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This commit is contained in:
Konstantin Matskevich 2014-01-20 10:25:05 +04:00
parent ee88cc2c52
commit 450ea3131f
9 changed files with 1574 additions and 1 deletions
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2
samples/tapi/CMakeLists.txt
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SET(OPENCV_TAPI_SAMPLES_REQUIRED_DEPS opencv_core opencv_imgproc opencv_video opencv_highgui) SET(OPENCV_TAPI_SAMPLES_REQUIRED_DEPS opencv_core opencv_imgproc opencv_video opencv_highgui opencv_objdetect opencv_features2d opencv_calib3d opencv_nonfree opencv_flann)
ocv_check_dependencies(${OPENCV_TAPI_SAMPLES_REQUIRED_DEPS}) ocv_check_dependencies(${OPENCV_TAPI_SAMPLES_REQUIRED_DEPS})

122
samples/tapi/bgfg_segm.cpp Normal file
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#include <iostream>
#include <string>
#include "opencv2/core.hpp"
#include "opencv2/core/ocl.hpp"
#include "opencv2/core/utility.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/video.hpp"
using namespace std;
using namespace cv;
#define M_MOG 1
#define M_MOG2 2
int main(int argc, const char** argv)
{
cv::CommandLineParser cmd(argc, argv,
"{ c camera | false | use camera }"
"{ f file | 768x576.avi | input video file }"
"{ t type | mog | method's type (mog, mog2) }"
"{ h help | false | print help message }"
"{ m cpu_mode | false | press 'm' to switch OpenCL<->CPU}");
if (cmd.has("help"))
{
cout << "Usage : bgfg_segm [options]" << endl;
cout << "Available options:" << endl;
cmd.printMessage();
return EXIT_SUCCESS;
}
bool useCamera = cmd.has("camera");
string file = cmd.get<string>("file");
string method = cmd.get<string>("type");
if (method != "mog" && method != "mog2")
{
cerr << "Incorrect method" << endl;
return EXIT_FAILURE;
}
int m = method == "mog" ? M_MOG : M_MOG2;
VideoCapture cap;
if (useCamera)
cap.open(0);
else
cap.open(file);
if (!cap.isOpened())
{
cout << "can not open camera or video file" << endl;
return EXIT_FAILURE;
}
UMat frame, fgmask, fgimg;
cap >> frame;
fgimg.create(frame.size(), frame.type());
Ptr<cv::BackgroundSubtractorMOG> mog = createBackgroundSubtractorMOG();
cv::Ptr<cv::BackgroundSubtractorMOG2> mog2 = createBackgroundSubtractorMOG2();
switch (m)
{
case M_MOG:
mog->apply(frame, fgmask, 0.01f);
break;
case M_MOG2:
mog2->apply(frame, fgmask);
break;
}
bool running=true;
for (;;)
{
if(!running)
break;
cap >> frame;
if (frame.empty())
break;
int64 start = cv::getTickCount();
//update the model
switch (m)
{
case M_MOG:
mog->apply(frame, fgmask, 0.01f);
break;
case M_MOG2:
mog2->apply(frame, fgmask);
break;
}
double fps = cv::getTickFrequency() / (cv::getTickCount() - start);
std::cout << "FPS : " << fps << std::endl;
std::cout << fgimg.size() << std::endl;
fgimg.setTo(Scalar::all(0));
frame.copyTo(fgimg, fgmask);
imshow("image", frame);
imshow("foreground mask", fgmask);
imshow("foreground image", fgimg);
char key = (char)waitKey(30);
switch (key)
{
case 27:
running = false;
break;
case 'm':
case 'M':
ocl::setUseOpenCL(!cv::ocl::useOpenCL());
cout << "Switched to " << (ocl::useOpenCL() ? "OpenCL" : "CPU") << " mode\n";
break;
}
}
return EXIT_SUCCESS;
}

107
samples/tapi/clahe.cpp Normal file
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#include <iostream>
#include "opencv2/core/core.hpp"
#include "opencv2/core/ocl.hpp"
#include "opencv2/core/utility.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
using namespace cv;
using namespace std;
Ptr<CLAHE> pFilter;
int tilesize;
int cliplimit;
static void TSize_Callback(int pos)
{
if(pos==0)
pFilter->setTilesGridSize(Size(1,1));
else
pFilter->setTilesGridSize(Size(tilesize,tilesize));
}
static void Clip_Callback(int)
{
pFilter->setClipLimit(cliplimit);
}
int main(int argc, char** argv)
{
const char* keys =
"{ i input | | specify input image }"
"{ c camera | 0 | specify camera id }"
"{ o output | clahe_output.jpg | specify output save path}"
"{ h help | false | print help message }";
cv::CommandLineParser cmd(argc, argv, keys);
if (cmd.has("help"))
{
cout << "Usage : clahe [options]" << endl;
cout << "Available options:" << endl;
cmd.printMessage();
return EXIT_SUCCESS;
}
string infile = cmd.get<string>("i"), outfile = cmd.get<string>("o");
int camid = cmd.get<int>("c");
VideoCapture capture;
namedWindow("CLAHE");
createTrackbar("Tile Size", "CLAHE", &tilesize, 32, (TrackbarCallback)TSize_Callback);
createTrackbar("Clip Limit", "CLAHE", &cliplimit, 20, (TrackbarCallback)Clip_Callback);
