),(char)((ex & 0XFF0000) >> 16),(char)((ex & 0XFF000000) >> 24), 0};
Size S = Size((int) inputVideo.get(CV_CAP_PROP_FRAME_WIDTH), // Acquire input size
(int) inputVideo.get(CV_CAP_PROP_FRAME_HEIGHT));
Size S = Size((int) inputVideo.get(CAP_PROP_FRAME_WIDTH), // Acquire input size
(int) inputVideo.get(CAP_PROP_FRAME_HEIGHT));
VideoWriter outputVideo; // Open the output
if (askOutputType)
outputVideo.open(NAME, ex=-1, inputVideo.get(CV_CAP_PROP_FPS), S, true);
outputVideo.open(NAME, ex=-1, inputVideo.get(CAP_PROP_FPS), S, true);
else
outputVideo.open(NAME, ex, inputVideo.get(CV_CAP_PROP_FPS), S, true);
outputVideo.open(NAME, ex, inputVideo.get(CAP_PROP_FPS), S, true);
if (!outputVideo.isOpened())
{
@@ -62,7 +62,7 @@ int main(int argc, char *argv[])
}
cout << "Input frame resolution: Width=" << S.width << " Height=" << S.height
<< " of nr#: " << inputVideo.get(CV_CAP_PROP_FRAME_COUNT) << endl;
<< " of nr#: " << inputVideo.get(CAP_PROP_FRAME_COUNT) << endl;
cout << "Input codec type: " << EXT << endl;
int channel = 2; // Select the channel to save

6
samples/cpp/tutorial_code/Histograms_Matching/EqualizeHist_Demo.cpp
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@@ -31,14 +31,14 @@ int main( int, char** argv )
}
/// Convert to grayscale
cvtColor( src, src, CV_BGR2GRAY );
cvtColor( src, src, COLOR_BGR2GRAY );
/// Apply Histogram Equalization
equalizeHist( src, dst );
/// Display results
namedWindow( source_window, CV_WINDOW_AUTOSIZE );
namedWindow( equalized_window, CV_WINDOW_AUTOSIZE );
namedWindow( source_window, WINDOW_AUTOSIZE );
namedWindow( equalized_window, WINDOW_AUTOSIZE );
imshow( source_window, src );
imshow( equalized_window, dst );

6
samples/cpp/tutorial_code/Histograms_Matching/MatchTemplate_Demo.cpp
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@@ -33,8 +33,8 @@ int main( int, char** argv )
templ = imread( argv[2], 1 );
/// Create windows
namedWindow( image_window, CV_WINDOW_AUTOSIZE );
namedWindow( result_window, CV_WINDOW_AUTOSIZE );
namedWindow( image_window, WINDOW_AUTOSIZE );
namedWindow( result_window, WINDOW_AUTOSIZE );
/// Create Trackbar
const char* trackbar_label = "Method: \n 0: SQDIFF \n 1: SQDIFF NORMED \n 2: TM CCORR \n 3: TM CCORR NORMED \n 4: TM COEFF \n 5: TM COEFF NORMED";
@@ -74,7 +74,7 @@ void MatchingMethod( int, void* )
/// For SQDIFF and SQDIFF_NORMED, the best matches are lower values. For all the other methods, the higher the better
if( match_method == CV_TM_SQDIFF || match_method == CV_TM_SQDIFF_NORMED )
if( match_method == TM_SQDIFF || match_method == TM_SQDIFF_NORMED )
{ matchLoc = minLoc; }
else
{ matchLoc = maxLoc; }

4
samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo1.cpp
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@@ -28,7 +28,7 @@ int main( int, char** argv )
/// Read the image
src = imread( argv[1], 1 );
/// Transform it to HSV
cvtColor( src, hsv, CV_BGR2HSV );
cvtColor( src, hsv, COLOR_BGR2HSV );
/// Use only the Hue value
hue.create( hsv.size(), hsv.depth() );
@@ -37,7 +37,7 @@ int main( int, char** argv )
/// Create Trackbar to enter the number of bins
const char* window_image = "Source image";
namedWindow( window_image, CV_WINDOW_AUTOSIZE );
namedWindow( window_image, WINDOW_AUTOSIZE );
createTrackbar("* Hue bins: ", window_image, &bins, 180, Hist_and_Backproj );
Hist_and_Backproj(0, 0);

6
samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo2.cpp
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@@ -31,10 +31,10 @@ int main( int, char** argv )
/// Read the image
src = imread( argv[1], 1 );
/// Transform it to HSV
cvtColor( src, hsv, CV_BGR2HSV );
cvtColor( src, hsv, COLOR_BGR2HSV );
/// Show the image
namedWindow( window_image, CV_WINDOW_AUTOSIZE );
namedWindow( window_image, WINDOW_AUTOSIZE );
imshow( window_image, src );
/// Set Trackbars for floodfill thresholds
@@ -52,7 +52,7 @@ int main( int, char** argv )
*/
void pickPoint (int event, int x, int y, int, void* )
{
if( event != CV_EVENT_LBUTTONDOWN )
if( event != EVENT_LBUTTONDOWN )
{ return; }
// Fill and get the mask

2
samples/cpp/tutorial_code/Histograms_Matching/calcHist_Demo.cpp
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@@ -71,7 +71,7 @@ int main( int, char** argv )
}
/// Display
namedWindow("calcHist Demo", CV_WINDOW_AUTOSIZE );
namedWindow("calcHist Demo", WINDOW_AUTOSIZE );
imshow("calcHist Demo", histImage );
waitKey(0);

6
samples/cpp/tutorial_code/Histograms_Matching/compareHist_Demo.cpp
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@@ -33,9 +33,9 @@ int main( int argc, char** argv )
src_test2 = imread( argv[3], 1 );
/// Convert to HSV
cvtColor( src_base, hsv_base, CV_BGR2HSV );
cvtColor( src_test1, hsv_test1, CV_BGR2HSV );
cvtColor( src_test2, hsv_test2, CV_BGR2HSV );
cvtColor( src_base, hsv_base, COLOR_BGR2HSV );
cvtColor( src_test1, hsv_test1, COLOR_BGR2HSV );
cvtColor( src_test2, hsv_test2, COLOR_BGR2HSV );
hsv_half_down = hsv_base( Range( hsv_base.rows/2, hsv_base.rows - 1 ), Range( 0, hsv_base.cols - 1 ) );

6
samples/cpp/tutorial_code/ImgProc/Morphology_1.cpp
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@@ -37,9 +37,9 @@ int main( int, char** argv )
{ return -1; }
/// Create windows
namedWindow( "Erosion Demo", CV_WINDOW_AUTOSIZE );
namedWindow( "Dilation Demo", CV_WINDOW_AUTOSIZE );
cvMoveWindow( "Dilation Demo", src.cols, 0 );
namedWindow( "Erosion Demo", WINDOW_AUTOSIZE );
namedWindow( "Dilation Demo", WINDOW_AUTOSIZE );
moveWindow( "Dilation Demo", src.cols, 0 );
/// Create Erosion Trackbar
createTrackbar( "Element:\n 0: Rect \n 1: Cross \n 2: Ellipse", "Erosion Demo",

4
samples/cpp/tutorial_code/ImgProc/Morphology_2.cpp
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@@ -39,7 +39,7 @@ int main( int, char** argv )
{ return -1; }
/// Create window
namedWindow( window_name, CV_WINDOW_AUTOSIZE );
namedWindow( window_name, WINDOW_AUTOSIZE );
/// Create Trackbar to select Morphology operation
createTrackbar("Operator:\n 0: Opening - 1: Closing \n 2: Gradient - 3: Top Hat \n 4: Black Hat", window_name, &morph_operator, max_operator, Morphology_Operations );
@@ -76,5 +76,3 @@ void Morphology_Operations( int, void* )
morphologyEx( src, dst, operation, element );
imshow( window_name, dst );
}

9
samples/cpp/tutorial_code/ImgProc/Pyramids.cpp
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@@ -40,7 +40,7 @@ int main( void )
dst = tmp;
/// Create window
namedWindow( window_name, CV_WINDOW_AUTOSIZE );
namedWindow( window_name, WINDOW_AUTOSIZE );
imshow( window_name, dst );
/// Loop
@@ -66,10 +66,3 @@ int main( void )
return 0;
}

4
samples/cpp/tutorial_code/ImgProc/Smoothing.cpp
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@@ -31,7 +31,7 @@ int display_dst( int delay );
*/
int main( void )
{
namedWindow( window_name, CV_WINDOW_AUTOSIZE );
namedWindow( window_name, WINDOW_AUTOSIZE );
/// Load the source image
src = imread( "../images/lena.png", 1 );
@@ -89,7 +89,7 @@ int display_caption( const char* caption )
dst = Mat::zeros( src.size(), src.type() );
putText( dst, caption,
Point( src.cols/4, src.rows/2),
CV_FONT_HERSHEY_COMPLEX, 1, Scalar(255, 255, 255) );
FONT_HERSHEY_COMPLEX, 1, Scalar(255, 255, 255) );
imshow( window_name, dst );
int c = waitKey( DELAY_CAPTION );

4
samples/cpp/tutorial_code/ImgProc/Threshold.cpp
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@@ -37,10 +37,10 @@ int main( int, char** argv )
src = imread( argv[1], 1 );
/// Convert the image to Gray
cvtColor( src, src_gray, CV_RGB2GRAY );
cvtColor( src, src_gray, COLOR_RGB2GRAY );
/// Create a window to display results
namedWindow( window_name, CV_WINDOW_AUTOSIZE );
namedWindow( window_name, WINDOW_AUTOSIZE );
/// Create Trackbar to choose type of Threshold
createTrackbar( trackbar_type,

