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Commit 6bb9342a authored by Vadim Pisarevsky's avatar Vadim Pisarevsky Committed by OpenCV Buildbot
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Merge pull request #918 from bitwangyaoyao:2.4_samples

parents 5a4efe8b fad96b95
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samples/ocl/facedetect.cpp
View file @ 6bb9342a
//This sample is inherited from facedetect.cpp in smaple/c
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
......@@ -9,78 +7,84 @@
using namespace std;
using namespace cv;
#define LOOP_NUM 10
const static Scalar colors[] = { CV_RGB(0,0,255),
CV_RGB(0,128,255),
CV_RGB(0,255,255),
CV_RGB(0,255,0),
CV_RGB(255,128,0),
CV_RGB(255,255,0),
CV_RGB(255,0,0),
CV_RGB(255,0,255)} ;
static void help()
int64 work_begin = 0;
int64 work_end = 0;
static void workBegin()
{
work_begin = getTickCount();
}
static void workEnd()
{
cout << "\nThis program demonstrates the cascade recognizer.\n"
"This classifier can recognize many ~rigid objects, it's most known use is for faces.\n"
"Usage:\n"
"./facedetect [--cascade=<cascade_path> this is the primary trained classifier such as frontal face]\n"
" [--scale=<image scale greater or equal to 1, try 1.3 for example>\n"
" [filename|camera_index]\n\n"
"see facedetect.cmd for one call:\n"
"./facedetect --cascade=\"../../data/haarcascades/haarcascade_frontalface_alt.xml\" --scale=1.3 \n"
"Hit any key to quit.\n"
"Using OpenCV version " << CV_VERSION << "\n" << endl;
work_end += (getTickCount() - work_begin);
}
struct getRect { Rect operator ()(const CvAvgComp& e) const { return e.rect; } };
void detectAndDraw( Mat& img,
cv::ocl::OclCascadeClassifier& cascade, CascadeClassifier& nestedCascade,
double scale);
static double getTime(){
return work_end /((double)cvGetTickFrequency() * 1000.);
}
void detect( Mat& img, vector<Rect>& faces,
cv::ocl::OclCascadeClassifierBuf& cascade,
double scale, bool calTime);
String cascadeName = "../../../data/haarcascades/haarcascade_frontalface_alt.xml";
void detectCPU( Mat& img, vector<Rect>& faces,
CascadeClassifier& cascade,
double scale, bool calTime);
void Draw(Mat& img, vector<Rect>& faces, double scale);
// 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);
int main( int argc, const char** argv )
{
CvCapture* capture = 0;
Mat frame, frameCopy, image;
const String scaleOpt = "--scale=";
size_t scaleOptLen = scaleOpt.length();
const String cascadeOpt = "--cascade=";
size_t cascadeOptLen = cascadeOpt.length();
String inputName;
help();
cv::ocl::OclCascadeClassifier cascade;
CascadeClassifier nestedCascade;
double scale = 1;
for( int i = 1; i < argc; i++ )
const char* keys =
"{ h | help | false | print help message }"
"{ i | input | | specify input image }"
"{ t | template | ../../../data/haarcascades/haarcascade_frontalface_alt.xml | specify template file }"
"{ c | scale | 1.0 | scale image }"
"{ s | use_cpu | false | use cpu or gpu to process the image }";
CommandLineParser cmd(argc, argv, keys);
if (cmd.get<bool>("help"))
{
cout << "Processing " << i << " " << argv[i] << endl;
if( cascadeOpt.compare( 0, cascadeOptLen, argv[i], cascadeOptLen ) == 0 )
{
cascadeName.assign( argv[i] + cascadeOptLen );
cout << " from which we have cascadeName= " << cascadeName << endl;
}
else if( scaleOpt.compare( 0, scaleOptLen, argv[i], scaleOptLen ) == 0 )
{
if( !sscanf( argv[i] + scaleOpt.length(), "%lf", &scale ) || scale < 1 )
scale = 1;
cout << " from which we read scale = " << scale << endl;
}
else if( argv[i][0] == '-' )
{
cerr << "WARNING: Unknown option %s" << argv[i] << endl;
}
else
inputName.assign( argv[i] );
cout << "Avaible options:" << endl;
cmd.printParams();
return 0;
}
CvCapture* capture = 0;
Mat frame, frameCopy, image;
if( !cascade.load( cascadeName ) )