UMat frame, outframe;
int cur_clip;
Size cur_tilesize;
pFilter = createCLAHE();
cur_clip = (int)pFilter->getClipLimit();
cur_tilesize = pFilter->getTilesGridSize();
setTrackbarPos("Tile Size", "CLAHE", cur_tilesize.width);
setTrackbarPos("Clip Limit", "CLAHE", cur_clip);
if(infile != "")
{
imread(infile).copyTo(frame);
if(frame.empty())
{
cout << "error read image: " << infile << endl;
return EXIT_FAILURE;
}
}
else
capture.open(camid);
cout << "\nControls:\n"
<< "\to - save output image\n"
<< "\tm - switch OpenCL <-> CPU mode"
<< "\tESC - exit\n";
for (;;)
{
if(capture.isOpened())
capture.read(frame);
else
imread(infile).copyTo(frame);
if(frame.empty())
continue;
cvtColor(frame, frame, COLOR_BGR2GRAY);
pFilter->apply(frame, outframe);
imshow("CLAHE", outframe);
char key = (char)waitKey(3);
if(key == 'o')
imwrite(outfile, outframe);
else if(key == 27)
break;
else if(key == 'm')
{
ocl::setUseOpenCL(!cv::ocl::useOpenCL());
cout << "Switched to " << (ocl::useOpenCL() ? "OpenCL" : "CPU") << " mode\n";
}
}
return EXIT_SUCCESS;
}

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samples/tapi/hog.cpp Normal file
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#include <iostream>
#include <fstream>
#include <string>
#include <sstream>
#include <iomanip>
#include <stdexcept>
#include <opencv2/core/ocl.hpp>
#include <opencv2/core/utility.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/objdetect.hpp>
#include <opencv2/imgproc.hpp>
using namespace std;
using namespace cv;
class App
{
public:
App(CommandLineParser& cmd);
void run();
void handleKey(char key);
void hogWorkBegin();
void hogWorkEnd();
string hogWorkFps() const;
void workBegin();
void workEnd();
string workFps() const;
string message() const;
// This function test if gpu_rst matches cpu_rst.
// If the two vectors are not equal, it will return the difference in vector size
// Else if will return
// (total diff of each cpu and gpu rects covered pixels)/(total cpu rects covered pixels)
double checkRectSimilarity(Size sz,
std::vector<Rect>& cpu_rst,
std::vector<Rect>& gpu_rst);
private:
App operator=(App&);
//Args args;
bool running;
bool make_gray;
double scale;
double resize_scale;
int win_width;
int win_stride_width, win_stride_height;
int gr_threshold;
int nlevels;
double hit_threshold;
bool gamma_corr;
int64 hog_work_begin;
double hog_work_fps;
int64 work_begin;
double work_fps;
string img_source;
string vdo_source;
string output;
int camera_id;
bool write_once;
};
int main(int argc, char** argv)
{
const char* keys =
"{ h help | false | print help message }"
"{ i input | | specify input image}"
"{ c camera | -1 | enable camera capturing }"
"{ v video | 768x576.avi | use video as input }"
"{ g gray | false | convert image to gray one or not}"
"{ s scale | 1.0 | resize the image before detect}"
"{ o output | | specify output path when input is images}";
CommandLineParser cmd(argc, argv, keys);
if (cmd.has("help"))
{
cout << "Usage : hog [options]" << endl;
cout << "Available options:" << endl;
cmd.printMessage();
return EXIT_SUCCESS;
}
App app(cmd);
try
{
app.run();
}
catch (const Exception& e)
{
return cout << "error: " << e.what() << endl, 1;
}
catch (const exception& e)
{
return cout << "error: " << e.what() << endl, 1;
}
catch(...)
{
return cout << "unknown exception" << endl, 1;
}
return EXIT_SUCCESS;
}
App::App(CommandLineParser& cmd)
{
cout << "\nControls:\n"
<< "\tESC - exit\n"
<< "\tm - change mode GPU <-> CPU\n"
<< "\tg - convert image to gray or not\n"
<< "\to - save output image once, or switch on/off video save\n"
<< "\t1/q - increase/decrease HOG scale\n"
<< "\t2/w - increase/decrease levels count\n"
<< "\t3/e - increase/decrease HOG group threshold\n"
<< "\t4/r - increase/decrease hit threshold\n"
<< endl;
make_gray = cmd.has("gray");
resize_scale = cmd.get<double>("s");
vdo_source = cmd.get<string>("v");
img_source = cmd.get<string>("i");
output = cmd.get<string>("o");
camera_id = cmd.get<int>("c");
win_width = 48;
win_stride_width = 8;
win_stride_height = 8;
gr_threshold = 8;
nlevels = 13;
hit_threshold = 1.4;
scale = 1.05;
gamma_corr = true;
write_once = false;
cout << "Group threshold: " << gr_threshold << endl;
cout << "Levels number: " << nlevels << endl;
cout << "Win width: " << win_width << endl;
cout << "Win stride: (" << win_stride_width << ", " << win_stride_height << ")\n";
cout << "Hit threshold: " << hit_threshold << endl;