4
samples/cpp/tutorial_code/ImgTrans/CannyDetector_Demo.cpp
View File

@@ -58,10 +58,10 @@ int main( int, char** argv )
dst.create( src.size(), src.type() );
/// Convert the image to grayscale
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
/// Create a window
namedWindow( window_name, CV_WINDOW_AUTOSIZE );
namedWindow( window_name, WINDOW_AUTOSIZE );
/// Create a Trackbar for user to enter threshold
createTrackbar( "Min Threshold:", window_name, &lowThreshold, max_lowThreshold, CannyThreshold );

6
samples/cpp/tutorial_code/ImgTrans/Geometric_Transforms_Demo.cpp
View File

@@ -65,13 +65,13 @@ int main( int, char** argv )
/// Show what you got
namedWindow( source_window, CV_WINDOW_AUTOSIZE );
namedWindow( source_window, WINDOW_AUTOSIZE );
imshow( source_window, src );
namedWindow( warp_window, CV_WINDOW_AUTOSIZE );
namedWindow( warp_window, WINDOW_AUTOSIZE );
imshow( warp_window, warp_dst );
namedWindow( warp_rotate_window, CV_WINDOW_AUTOSIZE );
namedWindow( warp_rotate_window, WINDOW_AUTOSIZE );
imshow( warp_rotate_window, warp_rotate_dst );
/// Wait until user exits the program

6
samples/cpp/tutorial_code/ImgTrans/HoughCircle_Demo.cpp
View File

@@ -26,7 +26,7 @@ int main(int, char** argv)
{ return -1; }
/// Convert it to gray
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
/// Reduce the noise so we avoid false circle detection
GaussianBlur( src_gray, src_gray, Size(9, 9), 2, 2 );
@@ -34,7 +34,7 @@ int main(int, char** argv)
vector<Vec3f> circles;
/// Apply the Hough Transform to find the circles
HoughCircles( src_gray, circles, CV_HOUGH_GRADIENT, 1, src_gray.rows/8, 200, 100, 0, 0 );
HoughCircles( src_gray, circles, HOUGH_GRADIENT, 1, src_gray.rows/8, 200, 100, 0, 0 );
/// Draw the circles detected
for( size_t i = 0; i < circles.size(); i++ )
@@ -48,7 +48,7 @@ int main(int, char** argv)
}
/// Show your results
namedWindow( "Hough Circle Transform Demo", CV_WINDOW_AUTOSIZE );
namedWindow( "Hough Circle Transform Demo", WINDOW_AUTOSIZE );
imshow( "Hough Circle Transform Demo", src );
waitKey(0);

14
samples/cpp/tutorial_code/ImgTrans/HoughLines_Demo.cpp
View File

@@ -46,7 +46,7 @@ int main( int, char** argv )
}
/// Pass the image to gray
cvtColor( src, src_gray, CV_RGB2GRAY );
cvtColor( src, src_gray, COLOR_RGB2GRAY );
/// Apply Canny edge detector
Canny( src_gray, edges, 50, 200, 3 );
@@ -55,10 +55,10 @@ int main( int, char** argv )
char thresh_label[50];
sprintf( thresh_label, "Thres: %d + input", min_threshold );
namedWindow( standard_name, CV_WINDOW_AUTOSIZE );
namedWindow( standard_name, WINDOW_AUTOSIZE );
createTrackbar( thresh_label, standard_name, &s_trackbar, max_trackbar, Standard_Hough);
namedWindow( probabilistic_name, CV_WINDOW_AUTOSIZE );
namedWindow( probabilistic_name, WINDOW_AUTOSIZE );
createTrackbar( thresh_label, probabilistic_name, &p_trackbar, max_trackbar, Probabilistic_Hough);
/// Initialize
@@ -85,7 +85,7 @@ void help()
void Standard_Hough( int, void* )
{
vector<Vec2f> s_lines;
cvtColor( edges, standard_hough, CV_GRAY2BGR );
cvtColor( edges, standard_hough, COLOR_GRAY2BGR );
/// 1. Use Standard Hough Transform
HoughLines( edges, s_lines, 1, CV_PI/180, min_threshold + s_trackbar, 0, 0 );
@@ -100,7 +100,7 @@ void Standard_Hough( int, void* )
Point pt1( cvRound(x0 + alpha*(-sin_t)), cvRound(y0 + alpha*cos_t) );
Point pt2( cvRound(x0 - alpha*(-sin_t)), cvRound(y0 - alpha*cos_t) );
line( standard_hough, pt1, pt2, Scalar(255,0,0), 3, CV_AA);
line( standard_hough, pt1, pt2, Scalar(255,0,0), 3, LINE_AA);
}
imshow( standard_name, standard_hough );
@@ -112,7 +112,7 @@ void Standard_Hough( int, void* )
void Probabilistic_Hough( int, void* )
{
vector<Vec4i> p_lines;
cvtColor( edges, probabilistic_hough, CV_GRAY2BGR );
cvtColor( edges, probabilistic_hough, COLOR_GRAY2BGR );
/// 2. Use Probabilistic Hough Transform
HoughLinesP( edges, p_lines, 1, CV_PI/180, min_threshold + p_trackbar, 30, 10 );
@@ -121,7 +121,7 @@ void Probabilistic_Hough( int, void* )
for( size_t i = 0; i < p_lines.size(); i++ )
{
Vec4i l = p_lines[i];
line( probabilistic_hough, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(255,0,0), 3, CV_AA);
line( probabilistic_hough, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(255,0,0), 3, LINE_AA);
}
imshow( probabilistic_name, probabilistic_hough );

4
samples/cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp
View File

@@ -34,10 +34,10 @@ int main( int, char** argv )
GaussianBlur( src, src, Size(3,3), 0, 0, BORDER_DEFAULT );
/// Convert the image to grayscale
cvtColor( src, src_gray, CV_RGB2GRAY );
cvtColor( src, src_gray, COLOR_RGB2GRAY );
/// Create window
namedWindow( window_name, CV_WINDOW_AUTOSIZE );
namedWindow( window_name, WINDOW_AUTOSIZE );
/// Apply Laplace function
Mat abs_dst;

4
samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp
View File

@@ -34,7 +34,7 @@ int main( int, char** argv )
map_y.create( src.size(), CV_32FC1 );
/// Create window
namedWindow( remap_window, CV_WINDOW_AUTOSIZE );
namedWindow( remap_window, WINDOW_AUTOSIZE );
/// Loop
for(;;)
@@ -47,7 +47,7 @@ int main( int, char** argv )
/// Update map_x & map_y. Then apply remap
update_map();
remap( src, dst, map_x, map_y, CV_INTER_LINEAR, BORDER_CONSTANT, Scalar(0, 0, 0) );
remap( src, dst, map_x, map_y, INTER_LINEAR, BORDER_CONSTANT, Scalar(0, 0, 0) );
// Display results
imshow( remap_window, dst );

6
samples/cpp/tutorial_code/ImgTrans/Sobel_Demo.cpp
View File

@@ -33,10 +33,10 @@ int main( int, char** argv )
GaussianBlur( src, src, Size(3,3), 0, 0, BORDER_DEFAULT );
/// Convert it to gray
cvtColor( src, src_gray, CV_RGB2GRAY );
cvtColor( src, src_gray, COLOR_RGB2GRAY );
/// Create window
namedWindow( window_name, CV_WINDOW_AUTOSIZE );
namedWindow( window_name, WINDOW_AUTOSIZE );
/// Generate grad_x and grad_y
Mat grad_x, grad_y;
@@ -61,5 +61,3 @@ int main( int, char** argv )
return 0;
}

7
samples/cpp/tutorial_code/ImgTrans/copyMakeBorder_demo.cpp
View File

@@ -15,7 +15,6 @@ using namespace cv;
Mat src, dst;
int top, bottom, left, right;
int borderType;
Scalar value;
const char* window_name = "copyMakeBorder Demo";
RNG rng(12345);
@@ -44,7 +43,7 @@ int main( int, char** argv )
printf( " ** Press 'ESC' to exit the program \n");
/// Create window
namedWindow( window_name, CV_WINDOW_AUTOSIZE );
namedWindow( window_name, WINDOW_AUTOSIZE );
/// Initialize arguments for the filter
top = (int) (0.05*src.rows); bottom = (int) (0.05*src.rows);
@@ -64,7 +63,7 @@ int main( int, char** argv )
else if( (char)c == 'r' )
{ borderType = BORDER_REPLICATE; }
value = Scalar( rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255) );
Scalar value( rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255) );
copyMakeBorder( src, dst, top, bottom, left, right, borderType, value );
imshow( window_name, dst );
@@ -72,5 +71,3 @@ int main( int, char** argv )
return 0;
}

2
samples/cpp/tutorial_code/ImgTrans/filter2D_demo.cpp
View File

@@ -35,7 +35,7 @@ int main ( int, char** argv )
{ return -1; }
/// Create window
namedWindow( window_name, CV_WINDOW_AUTOSIZE );
namedWindow( window_name, WINDOW_AUTOSIZE );
/// Initialize arguments for the filter
anchor = Point( -1, -1 );