bool useCPU = cmd.get<bool>("s");
string inputName = cmd.get<string>("i");
string cascadeName = cmd.get<string>("t");
double scale = cmd.get<double>("c");
cv::ocl::OclCascadeClassifierBuf cascade;
CascadeClassifier cpu_cascade;
if( !cascade.load( cascadeName ) || !cpu_cascade.load(cascadeName) )
{
cerr << "ERROR: Could not load classifier cascade" << endl;
cerr << "Usage: facedetect [--cascade=<cascade_path>]\n"
" [--scale[=<image scale>\n"
" [filename|camera_index]\n" << endl ;
return -1;
}
if( inputName.empty() || (isdigit(inputName.c_str()[0]) && inputName.c_str()[1] == '\0') )
if( inputName.empty() )
{
capture = cvCaptureFromCAM( inputName.empty() ? 0 : inputName.c_str()[0] - '0' );
int c = inputName.empty() ? 0 : inputName.c_str()[0] - '0' ;
if(!capture) cout << "Capture from CAM " << c << " didn't work" << endl;
capture = cvCaptureFromCAM(0);
if(!capture)
cout << "Capture from CAM 0 didn't work" << endl;
}
else if( inputName.size() )
{
......@@ -88,26 +92,30 @@ int main( int argc, const char** argv )
if( image.empty() )
{
capture = cvCaptureFromAVI( inputName.c_str() );
if(!capture) cout << "Capture from AVI didn't work" << endl;
if(!capture)
cout << "Capture from AVI didn't work" << endl;
return -1;
}
}
else
{
image = imread( "lena.jpg", 1 );
if(image.empty()) cout << "Couldn't read lena.jpg" << endl;
if(image.empty())
cout << "Couldn't read lena.jpg" << endl;
return -1;
}
cvNamedWindow( "result", 1 );
std::vector<cv::ocl::Info> oclinfo;
int devnums = cv::ocl::getDevice(oclinfo);
if(devnums<1)
if( devnums < 1 )
{
std::cout << "no device found\n";
return -1;
}
//if you want to use undefault device, set it here
//setDevice(oclinfo[0]);
//setBinpath(CLBINPATH);
ocl::setBinpath("./");
if( capture )
{
cout << "In capture ..." << endl;
......@@ -115,15 +123,20 @@ int main( int argc, const char** argv )
{
IplImage* iplImg = cvQueryFrame( capture );
frame = iplImg;
vector<Rect> faces;
if( frame.empty() )
break;
if( iplImg->origin == IPL_ORIGIN_TL )
frame.copyTo( frameCopy );
else
flip( frame, frameCopy, 0 );
detectAndDraw( frameCopy, cascade, nestedCascade, scale );
if(useCPU){
detectCPU(frameCopy, faces, cpu_cascade, scale, false);
}
else{
detect(frameCopy, faces, cascade, scale, false);
}
Draw(frameCopy, faces, scale);
if( waitKey( 10 ) >= 0 )
goto _cleanup_;
}
......@@ -136,42 +149,34 @@ _cleanup_:
else
{
cout << "In image read" << endl;
if( !image.empty() )
{
detectAndDraw( image, cascade, nestedCascade, scale );
waitKey(0);
}
else if( !inputName.empty() )
vector<Rect> faces;
vector<Rect> ref_rst;
double accuracy = 0.;
for(int i = 0; i <= LOOP_NUM;i ++)
{
/* assume it is a text file containing the
list of the image filenames to be processed - one per line */
FILE* f = fopen( inputName.c_str(), "rt" );
if( f )
cout << "loop" << i << endl;
if(useCPU){
detectCPU(image, faces, cpu_cascade, scale, i==0?false:true);
}
else{
detect(image, faces, cascade, scale, i==0?false:true);
if(i == 0){
detectCPU(image, ref_rst, cpu_cascade, scale, false);
accuracy = checkRectSimilarity(image.size(), ref_rst, faces);
}
}
if (i == LOOP_NUM)
{
char buf[1000+1];
while( fgets( buf, 1000, f ) )
{
int len = (int)strlen(buf), c;
while( len > 0 && isspace(buf[len-1]) )
len--;
buf[len] = '\0';
cout << "file " << buf << endl;
image = imread( buf, 1 );
if( !image.empty() )
{
detectAndDraw( image, cascade, nestedCascade, scale );
c = waitKey(0);
if( c == 27 || c == 'q' || c == 'Q' )
break;
}
else
{
cerr << "Aw snap, couldn't read image " << buf << endl;
}
}
fclose(f);
if (useCPU)
cout << "average CPU time (noCamera) : ";
else
cout << "average GPU time (noCamera) : ";
cout << getTime() / LOOP_NUM << " ms" << endl;
cout << "accuracy value: " << accuracy <<endl;
}
}
Draw(image, faces, scale);
waitKey(0);
}
cvDestroyWindow("result");