cout << "Gamma correction: " << gamma_corr << endl;
cout << endl;
}
void App::run()
{
running = true;
VideoWriter video_writer;
Size win_size(win_width, win_width * 2);
Size win_stride(win_stride_width, win_stride_height);
// Create HOG descriptors and detectors here
HOGDescriptor hog(win_size, Size(16, 16), Size(8, 8), Size(8, 8), 9, 1, -1,
HOGDescriptor::L2Hys, 0.2, gamma_corr, cv::HOGDescriptor::DEFAULT_NLEVELS);
hog.setSVMDetector( HOGDescriptor::getDaimlerPeopleDetector() );
while (running)
{
VideoCapture vc;
UMat frame;
if (vdo_source!="")
{
vc.open(vdo_source.c_str());
if (!vc.isOpened())
throw runtime_error(string("can't open video file: " + vdo_source));
vc >> frame;
}
else if (camera_id != -1)
{
vc.open(camera_id);
if (!vc.isOpened())
{
stringstream msg;
msg << "can't open camera: " << camera_id;
throw runtime_error(msg.str());
}
vc >> frame;
}
else
{
imread(img_source).copyTo(frame);
if (frame.empty())
throw runtime_error(string("can't open image file: " + img_source));
}
UMat img_aux, img;
Mat img_to_show;
// Iterate over all frames
while (running && !frame.empty())
{
workBegin();
// Change format of the image
if (make_gray) cvtColor(frame, img_aux, COLOR_BGR2GRAY );
else frame.copyTo(img_aux);
// Resize image
if (abs(scale-1.0)>0.001)
{
Size sz((int)((double)img_aux.cols/resize_scale), (int)((double)img_aux.rows/resize_scale));
resize(img_aux, img, sz);
}
else img = img_aux;
img.copyTo(img_to_show);
hog.nlevels = nlevels;
vector<Rect> found;
// Perform HOG classification
hogWorkBegin();
hog.detectMultiScale(img.getMat(ACCESS_READ), found, hit_threshold, win_stride,
Size(0, 0), scale, gr_threshold);
hogWorkEnd();
// Draw positive classified windows
for (size_t i = 0; i < found.size(); i++)
{
Rect r = found[i];
rectangle(img_to_show, r.tl(), r.br(), Scalar(0, 255, 0), 3);
}
putText(img_to_show, "Mode: CPU", Point(5, 25), FONT_HERSHEY_SIMPLEX, 1., Scalar(255, 100, 0), 2);
putText(img_to_show, "FPS (HOG only): " + hogWorkFps(), Point(5, 65), FONT_HERSHEY_SIMPLEX, 1., Scalar(255, 100, 0), 2);
putText(img_to_show, "FPS (total): " + workFps(), Point(5, 105), FONT_HERSHEY_SIMPLEX, 1., Scalar(255, 100, 0), 2);
imshow("opencv_hog", img_to_show);
if (vdo_source!="" || camera_id!=-1) vc >> frame;
workEnd();
if (output!="" && write_once)
{
if (img_source!="") // wirte image
{
write_once = false;
imwrite(output, img_to_show);
}
else //write video
{
if (!video_writer.isOpened())
{
video_writer.open(output, VideoWriter::fourcc('x','v','i','d'), 24,
img_to_show.size(), true);
if (!video_writer.isOpened())
throw std::runtime_error("can't create video writer");
}
if (make_gray) cvtColor(img_to_show, img, COLOR_GRAY2BGR);
else cvtColor(img_to_show, img, COLOR_BGRA2BGR);
video_writer << img.getMat(ACCESS_READ);
}
}
handleKey((char)waitKey(3));
}
}
}
void App::handleKey(char key)
{
switch (key)
{
case 27:
running = false;
break;
case 'm':
case 'M':
ocl::setUseOpenCL(!cv::ocl::useOpenCL());
cout << "Switched to " << (ocl::useOpenCL() ? "OpenCL" : "CPU") << " mode\n";
break;
case 'g':
case 'G':
make_gray = !make_gray;
cout << "Convert image to gray: " << (make_gray ? "YES" : "NO") << endl;
break;
case '1':
scale *= 1.05;
cout << "Scale: " << scale << endl;
break;
case 'q':
case 'Q':
scale /= 1.05;
cout << "Scale: " << scale << endl;
break;
case '2':
nlevels++;
cout << "Levels number: " << nlevels << endl;
break;
case 'w':
case 'W':
nlevels = max(nlevels - 1, 1);
cout << "Levels number: " << nlevels << endl;
break;
case '3':
gr_threshold++;
cout << "Group threshold: " << gr_threshold << endl;
break;
case 'e':
case 'E':
gr_threshold = max(0, gr_threshold - 1);
cout << "Group threshold: " << gr_threshold << endl;
break;
case '4':
hit_threshold+=0.25;
cout << "Hit threshold: " << hit_threshold << endl;
break;
case 'r':
case 'R':
hit_threshold = max(0.0, hit_threshold - 0.25);
cout << "Hit threshold: " << hit_threshold << endl;
break;
case 'c':
case 'C':
gamma_corr = !gamma_corr;
cout << "Gamma correction: " << gamma_corr << endl;
break;
case 'o':
case 'O':
write_once = !write_once;
break;
}
}
inline void App::hogWorkBegin()
{
hog_work_begin = getTickCount();
}
inline void App::hogWorkEnd()
{
int64 delta = getTickCount() - hog_work_begin;
double freq = getTickFrequency();
hog_work_fps = freq / delta;
}
inline string App::hogWorkFps() const
{
stringstream ss;
ss << hog_work_fps;
return ss.str();
}
inline void App::workBegin()
{
work_begin = getTickCount();