8
samples/cpp/tutorial_code/ShapeDescriptors/findContours_demo.cpp
View File

@@ -30,12 +30,12 @@ int main( int, char** argv )
src = imread( argv[1], 1 );
/// Convert image to gray and blur it
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
blur( src_gray, src_gray, Size(3,3) );
/// Create Window
const char* source_window = "Source";
namedWindow( source_window, CV_WINDOW_AUTOSIZE );
namedWindow( source_window, WINDOW_AUTOSIZE );
imshow( source_window, src );
createTrackbar( " Canny thresh:", "Source", &thresh, max_thresh, thresh_callback );
@@ -57,7 +57,7 @@ void thresh_callback(int, void* )
/// Detect edges using canny
Canny( src_gray, canny_output, thresh, thresh*2, 3 );
/// Find contours
findContours( canny_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) );
findContours( canny_output, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0) );
/// Draw contours
Mat drawing = Mat::zeros( canny_output.size(), CV_8UC3 );
@@ -68,6 +68,6 @@ void thresh_callback(int, void* )
}
/// Show in a window
namedWindow( "Contours", CV_WINDOW_AUTOSIZE );
namedWindow( "Contours", WINDOW_AUTOSIZE );
imshow( "Contours", drawing );
}

8
samples/cpp/tutorial_code/ShapeDescriptors/generalContours_demo1.cpp
View File

@@ -30,12 +30,12 @@ int main( int, char** argv )
src = imread( argv[1], 1 );
/// Convert image to gray and blur it
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
blur( src_gray, src_gray, Size(3,3) );
/// Create Window
const char* source_window = "Source";
namedWindow( source_window, CV_WINDOW_AUTOSIZE );
namedWindow( source_window, WINDOW_AUTOSIZE );
imshow( source_window, src );
createTrackbar( " Threshold:", "Source", &thresh, max_thresh, thresh_callback );
@@ -57,7 +57,7 @@ void thresh_callback(int, void* )
/// Detect edges using Threshold
threshold( src_gray, threshold_output, thresh, 255, THRESH_BINARY );
/// Find contours
findContours( threshold_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) );
findContours( threshold_output, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0) );
/// Approximate contours to polygons + get bounding rects and circles
vector<vector<Point> > contours_poly( contours.size() );
@@ -83,6 +83,6 @@ void thresh_callback(int, void* )
}
/// Show in a window
namedWindow( "Contours", CV_WINDOW_AUTOSIZE );
namedWindow( "Contours", WINDOW_AUTOSIZE );
imshow( "Contours", drawing );
}

8
samples/cpp/tutorial_code/ShapeDescriptors/generalContours_demo2.cpp
View File

@@ -30,12 +30,12 @@ int main( int, char** argv )
src = imread( argv[1], 1 );
/// Convert image to gray and blur it
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
blur( src_gray, src_gray, Size(3,3) );
/// Create Window
const char* source_window = "Source";
namedWindow( source_window, CV_WINDOW_AUTOSIZE );
namedWindow( source_window, WINDOW_AUTOSIZE );
imshow( source_window, src );
createTrackbar( " Threshold:", "Source", &thresh, max_thresh, thresh_callback );
@@ -57,7 +57,7 @@ void thresh_callback(int, void* )
/// Detect edges using Threshold
threshold( src_gray, threshold_output, thresh, 255, THRESH_BINARY );
/// Find contours
findContours( threshold_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) );
findContours( threshold_output, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0) );
/// Find the rotated rectangles and ellipses for each contour
vector<RotatedRect> minRect( contours.size() );
@@ -85,6 +85,6 @@ void thresh_callback(int, void* )
}
/// Show in a window
namedWindow( "Contours", CV_WINDOW_AUTOSIZE );
namedWindow( "Contours", WINDOW_AUTOSIZE );
imshow( "Contours", drawing );
}

8
samples/cpp/tutorial_code/ShapeDescriptors/hull_demo.cpp
View File

@@ -30,12 +30,12 @@ int main( int, char** argv )
src = imread( argv[1], 1 );
/// Convert image to gray and blur it
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
blur( src_gray, src_gray, Size(3,3) );
/// Create Window
const char* source_window = "Source";
namedWindow( source_window, CV_WINDOW_AUTOSIZE );
namedWindow( source_window, WINDOW_AUTOSIZE );
imshow( source_window, src );
createTrackbar( " Threshold:", "Source", &thresh, max_thresh, thresh_callback );
@@ -59,7 +59,7 @@ void thresh_callback(int, void* )
threshold( src_gray, threshold_output, thresh, 255, THRESH_BINARY );
/// Find contours
findContours( threshold_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) );
findContours( threshold_output, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0) );
/// Find the convex hull object for each contour
vector<vector<Point> >hull( contours.size() );
@@ -76,6 +76,6 @@ void thresh_callback(int, void* )
}
/// Show in a window
namedWindow( "Hull demo", CV_WINDOW_AUTOSIZE );
namedWindow( "Hull demo", WINDOW_AUTOSIZE );
imshow( "Hull demo", drawing );
}

9
samples/cpp/tutorial_code/ShapeDescriptors/moments_demo.cpp
View File

@@ -30,12 +30,12 @@ int main( int, char** argv )
src = imread( argv[1], 1 );
/// Convert image to gray and blur it
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
blur( src_gray, src_gray, Size(3,3) );
/// Create Window
const char* source_window = "Source";
namedWindow( source_window, CV_WINDOW_AUTOSIZE );
namedWindow( source_window, WINDOW_AUTOSIZE );
imshow( source_window, src );
createTrackbar( " Canny thresh:", "Source", &thresh, max_thresh, thresh_callback );
@@ -57,7 +57,7 @@ void thresh_callback(int, void* )
/// Detect edges using canny
Canny( src_gray, canny_output, thresh, thresh*2, 3 );
/// Find contours
findContours( canny_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) );
findContours( canny_output, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0) );
/// Get the moments
vector<Moments> mu(contours.size() );
@@ -79,7 +79,7 @@ void thresh_callback(int, void* )
}
/// Show in a window
namedWindow( "Contours", CV_WINDOW_AUTOSIZE );
namedWindow( "Contours", WINDOW_AUTOSIZE );
imshow( "Contours", drawing );
/// Calculate the area with the moments 00 and compare with the result of the OpenCV function
@@ -92,4 +92,3 @@ void thresh_callback(int, void* )
circle( drawing, mc[i], 4, color, -1, 8, 0 );
}
}

6
samples/cpp/tutorial_code/ShapeDescriptors/pointPolygonTest_demo.cpp
View File

@@ -71,13 +71,11 @@ int main( void )
/// Create Window and show your results
const char* source_window = "Source";
namedWindow( source_window, CV_WINDOW_AUTOSIZE );
namedWindow( source_window, WINDOW_AUTOSIZE );
imshow( source_window, src );
namedWindow( "Distance", CV_WINDOW_AUTOSIZE );
namedWindow( "Distance", WINDOW_AUTOSIZE );
imshow( "Distance", drawing );
waitKey(0);
return(0);
}

7
samples/cpp/tutorial_code/TrackingMotion/cornerDetector_Demo.cpp
View File

@@ -40,7 +40,7 @@ int main( int, char** argv )
{
/// Load source image and convert it to gray
src = imread( argv[1], 1 );
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
/// Set some parameters
int blockSize = 3; int apertureSize = 3;
@@ -64,7 +64,7 @@ int main( int, char** argv )
minMaxLoc( Mc, &myHarris_minVal, &myHarris_maxVal, 0, 0, Mat() );
/* Create Window and Trackbar */
namedWindow( myHarris_window, CV_WINDOW_AUTOSIZE );
namedWindow( myHarris_window, WINDOW_AUTOSIZE );
createTrackbar( " Quality Level:", myHarris_window, &myHarris_qualityLevel, max_qualityLevel, myHarris_function );
myHarris_function( 0, 0 );
@@ -75,7 +75,7 @@ int main( int, char** argv )
minMaxLoc( myShiTomasi_dst, &myShiTomasi_minVal, &myShiTomasi_maxVal, 0, 0, Mat() );
/* Create Window and Trackbar */
namedWindow( myShiTomasi_window, CV_WINDOW_AUTOSIZE );
namedWindow( myShiTomasi_window, WINDOW_AUTOSIZE );
createTrackbar( " Quality Level:", myShiTomasi_window, &myShiTomasi_qualityLevel, max_qualityLevel, myShiTomasi_function );
myShiTomasi_function( 0, 0 );
@@ -120,4 +120,3 @@ void myHarris_function( int, void* )
}
imshow( myHarris_window, myHarris_copy );
}

6
samples/cpp/tutorial_code/TrackingMotion/cornerHarris_Demo.cpp
View File

@@ -31,10 +31,10 @@ int main( int, char** argv )
{
/// Load source image and convert it to gray
src = imread( argv[1], 1 );
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
/// Create a window and a trackbar
namedWindow( source_window, CV_WINDOW_AUTOSIZE );
namedWindow( source_window, WINDOW_AUTOSIZE );
createTrackbar( "Threshold: ", source_window, &thresh, max_thresh, cornerHarris_demo );
imshow( source_window, src );
@@ -77,6 +77,6 @@ void cornerHarris_demo( int, void* )
}
}
/// Showing the result
namedWindow( corners_window, CV_WINDOW_AUTOSIZE );
namedWindow( corners_window, WINDOW_AUTOSIZE );
imshow( corners_window, dst_norm_scaled );
}