......@@ -179,44 +184,44 @@ _cleanup_:
return 0;
}
void detectAndDraw( Mat& img,
cv::ocl::OclCascadeClassifier& cascade, CascadeClassifier&,
double scale)
void detect( Mat& img, vector<Rect>& faces,
cv::ocl::OclCascadeClassifierBuf& cascade,
double scale, bool calTime)
{
int i = 0;
double t = 0;
vector<Rect> faces;
const static Scalar colors[] = { CV_RGB(0,0,255),
CV_RGB(0,128,255),
CV_RGB(0,255,255),
CV_RGB(0,255,0),
CV_RGB(255,128,0),
CV_RGB(255,255,0),
CV_RGB(255,0,0),
CV_RGB(255,0,255)} ;
cv::ocl::oclMat image(img);
cv::ocl::oclMat gray, smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );
if(calTime) workBegin();
cv::ocl::cvtColor( image, gray, CV_BGR2GRAY );
cv::ocl::resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
cv::ocl::equalizeHist( smallImg, smallImg );
CvSeq* _objects;
MemStorage storage(cvCreateMemStorage(0));
t = (double)cvGetTickCount();
_objects = cascade.oclHaarDetectObjects( smallImg, storage, 1.1,
cascade.detectMultiScale( smallImg, faces, 1.1,
3, 0
|CV_HAAR_SCALE_IMAGE
, Size(30,30), Size(0, 0) );
vector<CvAvgComp> vecAvgComp;
Seq<CvAvgComp>(_objects).copyTo(vecAvgComp);
faces.resize(vecAvgComp.size());
std::transform(vecAvgComp.begin(), vecAvgComp.end(), faces.begin(), getRect());
t = (double)cvGetTickCount() - t;
printf( "detection time = %g ms\n", t/((double)cvGetTickFrequency()*1000.) );
if(calTime) workEnd();
}
void detectCPU( Mat& img, vector<Rect>& faces,
CascadeClassifier& cascade,
double scale, bool calTime)
{
if(calTime) workBegin();
Mat cpu_gray, cpu_smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );
cvtColor(img, cpu_gray, CV_BGR2GRAY);
resize(cpu_gray, cpu_smallImg, cpu_smallImg.size(), 0, 0, INTER_LINEAR);
equalizeHist(cpu_smallImg, cpu_smallImg);
cascade.detectMultiScale(cpu_smallImg, faces, 1.1,
3, 0 | CV_HAAR_SCALE_IMAGE,
Size(30, 30), Size(0, 0));
if(calTime) workEnd();
}
void Draw(Mat& img, vector<Rect>& faces, double scale)
{
int i = 0;
for( vector<Rect>::const_iterator r = faces.begin(); r != faces.end(); r++, i++ )
{
Mat smallImgROI;
Point center;
Scalar color = colors[i%8];
int radius;
......@@ -227,3 +232,42 @@ void detectAndDraw( Mat& img,
}
cv::imshow( "result", img );
}
double checkRectSimilarity(Size sz, std::vector<Rect>& ob1, std::vector<Rect>& ob2)
{
double final_test_result = 0.0;
size_t sz1 = ob1.size();
size_t sz2 = ob2.size();
if(sz1 != sz2)
return sz1 > sz2 ? (double)(sz1 - sz2) : (double)(sz2 - sz1);
else
{
cv::Mat cpu_result(sz, CV_8UC1);
cpu_result.setTo(0);
for(vector<Rect>::const_iterator r = ob1.begin(); r != ob1.end(); r++)
{
cv::Mat cpu_result_roi(cpu_result, *r);
cpu_result_roi.setTo(1);
cpu_result.copyTo(cpu_result);
}
int cpu_area = cv::countNonZero(cpu_result > 0);
cv::Mat gpu_result(sz, CV_8UC1);
gpu_result.setTo(0);
for(vector<Rect>::const_iterator r2 = ob2.begin(); r2 != ob2.end(); r2++)
{
cv::Mat gpu_result_roi(gpu_result, *r2);
gpu_result_roi.setTo(1);
gpu_result.copyTo(gpu_result);
}
cv::Mat result_;
multiply(cpu_result, gpu_result, result_);
int result = cv::countNonZero(result_ > 0);
final_test_result = 1.0 - (double)result/(double)cpu_area;
}
return final_test_result;
}
samples/ocl/hog.cpp
View file @ 6bb9342a
......@@ -45,7 +45,6 @@ public:
bool gamma_corr;
};
class App
{
public:
......@@ -64,6 +63,13 @@ public:
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&);
......@@ -290,6 +296,7 @@ void App::run()
ocl::oclMat gpu_img;
// Iterate over all frames
bool verify = false;
while (running && !frame.empty())
{
workBegin();
......@@ -316,7 +323,18 @@ void App::run()
gpu_img.upload(img);
gpu_hog.detectMultiScale(gpu_img, found, hit_threshold, win_stride,
Size(0, 0), scale, gr_threshold);
}
if (!verify)
{
// verify if GPU output same objects with CPU at 1st run
verify = true;
vector<Rect> ref_rst;