}
inline void App::workEnd()
{
int64 delta = getTickCount() - work_begin;
double freq = getTickFrequency();
work_fps = freq / delta;
}
inline string App::workFps() const
{
stringstream ss;
ss << work_fps;
return ss.str();
}

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samples/tapi/morphology.cpp Normal file
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#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <stdlib.h>
#include <stdio.h>
#include "opencv2/core/ocl.hpp"
using namespace cv;
static void help()
{
printf("\nShow off image morphology: erosion, dialation, open and close\n"
"Call:\n morphology2 [image]\n"
"This program also shows use of rect, elipse and cross kernels\n\n");
printf( "Hot keys: \n"
"\tESC - quit the program\n"
"\tr - use rectangle structuring element\n"
"\te - use elliptic structuring element\n"
"\tc - use cross-shaped structuring element\n"
"\tSPACE - loop through all the options\n"
"\tm - switch openCL mode support\n");
}
UMat src, dst;
int element_shape = MORPH_RECT;
//the address of variable which receives trackbar position update
int max_iters = 10;
int open_close_pos = 0;
int erode_dilate_pos = 0;
// callback function for open/close trackbar
static void OpenClose(int, void*)
{
int n = open_close_pos - max_iters;
int an = n > 0 ? n : -n;
Mat element = getStructuringElement(element_shape, Size(an*2+1, an*2+1), Point(an, an) );
if( n < 0 )
morphologyEx(src, dst, MORPH_OPEN, element);
else
morphologyEx(src, dst, MORPH_CLOSE, element);
imshow("Open/Close",dst);
}
// callback function for erode/dilate trackbar
static void ErodeDilate(int, void*)
{
int n = erode_dilate_pos - max_iters;
int an = n > 0 ? n : -n;
Mat element = getStructuringElement(element_shape, Size(an*2+1, an*2+1), Point(an, an) );
if( n < 0 )
erode(src, dst, element);
else
dilate(src, dst, element);
imshow("Erode/Dilate",dst);
}
int main( int argc, char** argv )
{
char* filename = argc == 2 ? argv[1] : (char*)"baboon.jpg";
imread(filename,1).copyTo(src);
if( src.u == 0 )
return -1;
help();
//create windows for output images
namedWindow("Open/Close",1);
namedWindow("Erode/Dilate",1);
open_close_pos = erode_dilate_pos = max_iters;
createTrackbar("iterations", "Open/Close",&open_close_pos,max_iters*2+1,OpenClose);
createTrackbar("iterations", "Erode/Dilate",&erode_dilate_pos,max_iters*2+1,ErodeDilate);
for(;;)
{
int c;
OpenClose(open_close_pos, 0);
ErodeDilate(erode_dilate_pos, 0);
c = waitKey(0);
if( (char)c == 27 )
break;
if( (char)c == 'e' )
element_shape = MORPH_ELLIPSE;
else if( (char)c == 'r' )
element_shape = MORPH_RECT;
else if( (char)c == 'c' )
element_shape = MORPH_CROSS;
else if( (char)c == ' ' )
element_shape = (element_shape + 1) % 3;
else if( (char)c == 'm' )
{
cv::ocl::setUseOpenCL(!cv::ocl::useOpenCL());
printf("OpenCL is %s\n", ocl::useOpenCL() ? "enabled" : "disabled");
}
}
return 0;
}

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samples/tapi/pyrlk_optical_flow.cpp Normal file
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#include <iostream>
#include <vector>
#include <iomanip>
#include "opencv2/core/utility.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/core/ocl.hpp"
#include "opencv2/video/video.hpp"
using namespace std;
using namespace cv;
typedef unsigned char uchar;
#define LOOP_NUM 10
int64 work_begin = 0;
int64 work_end = 0;
static void workBegin()
{
work_begin = getTickCount();
}
static void workEnd()
{
work_end += (getTickCount() - work_begin);
}
static double getTime()
{
return work_end * 1000. / getTickFrequency();
}
static void drawArrows(UMat& _frame, const vector<Point2f>& prevPts, const vector<Point2f>& nextPts, const vector<uchar>& status,
Scalar line_color = Scalar(0, 0, 255))
{
Mat frame = _frame.getMat(ACCESS_WRITE);
for (size_t i = 0; i < prevPts.size(); ++i)
{
if (status[i])
{
int line_thickness = 1;
Point p = prevPts[i];
Point q = nextPts[i];
double angle = atan2((double) p.y - q.y, (double) p.x - q.x);
double hypotenuse = sqrt( (double)(p.y - q.y)*(p.y - q.y) + (double)(p.x - q.x)*(p.x - q.x) );
if (hypotenuse < 1.0)
continue;
// Here we lengthen the arrow by a factor of three.
q.x = (int) (p.x - 3 * hypotenuse * cos(angle));
q.y = (int) (p.y - 3 * hypotenuse * sin(angle));
// Now we draw the main line of the arrow.
line(frame, p, q, line_color, line_thickness);
// Now draw the tips of the arrow. I do some scaling so that the
// tips look proportional to the main line of the arrow.