9
samples/cpp/tutorial_code/TrackingMotion/cornerSubPix_Demo.cpp
View File

@@ -32,10 +32,10 @@ int main( int, char** argv )
{
/// Load source image and convert it to gray
src = imread( argv[1], 1 );
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
/// Create Window
namedWindow( source_window, CV_WINDOW_AUTOSIZE );
namedWindow( source_window, WINDOW_AUTOSIZE );
/// Create Trackbar to set the number of corners
createTrackbar( "Max corners:", source_window, &maxCorners, maxTrackbar, goodFeaturesToTrack_Demo );
@@ -87,13 +87,13 @@ void goodFeaturesToTrack_Demo( int, void* )
{ circle( copy, corners[i], r, Scalar(rng.uniform(0,255), rng.uniform(0,255), rng.uniform(0,255)), -1, 8, 0 ); }
/// Show what you got
namedWindow( source_window, CV_WINDOW_AUTOSIZE );
namedWindow( source_window, WINDOW_AUTOSIZE );
imshow( source_window, copy );
/// Set the neeed parameters to find the refined corners
Size winSize = Size( 5, 5 );
Size zeroZone = Size( -1, -1 );
TermCriteria criteria = TermCriteria( CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 40, 0.001 );
TermCriteria criteria = TermCriteria( TermCriteria::EPS + TermCriteria::COUNT, 40, 0.001 );
/// Calculate the refined corner locations
cornerSubPix( src_gray, corners, winSize, zeroZone, criteria );
@@ -102,4 +102,3 @@ void goodFeaturesToTrack_Demo( int, void* )
for( size_t i = 0; i < corners.size(); i++ )
{ cout<<" -- Refined Corner ["<<i<<"] ("<<corners[i].x<<","<<corners[i].y<<")"<<endl; }
}

7
samples/cpp/tutorial_code/TrackingMotion/goodFeaturesToTrack_Demo.cpp
View File

@@ -32,10 +32,10 @@ int main( int, char** argv )
{
/// Load source image and convert it to gray
src = imread( argv[1], 1 );
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
/// Create Window
namedWindow( source_window, CV_WINDOW_AUTOSIZE );
namedWindow( source_window, WINDOW_AUTOSIZE );
/// Create Trackbar to set the number of corners
createTrackbar( "Max corners:", source_window, &maxCorners, maxTrackbar, goodFeaturesToTrack_Demo );
@@ -87,7 +87,6 @@ void goodFeaturesToTrack_Demo( int, void* )
{ circle( copy, corners[i], r, Scalar(rng.uniform(0,255), rng.uniform(0,255), rng.uniform(0,255)), -1, 8, 0 ); }
/// Show what you got
namedWindow( source_window, CV_WINDOW_AUTOSIZE );
namedWindow( source_window, WINDOW_AUTOSIZE );
imshow( source_window, copy );
}

15
samples/cpp/tutorial_code/contrib/retina_tutorial.cpp → samples/cpp/tutorial_code/bioinspired/retina_tutorial.cpp
View File

@@ -9,7 +9,8 @@
#include <iostream>
#include <cstring>
#include "opencv2/opencv.hpp"
#include "opencv2/bioinspired.hpp"
#include "opencv2/highgui.hpp"
static void help(std::string errorMessage)
{
@@ -38,7 +39,7 @@ int main(int argc, char* argv[]) {
// welcome message
std::cout<<"****************************************************"<<std::endl;
std::cout<<"* Retina demonstration : demonstrates the use of is a wrapper class of the Gipsa/Listic Labs retina model."<<std::endl;
std::cout<<"* This demo will try to load the file 'RetinaSpecificParameters.xml' (if exists).\nTo create it, copy the autogenerated template 'RetinaDefaultParameters.xml'.\nThen twaek it with your own retina parameters."<<std::endl;
std::cout<<"* This demo will try to load the file 'RetinaSpecificParameters.xml' (if exists).\nTo create it, copy the autogenerated template 'RetinaDefaultParameters.xml'.\nThen tweak it with your own retina parameters."<<std::endl;
// basic input arguments checking
if (argc<2)
{
@@ -94,15 +95,17 @@ int main(int argc, char* argv[]) {
try
{
// create a retina instance with default parameters setup, uncomment the initialisation you wanna test
cv::Ptr<cv::Retina> myRetina;
cv::Ptr<cv::bioinspired::Retina> myRetina;
// if the last parameter is 'log', then activate log sampling (favour foveal vision and subsamples peripheral vision)
if (useLogSampling)
{
myRetina = new cv::Retina(inputFrame.size(), true, cv::RETINA_COLOR_BAYER, true, 2.0, 10.0);
myRetina = cv::bioinspired::createRetina(inputFrame.size(), true, cv::bioinspired::RETINA_COLOR_BAYER, true, 2.0, 10.0);
}
else// -> else allocate "classical" retina :
myRetina = new cv::Retina(inputFrame.size());
{
myRetina = cv::bioinspired::createRetina(inputFrame.size());
}
// save default retina parameters file in order to let you see this and maybe modify it and reload using method "setup"
myRetina->write("RetinaDefaultParameters.xml");
@@ -136,7 +139,7 @@ int main(int argc, char* argv[]) {
}
}catch(cv::Exception e)
{
std::cerr<<"Error using Retina : "<<e.what()<<std::endl;
std::cerr<<"Error using Retina or end of video sequence reached : "<<e.what()<<std::endl;
}
// Program end message

45
samples/cpp/tutorial_code/calib3d/camera_calibration/camera_calibration.cpp
View File

@@ -3,10 +3,11 @@
#include <time.h>
#include <stdio.h>
#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/calib3d/calib3d.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/core.hpp>
#include <opencv2/core/utility.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/calib3d.hpp>
#include <opencv2/highgui.hpp>
using namespace cv;
using namespace std;
@@ -23,7 +24,7 @@ class Settings
public:
Settings() : goodInput(false) {}
enum Pattern { NOT_EXISTING, CHESSBOARD, CIRCLES_GRID, ASYMMETRIC_CIRCLES_GRID };
enum InputType {INVALID, CAMERA, VIDEO_FILE, IMAGE_LIST};
enum InputType { INVALID, CAMERA, VIDEO_FILE, IMAGE_LIST };
void write(FileStorage& fs) const //Write serialization for this class
{
@@ -119,9 +120,9 @@ public:
}
flag = 0;
if(calibFixPrincipalPoint) flag |= CV_CALIB_FIX_PRINCIPAL_POINT;
if(calibZeroTangentDist) flag |= CV_CALIB_ZERO_TANGENT_DIST;
if(aspectRatio) flag |= CV_CALIB_FIX_ASPECT_RATIO;
if(calibFixPrincipalPoint) flag |= CALIB_FIX_PRINCIPAL_POINT;
if(calibZeroTangentDist) flag |= CALIB_ZERO_TANGENT_DIST;
if(aspectRatio) flag |= CALIB_FIX_ASPECT_RATIO;
calibrationPattern = NOT_EXISTING;
@@ -146,7 +147,7 @@ public:
view0.copyTo(result);
}
else if( atImageList < (int)imageList.size() )
result = imread(imageList[atImageList++], CV_LOAD_IMAGE_COLOR);
result = imread(imageList[atImageList++], IMREAD_COLOR);
return result;
}
@@ -271,7 +272,7 @@ int main(int argc, char* argv[])
{
case Settings::CHESSBOARD:
found = findChessboardCorners( view, s.boardSize, pointBuf,
CV_CALIB_CB_ADAPTIVE_THRESH | CV_CALIB_CB_FAST_CHECK | CV_CALIB_CB_NORMALIZE_IMAGE);
CALIB_CB_ADAPTIVE_THRESH | CALIB_CB_FAST_CHECK | CALIB_CB_NORMALIZE_IMAGE);
break;
case Settings::CIRCLES_GRID:
found = findCirclesGrid( view, s.boardSize, pointBuf );
@@ -290,9 +291,9 @@ int main(int argc, char* argv[])
if( s.calibrationPattern == Settings::CHESSBOARD)
{
Mat viewGray;
cvtColor(view, viewGray, CV_BGR2GRAY);
cvtColor(view, viewGray, COLOR_BGR2GRAY);
cornerSubPix( viewGray, pointBuf, Size(11,11),
Size(-1,-1), TermCriteria( CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 30, 0.1 ));
Size(-1,-1), TermCriteria( TermCriteria::EPS+TermCriteria::COUNT, 30, 0.1 ));
}
if( mode == CAPTURING && // For camera only take new samples after delay time
@@ -391,7 +392,7 @@ static double computeReprojectionErrors( const vector<vector<Point3f> >& objectP
{
projectPoints( Mat(objectPoints[i]), rvecs[i], tvecs[i], cameraMatrix,
distCoeffs, imagePoints2);
err = norm(Mat(imagePoints[i]), Mat(imagePoints2), CV_L2);
err = norm(Mat(imagePoints[i]), Mat(imagePoints2), NORM_L2);
int n = (int)objectPoints[i].size();
perViewErrors[i] = (float) std::sqrt(err*err/n);
@@ -432,7 +433,7 @@ static bool runCalibration( Settings& s, Size& imageSize, Mat& cameraMatrix, Mat
{
cameraMatrix = Mat::eye(3, 3, CV_64F);
if( s.flag & CV_CALIB_FIX_ASPECT_RATIO )
if( s.flag & CALIB_FIX_ASPECT_RATIO )
cameraMatrix.at<double>(0,0) = 1.0;
distCoeffs = Mat::zeros(8, 1, CV_64F);
@@ -444,7 +445,7 @@ static bool runCalibration( Settings& s, Size& imageSize, Mat& cameraMatrix, Mat
//Find intrinsic and extrinsic camera parameters
double rms = calibrateCamera(objectPoints, imagePoints, imageSize, cameraMatrix,
distCoeffs, rvecs, tvecs, s.flag|CV_CALIB_FIX_K4|CV_CALIB_FIX_K5);
distCoeffs, rvecs, tvecs, s.flag|CALIB_FIX_K4|CALIB_FIX_K5);
cout << "Re-projection error reported by calibrateCamera: "<< rms << endl;
@@ -480,17 +481,17 @@ static void saveCameraParams( Settings& s, Size& imageSize, Mat& cameraMatrix, M
fs << "board_Height" << s.boardSize.height;
fs << "square_Size" << s.squareSize;
if( s.flag & CV_CALIB_FIX_ASPECT_RATIO )
if( s.flag & CALIB_FIX_ASPECT_RATIO )
fs << "FixAspectRatio" << s.aspectRatio;
if( s.flag )
{
sprintf( buf, "flags: %s%s%s%s",
s.flag & CV_CALIB_USE_INTRINSIC_GUESS ? " +use_intrinsic_guess" : "",
s.flag & CV_CALIB_FIX_ASPECT_RATIO ? " +fix_aspectRatio" : "",
s.flag & CV_CALIB_FIX_PRINCIPAL_POINT ? " +fix_principal_point" : "",
s.flag & CV_CALIB_ZERO_TANGENT_DIST ? " +zero_tangent_dist" : "" );
cvWriteComment( *fs, buf, 0 );
s.flag & CALIB_USE_INTRINSIC_GUESS ? " +use_intrinsic_guess" : "",
s.flag & CALIB_FIX_ASPECT_RATIO ? " +fix_aspectRatio" : "",
s.flag & CALIB_FIX_PRINCIPAL_POINT ? " +fix_principal_point" : "",
s.flag & CALIB_ZERO_TANGENT_DIST ? " +zero_tangent_dist" : "" );
//cvWriteComment( *fs, buf, 0 );
}
@@ -518,7 +519,7 @@ static void saveCameraParams( Settings& s, Size& imageSize, Mat& cameraMatrix, M
r = rvecs[i].t();
t = tvecs[i].t();
}
cvWriteComment( *fs, "a set of 6-tuples (rotation vector + translation vector) for each view", 0 );
//cvWriteComment( *fs, "a set of 6-tuples (rotation vector + translation vector) for each view", 0 );
fs << "Extrinsic_Parameters" << bigmat;
}

