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Add Java and Python code for cascade classifier and HDR tutorials.

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This commit is contained in:
catree
2018-06-07 20:14:16 +02:00
parent 1187a7fa34
commit afa5b0cc93
13 changed files with 557 additions and 100 deletions
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63
samples/cpp/tutorial_code/objectDetection/objectDetection.cpp
View File

@@ -2,7 +2,7 @@
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include <stdio.h>
#include <iostream>
using namespace std;
using namespace cv;
@@ -11,48 +11,63 @@ using namespace cv;
void detectAndDisplay( Mat frame );
/** Global variables */
String face_cascade_name, eyes_cascade_name;
CascadeClassifier face_cascade;
CascadeClassifier eyes_cascade;
String window_name = "Capture - Face detection";
/** @function main */
int main( int argc, const char** argv )
{
CommandLineParser parser(argc, argv,
"{help h||}"
"{face_cascade|../../data/haarcascades/haarcascade_frontalface_alt.xml|}"
"{eyes_cascade|../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml|}");
"{help h||}"
"{face_cascade|../../data/haarcascades/haarcascade_frontalface_alt.xml|Path to face cascade.}"
"{eyes_cascade|../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml|Path to eyes cascade.}"
"{camera|0|Camera device number.}");
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");
VideoCapture capture;
Mat frame;
String face_cascade_name = parser.get<String>("face_cascade");
String eyes_cascade_name = parser.get<String>("eyes_cascade");
//-- 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; };
if( !face_cascade.load( face_cascade_name ) )
{
cout << "--(!)Error loading face cascade\n";
return -1;
};
if( !eyes_cascade.load( eyes_cascade_name ) )
{
cout << "--(!)Error loading eyes cascade\n";
return -1;
};
int camera_device = parser.get<int>("camera");
VideoCapture capture;
//-- 2. Read the video stream
capture.open( 0 );
if ( ! capture.isOpened() ) { printf("--(!)Error opening video capture\n"); return -1; }
capture.open( camera_device );
if ( ! capture.isOpened() )
{
cout << "--(!)Error opening video capture\n";
return -1;
}
Mat frame;
while ( capture.read(frame) )
{
if( frame.empty() )
{
printf(" --(!) No captured frame -- Break!");
cout << "--(!) No captured frame -- Break!\n";
break;
}
//-- 3. Apply the classifier to the frame
detectAndDisplay( frame );
if( waitKey(10) == 27 ) { break; } // escape
if( waitKey(10) == 27 )
{
break; // escape
}
}
return 0;
}
@@ -60,33 +75,33 @@ int main( int argc, const char** argv )
/** @function detectAndDisplay */
void detectAndDisplay( Mat frame )
{
std::vector<Rect> faces;
Mat 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|CASCADE_SCALE_IMAGE, Size(60, 60) );
std::vector<Rect> faces;
face_cascade.detectMultiScale( frame_gray, faces );
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 ), 4, 8, 0 );
ellipse( frame, center, Size( faces[i].width/2, faces[i].height/2 ), 0, 0, 360, Scalar( 255, 0, 255 ), 4 );
Mat faceROI = frame_gray( faces[i] );
std::vector<Rect> eyes;
//-- In each face, detect eyes
eyes_cascade.detectMultiScale( faceROI, eyes, 1.1, 2, 0 |CASCADE_SCALE_IMAGE, Size(30, 30) );
std::vector<Rect> eyes;
eyes_cascade.detectMultiScale( faceROI, eyes );
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 );
circle( frame, eye_center, radius, Scalar( 255, 0, 0 ), 4 );
}
}
//-- Show what you got
imshow( window_name, frame );
imshow( "Capture - Face detection", frame );
}

25
samples/cpp/tutorial_code/photo/hdr_imaging/hdr_imaging.cpp
View File

@@ -1,6 +1,7 @@
#include <opencv2/photo.hpp>
#include "opencv2/photo.hpp"
#include "opencv2/imgcodecs.hpp"
#include <opencv2/highgui.hpp>
#include "opencv2/highgui.hpp"
#include <vector>
#include <iostream>
#include <fstream>
@@ -10,38 +11,52 @@ using namespace std;
void loadExposureSeq(String, vector<Mat>&, vector<float>&);
int main(int, char**argv)
int main(int argc, char**argv)
{
CommandLineParser parser( argc, argv, "{@input | | Input directory that contains images and exposure times. }" );
//! [Load images and exposure times]
vector<Mat> images;
vector<float> times;
loadExposureSeq(argv[1], images, times);
loadExposureSeq(parser.get<String>( "@input" ), images, times);
//! [Load images and exposure times]
//! [Estimate camera response]
Mat response;
Ptr<CalibrateDebevec> calibrate = createCalibrateDebevec();
calibrate->process(images, response, times);
//! [Estimate camera response]
//! [Make HDR image]
Mat hdr;
Ptr<MergeDebevec> merge_debevec = createMergeDebevec();
merge_debevec->process(images, hdr, times, response);
//! [Make HDR image]
//! [Tonemap HDR image]
Mat ldr;
Ptr<TonemapDurand> tonemap = createTonemapDurand(2.2f);
tonemap->process(hdr, ldr);
//! [Tonemap HDR image]
//! [Perform exposure fusion]
Mat fusion;
Ptr<MergeMertens> merge_mertens = createMergeMertens();
merge_mertens->process(images, fusion);
//! [Perform exposure fusion]
//! [Write results]
imwrite("fusion.png", fusion * 255);
imwrite("ldr.png", ldr * 255);
imwrite("hdr.hdr", hdr);
//! [Write results]
return 0;
}
void loadExposureSeq(String path, vector<Mat>& images, vector<float>& times)
{
path = path + std::string("/");
path = path + "/";
ifstream list_file((path + "list.txt").c_str());
string name;
float val;