p.x = (int) (q.x + 9 * cos(angle + CV_PI / 4));
p.y = (int) (q.y + 9 * sin(angle + CV_PI / 4));
line(frame, p, q, line_color, line_thickness);
p.x = (int) (q.x + 9 * cos(angle - CV_PI / 4));
p.y = (int) (q.y + 9 * sin(angle - CV_PI / 4));
line(frame, p, q, line_color, line_thickness);
}
}
}
int main(int argc, const char* argv[])
{
const char* keys =
"{ h help | false | print help message }"
"{ l left | | specify left image }"
"{ r right | | specify right image }"
"{ c camera | 0 | enable camera capturing }"
"{ v video | | use video as input }"
"{ o output | pyrlk_output.jpg| specify output save path when input is images }"
"{ points | 1000 | specify points count [GoodFeatureToTrack] }"
"{ min_dist | 0 | specify minimal distance between points [GoodFeatureToTrack] }"
"{ m cpu_mode | false | run without OpenCL }";
CommandLineParser cmd(argc, argv, keys);
if (cmd.has("help"))
{
cout << "Usage: pyrlk_optical_flow [options]" << endl;
cout << "Available options:" << endl;
cmd.printMessage();
return EXIT_SUCCESS;
}
bool defaultPicturesFail = true;
string fname0 = cmd.get<string>("left");
string fname1 = cmd.get<string>("right");
string vdofile = cmd.get<string>("video");
string outfile = cmd.get<string>("output");
int points = cmd.get<int>("points");
double minDist = cmd.get<double>("min_dist");
int inputName = cmd.get<int>("c");
UMat frame0;
imread(fname0, cv::IMREAD_GRAYSCALE).copyTo(frame0);
UMat frame1;
imread(fname1, cv::IMREAD_GRAYSCALE).copyTo(frame1);
vector<cv::Point2f> pts(points);
vector<cv::Point2f> nextPts(points);
vector<unsigned char> status(points);
vector<float> err;
cout << "Points count : " << points << endl << endl;
if (frame0.empty() || frame1.empty())
{
VideoCapture capture;
UMat frame, frameCopy;
UMat frame0Gray, frame1Gray;
UMat ptr0, ptr1;
if(vdofile.empty())
capture.open( inputName );
else
capture.open(vdofile.c_str());
int c = inputName ;
if(!capture.isOpened())
{
if(vdofile.empty())
cout << "Capture from CAM " << c << " didn't work" << endl;
else
cout << "Capture from file " << vdofile << " failed" <<endl;
if (defaultPicturesFail)
return EXIT_FAILURE;
goto nocamera;
}
cout << "In capture ..." << endl;
for(int i = 0;; i++)
{
if( !capture.read(frame) )
break;
if (i == 0)
{
frame.copyTo( frame0 );
cvtColor(frame0, frame0Gray, COLOR_BGR2GRAY);
}
else
{
if (i%2 == 1)
{
frame.copyTo(frame1);
cvtColor(frame1, frame1Gray, COLOR_BGR2GRAY);
ptr0 = frame0Gray;
ptr1 = frame1Gray;
}
else
{
frame.copyTo(frame0);
cvtColor(frame0, frame0Gray, COLOR_BGR2GRAY);
ptr0 = frame1Gray;
ptr1 = frame0Gray;
}
pts.clear();
goodFeaturesToTrack(ptr0, pts, points, 0.01, 0.0);
if(pts.size() == 0)
continue;
calcOpticalFlowPyrLK(ptr0, ptr1, pts, nextPts, status, err);
if (i%2 == 1)
frame1.copyTo(frameCopy);
else
frame0.copyTo(frameCopy);
drawArrows(frameCopy, pts, nextPts, status, Scalar(255, 0, 0));
imshow("PyrLK [Sparse]", frameCopy);
}
char key = (char)waitKey(10);
if (key == 27)
break;
else if (key == 'm' || key == 'M')
{
ocl::setUseOpenCL(!cv::ocl::useOpenCL());
cout << "Switched to " << (ocl::useOpenCL() ? "OpenCL" : "CPU") << " mode\n";
}
}
capture.release();
}
else
{
nocamera:
if (cmd.has("cpu_mode"))
{
ocl::setUseOpenCL(false);
std::cout << "OpenCL was disabled" << std::endl;
}
for(int i = 0; i <= LOOP_NUM; i ++)
{
cout << "loop" << i << endl;
if (i > 0) workBegin();
goodFeaturesToTrack(frame0, pts, points, 0.01, minDist);
calcOpticalFlowPyrLK(frame0, frame1, pts, nextPts, status, err);
if (i > 0 && i <= LOOP_NUM)
workEnd();
if (i == LOOP_NUM)
{
cout << "average time (noCamera) : ";
cout << getTime() / LOOP_NUM << " ms" << endl;
drawArrows(frame0, pts, nextPts, status, Scalar(255, 0, 0));
imshow("PyrLK [Sparse]", frame0);
imwrite(outfile, frame0);
}
}
}
waitKey();
return EXIT_SUCCESS;
}

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// The "Square Detector" program.
// It loads several images sequentially and tries to find squares in
// each image
#include "opencv2/core.hpp"
#include "opencv2/core/ocl.hpp"
#include "opencv2/core/utility.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <iostream>
#include <string.h>
using namespace cv;
using namespace std;
int thresh = 50, N = 11;
const char* wndname = "Square Detection Demo";
// helper function:
// finds a cosine of angle between vectors
// from pt0->pt1 and from pt0->pt2
static double angle( Point pt1, Point pt2, Point pt0 )
{
double dx1 = pt1.x - pt0.x;
double dy1 = pt1.y - pt0.y;
double dx2 = pt2.x - pt0.x;
double dy2 = pt2.y - pt0.y;
return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10);
}
// returns sequence of squares detected on the image.
// the sequence is stored in the specified memory storage
static void findSquares( const UMat& image, vector<vector<Point> >& squares )
{
squares.clear();
UMat pyr, timg, gray0(image.size(), CV_8U), gray;
// down-scale and upscale the image to filter out the noise
pyrDown(image, pyr, Size(image.cols/2, image.rows/2));
pyrUp(pyr, timg, image.size());
vector<vector<Point> > contours;
// find squares in every color plane of the image
for( int c = 0; c < 3; c++ )
{
int ch[] = {c, 0};
mixChannels(timg, gray0, ch, 1);
// try several threshold levels
for( int l = 0; l < N; l++ )
{
// hack: use Canny instead of zero threshold level.