12
samples/cpp/tutorial_code/calib3d/stereoBM/SBM_Sample.cpp
View File

@@ -26,8 +26,8 @@ int main( int argc, char** argv )
{ readme(); return -1; }
//-- 1. Read the images
Mat imgLeft = imread( argv[1], CV_LOAD_IMAGE_GRAYSCALE );
Mat imgRight = imread( argv[2], CV_LOAD_IMAGE_GRAYSCALE );
Mat imgLeft = imread( argv[1], IMREAD_GRAYSCALE );
Mat imgRight = imread( argv[2], IMREAD_GRAYSCALE );
//-- And create the image in which we will save our disparities
Mat imgDisparity16S = Mat( imgLeft.rows, imgLeft.cols, CV_16S );
Mat imgDisparity8U = Mat( imgLeft.rows, imgLeft.cols, CV_8UC1 );
@@ -39,12 +39,10 @@ int main( int argc, char** argv )
int ndisparities = 16*5; /**< Range of disparity */
int SADWindowSize = 21; /**< Size of the block window. Must be odd */
StereoBM sbm( StereoBM::BASIC_PRESET,
ndisparities,
SADWindowSize );
Ptr<StereoBM> sbm = createStereoBM( ndisparities, SADWindowSize );
//-- 3. Calculate the disparity image
sbm( imgLeft, imgRight, imgDisparity16S, CV_16S );
sbm->compute( imgLeft, imgRight, imgDisparity16S );
//-- Check its extreme values
double minVal; double maxVal;
@@ -56,7 +54,7 @@ int main( int argc, char** argv )
//-- 4. Display it as a CV_8UC1 image
imgDisparity16S.convertTo( imgDisparity8U, CV_8UC1, 255/(maxVal - minVal));
namedWindow( windowDisparity, CV_WINDOW_NORMAL );
namedWindow( windowDisparity, WINDOW_NORMAL );
imshow( windowDisparity, imgDisparity8U );
//-- 5. Save the image

6
samples/cpp/tutorial_code/core/Matrix/Drawing_1.cpp
View File

@@ -64,9 +64,9 @@ int main( void ){
/// 3. Display your stuff!
imshow( atom_window, atom_image );
cvMoveWindow( atom_window, 0, 200 );
moveWindow( atom_window, 0, 200 );
imshow( rook_window, rook_image );
cvMoveWindow( rook_window, w, 200 );
moveWindow( rook_window, w, 200 );
waitKey( 0 );
return(0);
@@ -168,5 +168,3 @@ void MyLine( Mat img, Point start, Point end )
thickness,
lineType );
}

4
samples/cpp/tutorial_code/core/Matrix/Drawing_2.cpp
View File

@@ -304,7 +304,7 @@ int Displaying_Random_Text( Mat image, char* window_name, RNG rng )
*/
int Displaying_Big_End( Mat image, char* window_name, RNG )
{
Size textsize = getTextSize("OpenCV forever!", CV_FONT_HERSHEY_COMPLEX, 3, 5, 0);
Size textsize = getTextSize("OpenCV forever!", FONT_HERSHEY_COMPLEX, 3, 5, 0);
Point org((window_width - textsize.width)/2, (window_height - textsize.height)/2);
int lineType = 8;
@@ -313,7 +313,7 @@ int Displaying_Big_End( Mat image, char* window_name, RNG )
for( int i = 0; i < 255; i += 2 )
{
image2 = image - Scalar::all(i);
putText( image2, "OpenCV forever!", org, CV_FONT_HERSHEY_COMPLEX, 3,
putText( image2, "OpenCV forever!", org, FONT_HERSHEY_COMPLEX, 3,
Scalar(i, i, 255), 5, lineType );
imshow( window_name, image2 );

6
samples/cpp/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.cpp
View File

@@ -22,7 +22,7 @@ int main(int argc, char ** argv)
const char* filename = argc >=2 ? argv[1] : "lena.jpg";
Mat I = imread(filename, CV_LOAD_IMAGE_GRAYSCALE);
Mat I = imread(filename, IMREAD_GRAYSCALE);
if( I.empty())
return -1;
@@ -67,7 +67,7 @@ int main(int argc, char ** argv)
q2.copyTo(q1);
tmp.copyTo(q2);
normalize(magI, magI, 0, 1, CV_MINMAX); // Transform the matrix with float values into a
normalize(magI, magI, 0, 1, NORM_MINMAX); // Transform the matrix with float values into a
// viewable image form (float between values 0 and 1).
imshow("Input Image" , I ); // Show the result
@@ -75,4 +75,4 @@ int main(int argc, char ** argv)
waitKey();
return 0;
}
}

2
samples/cpp/tutorial_code/core/file_input_output/file_input_output.cpp
View File

@@ -151,4 +151,4 @@ int main(int ac, char** av)
<< "Tip: Open up " << filename << " with a text editor to see the serialized data." << endl;
return 0;
}
}

11
samples/cpp/tutorial_code/core/how_to_scan_images/how_to_scan_images.cpp
View File

@@ -1,5 +1,6 @@
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/core.hpp>
#include <opencv2/core/utility.hpp>
#include <opencv2/highgui.hpp>
#include <iostream>
#include <sstream>
@@ -35,9 +36,9 @@ int main( int argc, char* argv[])
Mat I, J;
if( argc == 4 && !strcmp(argv[3],"G") )
I = imread(argv[1], CV_LOAD_IMAGE_GRAYSCALE);
I = imread(argv[1], IMREAD_GRAYSCALE);
else
I = imread(argv[1], CV_LOAD_IMAGE_COLOR);
I = imread(argv[1], IMREAD_COLOR);
if (!I.data)
{
@@ -213,4 +214,4 @@ Mat& ScanImageAndReduceRandomAccess(Mat& I, const uchar* const table)
}
return I;
}
}

17
samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp
View File

@@ -4,6 +4,7 @@
#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/core/utility.hpp>
using namespace cv; // The new C++ interface API is inside this namespace. Import it.
using namespace std;
@@ -21,19 +22,23 @@ static void help( char* progName)
// comment out the define to use only the latest C++ API
#define DEMO_MIXED_API_USE
#ifdef DEMO_MIXED_API_USE
# include <opencv2/highgui/highgui_c.h>
#endif
int main( int argc, char** argv )
{
help(argv[0]);
const char* imagename = argc > 1 ? argv[1] : "lena.jpg";
#ifdef DEMO_MIXED_API_USE
Ptr<IplImage> IplI = cvLoadImage(imagename); // Ptr<T> is safe ref-counting pointer class
if(IplI.empty())
Ptr<IplImage> IplI(cvLoadImage(imagename)); // Ptr<T> is a safe ref-counting pointer class
if(!IplI)
{
cerr << "Can not load image " << imagename << endl;
return -1;
}
Mat I(IplI); // Convert to the new style container. Only header created. Image not copied.
Mat I = cv::cvarrToMat(IplI); // Convert to the new style container. Only header created. Image not copied.
#else
Mat I = imread(imagename); // the newer cvLoadImage alternative, MATLAB-style function
if( I.empty() ) // same as if( !I.data )
@@ -45,7 +50,7 @@ int main( int argc, char** argv )
// convert image to YUV color space. The output image will be created automatically.
Mat I_YUV;
cvtColor(I, I_YUV, CV_BGR2YCrCb);
cvtColor(I, I_YUV, COLOR_BGR2YCrCb);
vector<Mat> planes; // Use the STL's vector structure to store multiple Mat objects
split(I_YUV, planes); // split the image into separate color planes (Y U V)
@@ -114,10 +119,10 @@ int main( int argc, char** argv )
merge(planes, I_YUV); // now merge the results back
cvtColor(I_YUV, I, CV_YCrCb2BGR); // and produce the output RGB image
cvtColor(I_YUV, I, COLOR_YCrCb2BGR); // and produce the output RGB image
namedWindow("image with grain", CV_WINDOW_AUTOSIZE); // use this to create images
namedWindow("image with grain", WINDOW_AUTOSIZE); // use this to create images
#ifdef DEMO_MIXED_API_USE
// this is to demonstrate that I and IplI really share the data - the result of the above

