third_party/opencv
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Update samples (#10333)

Browse Source 
* Update samples

* Update calib3d.hpp

* Update calib3d.hpp

* Update calib3d.hpp

* Update calib3d.hpp
This commit is contained in:
Suleyman TURKMEN
2017-12-18 12:44:11 +02:00
committed by Vadim Pisarevsky
parent d3a124c820
commit 1654dfe3a9
36 changed files with 285 additions and 224 deletions
Download Patch File Download Diff File Expand all files Collapse all files
samples/cpp/tutorial_code/objectDetection/objectDetection.cpp
+6 -9
View File
@@ -1,9 +1,7 @@
#include "opencv2/objdetect.hpp"
#include "opencv2/videoio.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include <iostream>
#include <stdio.h>
using namespace std;
@@ -26,12 +24,12 @@ int main( int argc, const char** argv )
"{face_cascade|../../data/haarcascades/haarcascade_frontalface_alt.xml|}"
"{eyes_cascade|../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml|}");
cout << "\nThis program demonstrates using the cv::CascadeClassifier class to detect objects (Face + eyes) in a video stream.\n"
"You can use Haar or LBP features.\n\n";
parser.about( "\nThis program demonstrates using the cv::CascadeClassifier class to detect objects (Face + eyes) in a video stream.\n"
"You can use Haar or LBP features.\n\n" );
parser.printMessage();
face_cascade_name = parser.get<string>("face_cascade");
eyes_cascade_name = parser.get<string>("eyes_cascade");
face_cascade_name = parser.get<String>("face_cascade");
eyes_cascade_name = parser.get<String>("eyes_cascade");
VideoCapture capture;
Mat frame;
@@ -54,8 +52,7 @@ int main( int argc, const char** argv )
//-- 3. Apply the classifier to the frame
detectAndDisplay( frame );
char c = (char)waitKey(10);
if( c == 27 ) { break; } // escape
if( waitKey(10) == 27 ) { break; } // escape
}
return 0;
}
@@ -70,7 +67,7 @@ void detectAndDisplay( Mat frame )
equalizeHist( frame_gray, frame_gray );
//-- Detect faces
face_cascade.detectMultiScale( frame_gray, faces, 1.1, 2, 0|CASCADE_SCALE_IMAGE, Size(30, 30) );
face_cascade.detectMultiScale( frame_gray, faces, 1.1, 2, 0|CASCADE_SCALE_IMAGE, Size(60, 60) );
for ( size_t i = 0; i < faces.size(); i++ )
{