// Canny helps to catch squares with gradient shading
if( l == 0 )
{
// apply Canny. Take the upper threshold from slider
// and set the lower to 0 (which forces edges merging)
Canny(gray0, gray, 0, thresh, 5);
// dilate canny output to remove potential
// holes between edge segments
dilate(gray, gray, UMat(), Point(-1,-1));
}
else
{
// apply threshold if l!=0:
// tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0
cv::threshold(gray0, gray, (l+1)*255/N, 255, THRESH_BINARY);
}
// find contours and store them all as a list
findContours(gray, contours, RETR_LIST, CHAIN_APPROX_SIMPLE);
vector<Point> approx;
// test each contour
for( size_t i = 0; i < contours.size(); i++ )
{
// approximate contour with accuracy proportional
// to the contour perimeter
approxPolyDP(Mat(contours[i]), approx, arcLength(Mat(contours[i]), true)*0.02, true);
// square contours should have 4 vertices after approximation
// relatively large area (to filter out noisy contours)
// and be convex.
// Note: absolute value of an area is used because
// area may be positive or negative - in accordance with the
// contour orientation
if( approx.size() == 4 &&
fabs(contourArea(Mat(approx))) > 1000 &&
isContourConvex(Mat(approx)) )
{
double maxCosine = 0;
for( int j = 2; j < 5; j++ )
{
// find the maximum cosine of the angle between joint edges
double cosine = fabs(angle(approx[j%4], approx[j-2], approx[j-1]));
maxCosine = MAX(maxCosine, cosine);
}
// if cosines of all angles are small
// (all angles are ~90 degree) then write quandrange
// vertices to resultant sequence
if( maxCosine < 0.3 )
squares.push_back(approx);
}
}
}
}
}
// the function draws all the squares in the image
static void drawSquares( UMat& _image, const vector<vector<Point> >& squares )
{
Mat image = _image.getMat(ACCESS_WRITE);
for( size_t i = 0; i < squares.size(); i++ )
{
const Point* p = &squares[i][0];
int n = (int)squares[i].size();
polylines(image, &p, &n, 1, true, Scalar(0,255,0), 3, LINE_AA);
}
}
// draw both pure-C++ and ocl square results onto a single image
static UMat drawSquaresBoth( const UMat& image,
const vector<vector<Point> >& sqs)
{
UMat imgToShow(Size(image.cols, image.rows), image.type());
image.copyTo(imgToShow);
drawSquares(imgToShow, sqs);
return imgToShow;
}
int main(int argc, char** argv)
{
const char* keys =
"{ i input | | specify input image }"
"{ o output | squares_output.jpg | specify output save path}"
"{ h help | false | print help message }"
"{ m cpu_mode | false | run without OpenCL }";
CommandLineParser cmd(argc, argv, keys);
if(cmd.has("help"))
{
cout << "Usage : squares [options]" << endl;
cout << "Available options:" << endl;
cmd.printMessage();
return EXIT_SUCCESS;
}
if (cmd.has("cpu_mode"))
{
ocl::setUseOpenCL(false);
std::cout << "OpenCL was disabled" << std::endl;
}
string inputName = cmd.get<string>("i");
string outfile = cmd.get<string>("o");
int iterations = 10;
namedWindow( wndname, WINDOW_AUTOSIZE );
vector<vector<Point> > squares;
UMat image;
imread(inputName, 1).copyTo(image);
if( image.empty() )
{
cout << "Couldn't load " << inputName << endl;
return EXIT_FAILURE;
}
int j = iterations;
int64 t_cpp = 0;
//warm-ups
cout << "warming up ..." << endl;
findSquares(image, squares);
do
{
int64 t_start = cv::getTickCount();
findSquares(image, squares);
t_cpp += cv::getTickCount() - t_start;
t_start = cv::getTickCount();
cout << "run loop: " << j << endl;
}
while(--j);
cout << "average time: " << 1000.0f * (double)t_cpp / getTickFrequency() / iterations << "ms" << endl;
UMat result = drawSquaresBoth(image, squares);
imshow(wndname, result);
imwrite(outfile, result);
waitKey(0);
return EXIT_SUCCESS;
}

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#include <iostream>
#include <stdio.h>
#include "opencv2/core/core.hpp"
#include "opencv2/core/utility.hpp"
#include "opencv2/core/ocl.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/features2d.hpp"
#include "opencv2/calib3d.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/nonfree.hpp"
using namespace cv;
const int LOOP_NUM = 10;
const int GOOD_PTS_MAX = 50;
const float GOOD_PORTION = 0.15f;
int64 work_begin = 0;
int64 work_end = 0;
static void workBegin()
{
work_begin = getTickCount();
}
static void workEnd()
{
work_end = getTickCount() - work_begin;
}
static double getTime()
{
return work_end /((double)getTickFrequency() * 1000.);
}
template<class KPDetector>
struct SURFDetector
{
KPDetector surf;
SURFDetector(double hessian = 800.0)
:surf(hessian)
{
}
template<class T>
void operator()(const T& in, const T& mask, std::vector<cv::KeyPoint>& pts, T& descriptors, bool useProvided = false)
{
surf(in, mask, pts, descriptors, useProvided);
}
};
template<class KPMatcher>
struct SURFMatcher
{
KPMatcher matcher;
template<class T>