21
samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp
View File

@@ -1,6 +1,7 @@
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/core.hpp>
#include <opencv2/core/utility.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include <iostream>
using namespace std;
@@ -26,12 +27,12 @@ int main( int argc, char* argv[])
Mat I, J, K;
if (argc >= 3 && !strcmp("G", argv[2]))
I = imread( filename, CV_LOAD_IMAGE_GRAYSCALE);
I = imread( filename, IMREAD_GRAYSCALE);
else
I = imread( filename, CV_LOAD_IMAGE_COLOR);
I = imread( filename, IMREAD_COLOR);
namedWindow("Input", CV_WINDOW_AUTOSIZE);
namedWindow("Output", CV_WINDOW_AUTOSIZE);
namedWindow("Input", WINDOW_AUTOSIZE);
namedWindow("Output", WINDOW_AUTOSIZE);
imshow("Input", I);
double t = (double)getTickCount();
@@ -42,7 +43,7 @@ int main( int argc, char* argv[])
cout << "Hand written function times passed in seconds: " << t << endl;
imshow("Output", J);
cvWaitKey(0);
waitKey();
Mat kern = (Mat_<char>(3,3) << 0, -1, 0,
-1, 5, -1,
@@ -54,7 +55,7 @@ int main( int argc, char* argv[])
imshow("Output", K);
cvWaitKey(0);
waitKey();
return 0;
}
void Sharpen(const Mat& myImage,Mat& Result)
@@ -83,4 +84,4 @@ void Sharpen(const Mat& myImage,Mat& Result)
Result.row(Result.rows-1).setTo(Scalar(0));
Result.col(0).setTo(Scalar(0));
Result.col(Result.cols-1).setTo(Scalar(0));
}
}

10
samples/cpp/tutorial_code/core/mat_the_basic_image_container/mat_the_basic_image_container.cpp
View File

@@ -59,10 +59,10 @@ int main(int,char**)
// Demonstrate the output formating options
cout << "R (default) = " << endl << R << endl << endl;
cout << "R (python) = " << endl << format(R,"python") << endl << endl;
cout << "R (numpy) = " << endl << format(R,"numpy" ) << endl << endl;
cout << "R (csv) = " << endl << format(R,"csv" ) << endl << endl;
cout << "R (c) = " << endl << format(R,"C" ) << endl << endl;
cout << "R (python) = " << endl << format(R, Formatter::FMT_PYTHON) << endl << endl;
cout << "R (numpy) = " << endl << format(R, Formatter::FMT_NUMPY ) << endl << endl;
cout << "R (csv) = " << endl << format(R, Formatter::FMT_CSV ) << endl << endl;
cout << "R (c) = " << endl << format(R, Formatter::FMT_C ) << endl << endl;
Point2f P(5, 1);
cout << "Point (2D) = " << P << endl << endl;
@@ -82,4 +82,4 @@ int main(int,char**)
cout << "A vector of 2D Points = " << vPoints << endl << endl;
return 0;
}
}

6
samples/cpp/tutorial_code/features2D/SURF_FlannMatcher.cpp
View File

@@ -25,8 +25,8 @@ int main( int argc, char** argv )
if( argc != 3 )
{ readme(); return -1; }
Mat img_1 = imread( argv[1], CV_LOAD_IMAGE_GRAYSCALE );
Mat img_2 = imread( argv[2], CV_LOAD_IMAGE_GRAYSCALE );
Mat img_1 = imread( argv[1], IMREAD_GRAYSCALE );
Mat img_2 = imread( argv[2], IMREAD_GRAYSCALE );
if( !img_1.data || !img_2.data )
{ std::cout<< " --(!) Error reading images " << std::endl; return -1; }
@@ -71,7 +71,7 @@ int main( int argc, char** argv )
std::vector< DMatch > good_matches;
for( int i = 0; i < descriptors_1.rows; i++ )
{ if( matches[i].distance < 2*min_dist )
{ if( matches[i].distance <= 2*min_dist )
{ good_matches.push_back( matches[i]); }
}

10
samples/cpp/tutorial_code/features2D/SURF_Homography.cpp
View File

@@ -26,8 +26,8 @@ int main( int argc, char** argv )
if( argc != 3 )
{ readme(); return -1; }
Mat img_object = imread( argv[1], CV_LOAD_IMAGE_GRAYSCALE );
Mat img_scene = imread( argv[2], CV_LOAD_IMAGE_GRAYSCALE );
Mat img_object = imread( argv[1], IMREAD_GRAYSCALE );
Mat img_scene = imread( argv[2], IMREAD_GRAYSCALE );
if( !img_object.data || !img_scene.data )
{ std::cout<< " --(!) Error reading images " << std::endl; return -1; }
@@ -92,12 +92,12 @@ int main( int argc, char** argv )
scene.push_back( keypoints_scene[ good_matches[i].trainIdx ].pt );
}
Mat H = findHomography( obj, scene, CV_RANSAC );
Mat H = findHomography( obj, scene, RANSAC );
//-- Get the corners from the image_1 ( the object to be "detected" )
std::vector<Point2f> obj_corners(4);
obj_corners[0] = cvPoint(0,0); obj_corners[1] = cvPoint( img_object.cols, 0 );
obj_corners[2] = cvPoint( img_object.cols, img_object.rows ); obj_corners[3] = cvPoint( 0, img_object.rows );
obj_corners[0] = Point(0,0); obj_corners[1] = Point( img_object.cols, 0 );
obj_corners[2] = Point( img_object.cols, img_object.rows ); obj_corners[3] = Point( 0, img_object.rows );
std::vector<Point2f> scene_corners(4);
perspectiveTransform( obj_corners, scene_corners, H);

4
samples/cpp/tutorial_code/features2D/SURF_descriptor.cpp
View File

@@ -24,8 +24,8 @@ int main( int argc, char** argv )
if( argc != 3 )
{ return -1; }
Mat img_1 = imread( argv[1], CV_LOAD_IMAGE_GRAYSCALE );
Mat img_2 = imread( argv[2], CV_LOAD_IMAGE_GRAYSCALE );
Mat img_1 = imread( argv[1], IMREAD_GRAYSCALE );
Mat img_2 = imread( argv[2], IMREAD_GRAYSCALE );
if( !img_1.data || !img_2.data )
{ return -1; }

4
samples/cpp/tutorial_code/features2D/SURF_detector.cpp
View File

@@ -24,8 +24,8 @@ int main( int argc, char** argv )
if( argc != 3 )
{ readme(); return -1; }
Mat img_1 = imread( argv[1], CV_LOAD_IMAGE_GRAYSCALE );
Mat img_2 = imread( argv[2], CV_LOAD_IMAGE_GRAYSCALE );
Mat img_1 = imread( argv[1], IMREAD_GRAYSCALE );
Mat img_2 = imread( argv[2], IMREAD_GRAYSCALE );
if( !img_1.data || !img_2.data )
{ std::cout<< " --(!) Error reading images " << std::endl; return -1; }

53
samples/cpp/tutorial_code/gpu/gpu-basics-similarity/gpu-basics-similarity.cpp
View File