void match(const T& in1, const T& in2, std::vector<cv::DMatch>& matches)
{
matcher.match(in1, in2, matches);
}
};
static Mat drawGoodMatches(
const Mat& img1,
const Mat& img2,
const std::vector<KeyPoint>& keypoints1,
const std::vector<KeyPoint>& keypoints2,
std::vector<DMatch>& matches,
std::vector<Point2f>& scene_corners_
)
{
//-- Sort matches and preserve top 10% matches
std::sort(matches.begin(), matches.end());
std::vector< DMatch > good_matches;
double minDist = matches.front().distance;
double maxDist = matches.back().distance;
const int ptsPairs = std::min(GOOD_PTS_MAX, (int)(matches.size() * GOOD_PORTION));
for( int i = 0; i < ptsPairs; i++ )
{
good_matches.push_back( matches[i] );
}
std::cout << "\nMax distance: " << maxDist << std::endl;
std::cout << "Min distance: " << minDist << std::endl;
std::cout << "Calculating homography using " << ptsPairs << " point pairs." << std::endl;
// drawing the results
Mat img_matches;
drawMatches( img1, keypoints1, img2, keypoints2,
good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
std::vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
//-- Localize the object
std::vector<Point2f> obj;
std::vector<Point2f> scene;
for( size_t i = 0; i < good_matches.size(); i++ )
{
//-- Get the keypoints from the good matches
obj.push_back( keypoints1[ good_matches[i].queryIdx ].pt );
scene.push_back( keypoints2[ good_matches[i].trainIdx ].pt );
}
//-- Get the corners from the image_1 ( the object to be "detected" )
std::vector<Point2f> obj_corners(4);
obj_corners[0] = Point(0,0);
obj_corners[1] = Point( img1.cols, 0 );
obj_corners[2] = Point( img1.cols, img1.rows );
obj_corners[3] = Point( 0, img1.rows );
std::vector<Point2f> scene_corners(4);
Mat H = findHomography( obj, scene, RANSAC );
perspectiveTransform( obj_corners, scene_corners, H);
scene_corners_ = scene_corners;
//-- Draw lines between the corners (the mapped object in the scene - image_2 )
line( img_matches,
scene_corners[0] + Point2f( (float)img1.cols, 0), scene_corners[1] + Point2f( (float)img1.cols, 0),
Scalar( 0, 255, 0), 2, LINE_AA );
line( img_matches,
scene_corners[1] + Point2f( (float)img1.cols, 0), scene_corners[2] + Point2f( (float)img1.cols, 0),
Scalar( 0, 255, 0), 2, LINE_AA );
line( img_matches,
scene_corners[2] + Point2f( (float)img1.cols, 0), scene_corners[3] + Point2f( (float)img1.cols, 0),
Scalar( 0, 255, 0), 2, LINE_AA );
line( img_matches,
scene_corners[3] + Point2f( (float)img1.cols, 0), scene_corners[0] + Point2f( (float)img1.cols, 0),
Scalar( 0, 255, 0), 2, LINE_AA );
return img_matches;
}
////////////////////////////////////////////////////
// This program demonstrates the usage of SURF_OCL.
// use cpu findHomography interface to calculate the transformation matrix
int main(int argc, char* argv[])
{
const char* keys =
"{ h help | false | print help message }"
"{ l left | | specify left image }"
"{ r right | | specify right image }"
"{ o output | SURF_output.jpg | specify output save path }"
"{ m cpu_mode | false | run without OpenCL }";
CommandLineParser cmd(argc, argv, keys);
if (cmd.has("help"))
{
std::cout << "Usage: surf_matcher [options]" << std::endl;
std::cout << "Available options:" << std::endl;
cmd.printMessage();
return EXIT_SUCCESS;
}
if (cmd.has("cpu_mode"))
{
ocl::setUseOpenCL(false);
std::cout << "OpenCL was disabled" << std::endl;
}
UMat img1, img2;
std::string outpath = cmd.get<std::string>("o");
imread(cmd.get<std::string>("l"), IMREAD_GRAYSCALE).copyTo(img1);
CV_Assert(!img1.empty());
imread(cmd.get<std::string>("r"), IMREAD_GRAYSCALE).copyTo(img2);
CV_Assert(!img2.empty());
double surf_time = 0.;
//declare input/output
std::vector<KeyPoint> keypoints1, keypoints2;
std::vector<DMatch> matches;
UMat _descriptors1, _descriptors2;
Mat descriptors1 = _descriptors1.getMat(ACCESS_RW),
descriptors2 = _descriptors2.getMat(ACCESS_RW);
//instantiate detectors/matchers
SURFDetector<SURF> surf;
SURFMatcher<BFMatcher> matcher;
//-- start of timing section
for (int i = 0; i <= LOOP_NUM; i++)
{
if(i == 1) workBegin();
surf(img1.getMat(ACCESS_READ), Mat(), keypoints1, descriptors1);
surf(img2.getMat(ACCESS_READ), Mat(), keypoints2, descriptors2);
matcher.match(descriptors1, descriptors2, matches);
}
workEnd();
std::cout << "FOUND " << keypoints1.size() << " keypoints on first image" << std::endl;
std::cout << "FOUND " << keypoints2.size() << " keypoints on second image" << std::endl;
surf_time = getTime();
std::cout << "SURF run time: " << surf_time / LOOP_NUM << " ms" << std::endl<<"\n";
std::vector<Point2f> corner;
Mat img_matches = drawGoodMatches(img1.getMat(ACCESS_READ), img2.getMat(ACCESS_READ), keypoints1, keypoints2, matches, corner);
//-- Show detected matches
namedWindow("surf matches", 0);
imshow("surf matches", img_matches);
imwrite(outpath, img_matches);
waitKey(0);