@@ -1,10 +1,14 @@
#include <iostream> // Console I/O
#include <sstream> // String to number conversion
#include <opencv2/core/core.hpp> // Basic OpenCV structures
#include <opencv2/imgproc/imgproc.hpp>// Image processing methods for the CPU
#include <opencv2/highgui/highgui.hpp>// Read images
#include <opencv2/gpu/gpu.hpp> // GPU structures and methods
#include <opencv2/core.hpp> // Basic OpenCV structures
#include <opencv2/core/utility.hpp>
#include <opencv2/imgproc.hpp>// Image processing methods for the CPU
#include <opencv2/highgui.hpp>// Read images
// GPU structures and methods
#include <opencv2/gpuarithm.hpp>
#include <opencv2/gpufilters.hpp>
using namespace std;
using namespace cv;
@@ -304,6 +308,8 @@ Scalar getMSSIM_GPU( const Mat& i1, const Mat& i2)
gpu::split(tmp2, vI2);
Scalar mssim;
Ptr<gpu::Filter> gauss = gpu::createGaussianFilter(vI2[0].type(), -1, Size(11, 11), 1.5);
for( int i = 0; i < gI1.channels(); ++i )
{
gpu::GpuMat I2_2, I1_2, I1_I2;
@@ -314,8 +320,8 @@ Scalar getMSSIM_GPU( const Mat& i1, const Mat& i2)
/*************************** END INITS **********************************/
gpu::GpuMat mu1, mu2; // PRELIMINARY COMPUTING
gpu::GaussianBlur(vI1[i], mu1, Size(11, 11), 1.5);
gpu::GaussianBlur(vI2[i], mu2, Size(11, 11), 1.5);
gauss->apply(vI1[i], mu1);
gauss->apply(vI2[i], mu2);
gpu::GpuMat mu1_2, mu2_2, mu1_mu2;
gpu::multiply(mu1, mu1, mu1_2);
@@ -324,13 +330,13 @@ Scalar getMSSIM_GPU( const Mat& i1, const Mat& i2)
gpu::GpuMat sigma1_2, sigma2_2, sigma12;
gpu::GaussianBlur(I1_2, sigma1_2, Size(11, 11), 1.5);
gauss->apply(I1_2, sigma1_2);
gpu::subtract(sigma1_2, mu1_2, sigma1_2); // sigma1_2 -= mu1_2;
gpu::GaussianBlur(I2_2, sigma2_2, Size(11, 11), 1.5);
gauss->apply(I2_2, sigma2_2);
gpu::subtract(sigma2_2, mu2_2, sigma2_2); // sigma2_2 -= mu2_2;
gpu::GaussianBlur(I1_I2, sigma12, Size(11, 11), 1.5);
gauss->apply(I1_I2, sigma12);
gpu::subtract(sigma12, mu1_mu2, sigma12); // sigma12 -= mu1_mu2;
///////////////////////////////// FORMULA ////////////////////////////////
@@ -364,37 +370,37 @@ Scalar getMSSIM_GPU_optimized( const Mat& i1, const Mat& i2, BufferMSSIM& b)
gpu::Stream stream;
stream.enqueueConvert(b.gI1, b.t1, CV_32F);
stream.enqueueConvert(b.gI2, b.t2, CV_32F);
b.gI1.convertTo(b.t1, CV_32F, stream);
b.gI2.convertTo(b.t2, CV_32F, stream);
gpu::split(b.t1, b.vI1, stream);
gpu::split(b.t2, b.vI2, stream);
Scalar mssim;
gpu::GpuMat buf;
Ptr<gpu::Filter> gauss = gpu::createGaussianFilter(b.vI1[0].type(), -1, Size(11, 11), 1.5);
for( int i = 0; i < b.gI1.channels(); ++i )
{
gpu::multiply(b.vI2[i], b.vI2[i], b.I2_2, stream); // I2^2
gpu::multiply(b.vI1[i], b.vI1[i], b.I1_2, stream); // I1^2
gpu::multiply(b.vI1[i], b.vI2[i], b.I1_I2, stream); // I1 * I2
gpu::multiply(b.vI2[i], b.vI2[i], b.I2_2, 1, -1, stream); // I2^2
gpu::multiply(b.vI1[i], b.vI1[i], b.I1_2, 1, -1, stream); // I1^2
gpu::multiply(b.vI1[i], b.vI2[i], b.I1_I2, 1, -1, stream); // I1 * I2
gpu::GaussianBlur(b.vI1[i], b.mu1, Size(11, 11), buf, 1.5, 0, BORDER_DEFAULT, -1, stream);
gpu::GaussianBlur(b.vI2[i], b.mu2, Size(11, 11), buf, 1.5, 0, BORDER_DEFAULT, -1, stream);
gauss->apply(b.vI1[i], b.mu1, stream);
gauss->apply(b.vI2[i], b.mu2, stream);
gpu::multiply(b.mu1, b.mu1, b.mu1_2, stream);
gpu::multiply(b.mu2, b.mu2, b.mu2_2, stream);
gpu::multiply(b.mu1, b.mu2, b.mu1_mu2, stream);
gpu::multiply(b.mu1, b.mu1, b.mu1_2, 1, -1, stream);
gpu::multiply(b.mu2, b.mu2, b.mu2_2, 1, -1, stream);
gpu::multiply(b.mu1, b.mu2, b.mu1_mu2, 1, -1, stream);
gpu::GaussianBlur(b.I1_2, b.sigma1_2, Size(11, 11), buf, 1.5, 0, BORDER_DEFAULT, -1, stream);
gauss->apply(b.I1_2, b.sigma1_2, stream);
gpu::subtract(b.sigma1_2, b.mu1_2, b.sigma1_2, gpu::GpuMat(), -1, stream);
//b.sigma1_2 -= b.mu1_2; - This would result in an extra data transfer operation
gpu::GaussianBlur(b.I2_2, b.sigma2_2, Size(11, 11), buf, 1.5, 0, BORDER_DEFAULT, -1, stream);
gauss->apply(b.I2_2, b.sigma2_2, stream);
gpu::subtract(b.sigma2_2, b.mu2_2, b.sigma2_2, gpu::GpuMat(), -1, stream);
//b.sigma2_2 -= b.mu2_2;
gpu::GaussianBlur(b.I1_I2, b.sigma12, Size(11, 11), buf, 1.5, 0, BORDER_DEFAULT, -1, stream);
gauss->apply(b.I1_I2, b.sigma12, stream);
gpu::subtract(b.sigma12, b.mu1_mu2, b.sigma12, gpu::GpuMat(), -1, stream);
//b.sigma12 -= b.mu1_mu2;
@@ -424,4 +430,3 @@ Scalar getMSSIM_GPU_optimized( const Mat& i1, const Mat& i2, BufferMSSIM& b)
}
return mssim;
}

12
samples/cpp/tutorial_code/introduction/display_image/display_image.cpp
View File

@@ -14,17 +14,17 @@ int main( int argc, char** argv )
}
Mat image;
image = imread(argv[1], CV_LOAD_IMAGE_COLOR); // Read the file
image = imread(argv[1], IMREAD_COLOR); // Read the file
if(! image.data ) // Check for invalid input
if(! image.data ) // Check for invalid input
{
cout << "Could not open or find the image" << std::endl ;
return -1;
}
namedWindow( "Display window", CV_WINDOW_AUTOSIZE );// Create a window for display.
imshow( "Display window", image ); // Show our image inside it.
namedWindow( "Display window", WINDOW_AUTOSIZE ); // Create a window for display.
imshow( "Display window", image ); // Show our image inside it.
waitKey(0); // Wait for a keystroke in the window
waitKey(0); // Wait for a keystroke in the window
return 0;
}
}

22
samples/cpp/tutorial_code/introduction/windows_visual_studio_Opencv/Test.cpp
View File

@@ -59,10 +59,10 @@ int main(int argc, char *argv[])
return -1;
}
Size refS = Size((int) captRefrnc.get(CV_CAP_PROP_FRAME_WIDTH),
(int) captRefrnc.get(CV_CAP_PROP_FRAME_HEIGHT)),
uTSi = Size((int) captUndTst.get(CV_CAP_PROP_FRAME_WIDTH),
(int) captUndTst.get(CV_CAP_PROP_FRAME_HEIGHT));
Size refS = Size((int) captRefrnc.get(CAP_PROP_FRAME_WIDTH),
(int) captRefrnc.get(CAP_PROP_FRAME_HEIGHT)),
uTSi = Size((int) captUndTst.get(CAP_PROP_FRAME_WIDTH),
(int) captUndTst.get(CAP_PROP_FRAME_HEIGHT));
if (refS != uTSi)
{
@@ -74,13 +74,13 @@ int main(int argc, char *argv[])
const char* WIN_RF = "Reference";
// Windows
namedWindow(WIN_RF, CV_WINDOW_AUTOSIZE );
namedWindow(WIN_UT, CV_WINDOW_AUTOSIZE );
cvMoveWindow(WIN_RF, 400 , 0); //750, 2 (bernat =0)
cvMoveWindow(WIN_UT, refS.width, 0); //1500, 2
namedWindow(WIN_RF, WINDOW_AUTOSIZE );
namedWindow(WIN_UT, WINDOW_AUTOSIZE );
moveWindow(WIN_RF, 400 , 0); //750, 2 (bernat =0)
moveWindow(WIN_UT, refS.width, 0); //1500, 2
cout << "Frame resolution: Width=" << refS.width << " Height=" << refS.height
<< " of nr#: " << captRefrnc.get(CV_CAP_PROP_FRAME_COUNT) << endl;
<< " of nr#: " << captRefrnc.get(CAP_PROP_FRAME_COUNT) << endl;
cout << "PSNR trigger value " <<
setiosflags(ios::fixed) << setprecision(3) << psnrTriggerValue << endl;
@@ -124,7 +124,7 @@ int main(int argc, char *argv[])
imshow( WIN_RF, frameReference);
imshow( WIN_UT, frameUnderTest);
c = (char)cvWaitKey(delay);
c = (char)waitKey(delay);
if (c == 27) break;
}
@@ -203,4 +203,4 @@ Scalar getMSSIM( const Mat& i1, const Mat& i2)
Scalar mssim = mean( ssim_map ); // mssim = average of ssim map
return mssim;
}
}

2
samples/cpp/tutorial_code/ml/non_linear_svms/non_linear_svms.cpp
View File

@@ -127,4 +127,4 @@ int main()
imwrite("result.png", I); // save the Image
imshow("SVM for Non-Linear Training Data", I); // show it to the user
waitKey(0);
}
}