return EXIT_SUCCESS;
}

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#include <iostream>
#include <vector>
#include <iomanip>
#include "opencv2/core/ocl.hpp"
#include "opencv2/core/utility.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/video/video.hpp"
using namespace std;
using namespace cv;
typedef unsigned char uchar;
#define LOOP_NUM 10
int64 work_begin = 0;
int64 work_end = 0;
static void workBegin()
{
work_begin = getTickCount();
}
static void workEnd()
{
work_end += (getTickCount() - work_begin);
}
static double getTime()
{
return work_end * 1000. / getTickFrequency();
}
template <typename T> inline T clamp (T x, T a, T b)
{
return ((x) > (a) ? ((x) < (b) ? (x) : (b)) : (a));
}
template <typename T> inline T mapValue(T x, T a, T b, T c, T d)
{
x = clamp(x, a, b);
return c + (d - c) * (x - a) / (b - a);
}
static void getFlowField(const Mat& u, const Mat& v, Mat& flowField)
{
float maxDisplacement = 1.0f;
for (int i = 0; i < u.rows; ++i)
{
const float* ptr_u = u.ptr<float>(i);
const float* ptr_v = v.ptr<float>(i);
for (int j = 0; j < u.cols; ++j)
{
float d = max(fabsf(ptr_u[j]), fabsf(ptr_v[j]));
if (d > maxDisplacement)
maxDisplacement = d;
}
}
flowField.create(u.size(), CV_8UC4);
for (int i = 0; i < flowField.rows; ++i)
{
const float* ptr_u = u.ptr<float>(i);
const float* ptr_v = v.ptr<float>(i);
Vec4b* row = flowField.ptr<Vec4b>(i);
for (int j = 0; j < flowField.cols; ++j)
{
row[j][0] = 0;
row[j][1] = static_cast<unsigned char> (mapValue (-ptr_v[j], -maxDisplacement, maxDisplacement, 0.0f, 255.0f));
row[j][2] = static_cast<unsigned char> (mapValue ( ptr_u[j], -maxDisplacement, maxDisplacement, 0.0f, 255.0f));
row[j][3] = 255;
}
}
}
int main(int argc, const char* argv[])
{
const char* keys =
"{ h help | false | print help message }"
"{ l left | | specify left image }"
"{ r right | | specify right image }"
"{ o output | tvl1_output.jpg | specify output save path }"
"{ c camera | 0 | enable camera capturing }"
"{ m cpu_mode | false | run without OpenCL }"
"{ v video | | use video as input }";
CommandLineParser cmd(argc, argv, keys);
if (cmd.has("help"))
{
cout << "Usage: pyrlk_optical_flow [options]" << endl;
cout << "Available options:" << endl;
cmd.printMessage();
return EXIT_SUCCESS;
}
string fname0 = cmd.get<string>("l");
string fname1 = cmd.get<string>("r");
string vdofile = cmd.get<string>("v");
string outpath = cmd.get<string>("o");
bool useCPU = cmd.get<bool>("s");
bool useCamera = cmd.get<bool>("c");
int inputName = cmd.get<int>("c");
UMat frame0, frame1;
imread(fname0, cv::IMREAD_GRAYSCALE).copyTo(frame0);
imread(fname1, cv::IMREAD_GRAYSCALE).copyTo(frame1);
cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1();
UMat flow;
Mat show_flow;
vector<UMat> flow_vec;
if (frame0.empty() || frame1.empty())
useCamera = true;
if (useCamera)
{
VideoCapture capture;
UMat frame, frameCopy;
UMat frame0Gray, frame1Gray;
UMat ptr0, ptr1;
if(vdofile.empty())
capture.open( inputName );
else
capture.open(vdofile.c_str());
if(!capture.isOpened())
{
if(vdofile.empty())
cout << "Capture from CAM " << inputName << " didn't work" << endl;
else
cout << "Capture from file " << vdofile << " failed" <<endl;
goto nocamera;
}
cout << "In capture ..." << endl;
for(int i = 0;; i++)
{
if( !capture.read(frame) )
break;
if (i == 0)
{
frame.copyTo( frame0 );
cvtColor(frame0, frame0Gray, COLOR_BGR2GRAY);
}
else
{
if (i%2 == 1)
{
frame.copyTo(frame1);
cvtColor(frame1, frame1Gray, COLOR_BGR2GRAY);
ptr0 = frame0Gray;
ptr1 = frame1Gray;
}
else
{
frame.copyTo(frame0);
cvtColor(frame0, frame0Gray, COLOR_BGR2GRAY);
ptr0 = frame1Gray;
ptr1 = frame0Gray;
}
alg->calc(ptr0, ptr1, flow);
split(flow, flow_vec);
if (i%2 == 1)
frame1.copyTo(frameCopy);
else
frame0.copyTo(frameCopy);
getFlowField(flow_vec[0].getMat(ACCESS_READ), flow_vec[1].getMat(ACCESS_READ), show_flow);
imshow("tvl1 optical flow field", show_flow);
}
char key = (char)waitKey(10);
if (key == 27)
break;
else if (key == 'm' || key == 'M')
{
ocl::setUseOpenCL(!cv::ocl::useOpenCL());
cout << "Switched to " << (ocl::useOpenCL() ? "OpenCL" : "CPU") << " mode\n";
}
}
capture.release();
}
else
{
nocamera:
if (cmd.has("cpu_mode"))
{
ocl::setUseOpenCL(false);
std::cout << "OpenCL was disabled" << std::endl;
}
for(int i = 0; i <= LOOP_NUM; i ++)
{
cout << "loop" << i << endl;
if (i > 0) workBegin();
alg->calc(frame0, frame1, flow);
split(flow, flow_vec);
if (i > 0 && i <= LOOP_NUM)
workEnd();
if (i == LOOP_NUM)
{
if (useCPU)
cout << "average CPU time (noCamera) : ";
else
cout << "average GPU time (noCamera) : ";
cout << getTime() / LOOP_NUM << " ms" << endl;
getFlowField(flow_vec[0].getMat(ACCESS_READ), flow_vec[1].getMat(ACCESS_READ), show_flow);
imshow("PyrLK [Sparse]", show_flow);
imwrite(outpath, show_flow);
}
}
}
waitKey();
return EXIT_SUCCESS;
}