111
samples/cpp/tutorial_code/objectDetection/objectDetection.cpp
View File

@@ -1,11 +1,6 @@
/**
* @file objectDetection.cpp
* @author A. Huaman ( based in the classic facedetect.cpp in samples/c )
* @brief A simplified version of facedetect.cpp, show how to load a cascade classifier and how to find objects (Face + eyes) in a video stream
*/
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/objdetect.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include <iostream>
#include <stdio.h>
@@ -17,79 +12,73 @@ using namespace cv;
void detectAndDisplay( Mat frame );
/** Global variables */
//-- Note, either copy these two files from opencv/data/haarscascades to your current folder, or change these locations
string face_cascade_name = "haarcascade_frontalface_alt.xml";
string eyes_cascade_name = "haarcascade_eye_tree_eyeglasses.xml";
String face_cascade_name = "haarcascade_frontalface_alt.xml";
String eyes_cascade_name = "haarcascade_eye_tree_eyeglasses.xml";
CascadeClassifier face_cascade;
CascadeClassifier eyes_cascade;
string window_name = "Capture - Face detection";
RNG rng(12345);
String window_name = "Capture - Face detection";
/**
* @function main
*/
/** @function main */
int main( void )
{
CvCapture* capture;
Mat frame;
VideoCapture capture;
Mat frame;
//-- 1. Load the cascades
if( !face_cascade.load( face_cascade_name ) ){ printf("--(!)Error loading\n"); return -1; };
if( !eyes_cascade.load( eyes_cascade_name ) ){ printf("--(!)Error loading\n"); return -1; };
//-- 1. Load the cascades
if( !face_cascade.load( face_cascade_name ) ){ printf("--(!)Error loading face cascade\n"); return -1; };
if( !eyes_cascade.load( eyes_cascade_name ) ){ printf("--(!)Error loading eyes cascade\n"); return -1; };
//-- 2. Read the video stream
capture = cvCaptureFromCAM( -1 );
if( capture )
{
for(;;)
//-- 2. Read the video stream
capture.open( -1 );
if ( ! capture.isOpened() ) { printf("--(!)Error opening video capture\n"); return -1; }
while ( capture.read(frame) )
{
frame = cvQueryFrame( capture );
if( frame.empty() )
{
printf(" --(!) No captured frame -- Break!");
break;
}
//-- 3. Apply the classifier to the frame
if( !frame.empty() )
{ detectAndDisplay( frame ); }
else
{ printf(" --(!) No captured frame -- Break!"); break; }
int c = waitKey(10);
if( (char)c == 'c' ) { break; }
//-- 3. Apply the classifier to the frame
detectAndDisplay( frame );
int c = waitKey(10);
if( (char)c == 27 ) { break; } // escape
}
}
return 0;
return 0;
}
/**
* @function detectAndDisplay
*/
/** @function detectAndDisplay */
void detectAndDisplay( Mat frame )
{
std::vector<Rect> faces;
Mat frame_gray;
std::vector<Rect> faces;
Mat frame_gray;
cvtColor( frame, frame_gray, CV_BGR2GRAY );
equalizeHist( frame_gray, frame_gray );
//-- Detect faces
face_cascade.detectMultiScale( frame_gray, faces, 1.1, 2, 0|CV_HAAR_SCALE_IMAGE, Size(30, 30) );
cvtColor( frame, frame_gray, COLOR_BGR2GRAY );
equalizeHist( frame_gray, frame_gray );
for( size_t i = 0; i < faces.size(); i++ )
//-- Detect faces
face_cascade.detectMultiScale( frame_gray, faces, 1.1, 2, 0|CASCADE_SCALE_IMAGE, Size(30, 30) );
for ( size_t i = 0; i < faces.size(); i++ )
{
Point center( faces[i].x + faces[i].width/2, faces[i].y + faces[i].height/2 );
ellipse( frame, center, Size( faces[i].width/2, faces[i].height/2), 0, 0, 360, Scalar( 255, 0, 255 ), 2, 8, 0 );
Point center( faces[i].x + faces[i].width/2, faces[i].y + faces[i].height/2 );
ellipse( frame, center, Size( faces[i].width/2, faces[i].height/2 ), 0, 0, 360, Scalar( 255, 0, 255 ), 4, 8, 0 );
Mat faceROI = frame_gray( faces[i] );
std::vector<Rect> eyes;
Mat faceROI = frame_gray( faces[i] );
std::vector<Rect> eyes;
//-- In each face, detect eyes
eyes_cascade.detectMultiScale( faceROI, eyes, 1.1, 2, 0 |CV_HAAR_SCALE_IMAGE, Size(30, 30) );
//-- In each face, detect eyes
eyes_cascade.detectMultiScale( faceROI, eyes, 1.1, 2, 0 |CASCADE_SCALE_IMAGE, Size(30, 30) );
for( size_t j = 0; j < eyes.size(); j++ )
{
Point eye_center( faces[i].x + eyes[j].x + eyes[j].width/2, faces[i].y + eyes[j].y + eyes[j].height/2 );
int radius = cvRound( (eyes[j].width + eyes[j].height)*0.25 );
circle( frame, eye_center, radius, Scalar( 255, 0, 0 ), 3, 8, 0 );
}
for ( size_t j = 0; j < eyes.size(); j++ )
{
Point eye_center( faces[i].x + eyes[j].x + eyes[j].width/2, faces[i].y + eyes[j].y + eyes[j].height/2 );
int radius = cvRound( (eyes[j].width + eyes[j].height)*0.25 );
circle( frame, eye_center, radius, Scalar( 255, 0, 0 ), 4, 8, 0 );
}
}
//-- Show what you got
imshow( window_name, frame );
//-- Show what you got
imshow( window_name, frame );
}

107
samples/cpp/tutorial_code/objectDetection/objectDetection2.cpp
View File

@@ -3,9 +3,9 @@
* @author A. Huaman ( based in the classic facedetect.cpp in samples/c )
* @brief A simplified version of facedetect.cpp, show how to load a cascade classifier and how to find objects (Face + eyes) in a video stream - Using LBP here
*/
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/objdetect.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include <iostream>
#include <stdio.h>
@@ -17,46 +17,43 @@ using namespace cv;
void detectAndDisplay( Mat frame );
/** Global variables */
string face_cascade_name = "lbpcascade_frontalface.xml";
string eyes_cascade_name = "haarcascade_eye_tree_eyeglasses.xml";
String face_cascade_name = "lbpcascade_frontalface.xml";
String eyes_cascade_name = "haarcascade_eye_tree_eyeglasses.xml";
CascadeClassifier face_cascade;
CascadeClassifier eyes_cascade;
string window_name = "Capture - Face detection";
RNG rng(12345);
String window_name = "Capture - Face detection";
/**
* @function main
*/
int main( void )
{
CvCapture* capture;
Mat frame;
VideoCapture capture;
Mat frame;
//-- 1. Load the cascade
if( !face_cascade.load( face_cascade_name ) ){ printf("--(!)Error loading\n"); return -1; };
if( !eyes_cascade.load( eyes_cascade_name ) ){ printf("--(!)Error loading\n"); return -1; };
//-- 1. Load the cascade
if( !face_cascade.load( face_cascade_name ) ){ printf("--(!)Error loading face cascade\n"); return -1; };
if( !eyes_cascade.load( eyes_cascade_name ) ){ printf("--(!)Error loading eyes cascade\n"); return -1; };
//-- 2. Read the video stream
capture = cvCaptureFromCAM( -1 );
if( capture )
{
for(;;)
//-- 2. Read the video stream
capture.open( -1 );
if ( ! capture.isOpened() ) { printf("--(!)Error opening video capture\n"); return -1; }
while ( capture.read(frame) )
{
frame = cvQueryFrame( capture );
if( frame.empty() )
{
printf(" --(!) No captured frame -- Break!");
break;
}
//-- 3. Apply the classifier to the frame
if( !frame.empty() )
{ detectAndDisplay( frame ); }
else
{ printf(" --(!) No captured frame -- Break!"); break; }
int c = waitKey(10);
if( (char)c == 'c' ) { break; }
//-- 3. Apply the classifier to the frame
detectAndDisplay( frame );
//-- bail out if escape was pressed
int c = waitKey(10);
if( (char)c == 27 ) { break; }
}
}
return 0;
return 0;
}
/**
@@ -64,37 +61,37 @@ int main( void )
*/
void detectAndDisplay( Mat frame )
{
std::vector<Rect> faces;
Mat frame_gray;
std::vector<Rect> faces;
Mat frame_gray;
cvtColor( frame, frame_gray, CV_BGR2GRAY );
equalizeHist( frame_gray, frame_gray );
cvtColor( frame, frame_gray, COLOR_BGR2GRAY );
equalizeHist( frame_gray, frame_gray );
//-- Detect faces
face_cascade.detectMultiScale( frame_gray, faces, 1.1, 2, 0, Size(80, 80) );
//-- Detect faces
face_cascade.detectMultiScale( frame_gray, faces, 1.1, 2, 0, Size(80, 80) );
for( size_t i = 0; i < faces.size(); i++ )
for( size_t i = 0; i < faces.size(); i++ )
{
Mat faceROI = frame_gray( faces[i] );
std::vector<Rect> eyes;
Mat faceROI = frame_gray( faces[i] );
std::vector<Rect> eyes;
//-- In each face, detect eyes
eyes_cascade.detectMultiScale( faceROI, eyes, 1.1, 2, 0 |CV_HAAR_SCALE_IMAGE, Size(30, 30) );
if( eyes.size() == 2)
{
//-- Draw the face
Point center( faces[i].x + faces[i].width/2, faces[i].y + faces[i].height/2 );
ellipse( frame, center, Size( faces[i].width/2, faces[i].height/2), 0, 0, 360, Scalar( 255, 0, 0 ), 2, 8, 0 );
//-- In each face, detect eyes
eyes_cascade.detectMultiScale( faceROI, eyes, 1.1, 2, 0 |CASCADE_SCALE_IMAGE, Size(30, 30) );
if( eyes.size() == 2)
{
//-- Draw the face
Point center( faces[i].x + faces[i].width/2, faces[i].y + faces[i].height/2 );
ellipse( frame, center, Size( faces[i].width/2, faces[i].height/2 ), 0, 0, 360, Scalar( 255, 0, 0 ), 2, 8, 0 );
for( size_t j = 0; j < eyes.size(); j++ )
{ //-- Draw the eyes
Point eye_center( faces[i].x + eyes[j].x + eyes[j].width/2, faces[i].y + eyes[j].y + eyes[j].height/2 );
int radius = cvRound( (eyes[j].width + eyes[j].height)*0.25 );
circle( frame, eye_center, radius, Scalar( 255, 0, 255 ), 3, 8, 0 );
}
}
for( size_t j = 0; j < eyes.size(); j++ )
{ //-- Draw the eyes
Point eye_center( faces[i].x + eyes[j].x + eyes[j].width/2, faces[i].y + eyes[j].y + eyes[j].height/2 );
int radius = cvRound( (eyes[j].width + eyes[j].height)*0.25 );
circle( frame, eye_center, radius, Scalar( 255, 0, 255 ), 3, 8, 0 );
}
}
}
//-- Show what you got
imshow( window_name, frame );
//-- Show what you got
imshow( window_name, frame );
}