cvtColor(img, img, CV_BGRA2BGR);
cpu_hog.detectMultiScale(img, ref_rst, hit_threshold, win_stride,
Size(0, 0), scale, gr_threshold-2);
double accuracy = checkRectSimilarity(img.size(), ref_rst, found);
cout << "\naccuracy value: " << accuracy << endl;
}
}
else cpu_hog.detectMultiScale(img, found, hit_threshold, win_stride,
Size(0, 0), scale, gr_threshold);
hogWorkEnd();
......@@ -457,3 +475,45 @@ inline string App::workFps() const
return ss.str();
}
double App::checkRectSimilarity(Size sz,
std::vector<Rect>& ob1,
std::vector<Rect>& ob2)
{
double final_test_result = 0.0;
size_t sz1 = ob1.size();
size_t sz2 = ob2.size();
if(sz1 != sz2)
return sz1 > sz2 ? (double)(sz1 - sz2) : (double)(sz2 - sz1);
else
{
cv::Mat cpu_result(sz, CV_8UC1);
cpu_result.setTo(0);
for(vector<Rect>::const_iterator r = ob1.begin(); r != ob1.end(); r++)
{
cv::Mat cpu_result_roi(cpu_result, *r);
cpu_result_roi.setTo(1);
cpu_result.copyTo(cpu_result);
}
int cpu_area = cv::countNonZero(cpu_result > 0);
cv::Mat gpu_result(sz, CV_8UC1);
gpu_result.setTo(0);
for(vector<Rect>::const_iterator r2 = ob2.begin(); r2 != ob2.end(); r2++)
{
cv::Mat gpu_result_roi(gpu_result, *r2);
gpu_result_roi.setTo(1);
gpu_result.copyTo(gpu_result);
}
cv::Mat result_;
multiply(cpu_result, gpu_result, result_);
int result = cv::countNonZero(result_ > 0);
final_test_result = 1.0 - (double)result/(double)cpu_area;
}
return final_test_result;
}
samples/ocl/pyrlk_optical_flow.cpp 0 → 100644
View file @ 6bb9342a
#include <iostream>
#include <vector>
#include <iomanip>
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/ocl/ocl.hpp"
#include "opencv2/video/video.hpp"
using namespace std;
using namespace cv;
using namespace cv::ocl;
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 download(const oclMat& d_mat, vector<Point2f>& vec)
{
vec.resize(d_mat.cols);
Mat mat(1, d_mat.cols, CV_32FC2, (void*)&vec[0]);
d_mat.download(mat);
}
static void download(const oclMat& d_mat, vector<uchar>& vec)
{
vec.resize(d_mat.cols);
Mat mat(1, d_mat.cols, CV_8UC1, (void*)&vec[0]);
d_mat.download(mat);
}
static void drawArrows(Mat& frame, const vector<Point2f>& prevPts, const vector<Point2f>& nextPts, const vector<uchar>& status, Scalar line_color = Scalar(0, 0, 255))
{
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[])
{
static std::vector<Info> ocl_info;
ocl::getDevice(ocl_info);
//if you want to use undefault device, set it here
setDevice(ocl_info[0]);
//set this to save kernel compile time from second time you run
ocl::setBinpath("./");
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 }"
"{ s | use_cpu | false | use cpu or gpu to process the image }"
"{ v | video | | use video as input }"
"{ points | points | 1000 | specify points count [GoodFeatureToTrack] }"
"{ min_dist | min_dist | 0 | specify minimal distance between points [GoodFeatureToTrack] }";
CommandLineParser cmd(argc, argv, keys);
if (cmd.get<bool>("help"))
{
cout << "Usage: pyrlk_optical_flow [options]" << endl;
cout << "Avaible options:" << endl;
cmd.printParams();
return 0;
}
bool defaultPicturesFail = false;
string fname0 = cmd.get<string>("left");
string fname1 = cmd.get<string>("right");
string vdofile = cmd.get<string>("video");
int points = cmd.get<int>("points");
double minDist = cmd.get<double>("min_dist");
bool useCPU = cmd.get<bool>("s");
bool useCamera = cmd.get<bool>("c");
int inputName = cmd.get<int>("c");
oclMat d_nextPts, d_status;
Mat frame0 = imread(fname0, cv::IMREAD_GRAYSCALE);
Mat frame1 = imread(fname1, cv::IMREAD_GRAYSCALE);
PyrLKOpticalFlow d_pyrLK;
vector<cv::Point2f> pts;
vector<cv::Point2f> nextPts;
vector<unsigned char> status;
vector<float> err;
if (frame0.empty() || frame1.empty())
{
useCamera = true;
defaultPicturesFail = true;
CvCapture* capture = 0;
capture = cvCaptureFromCAM( inputName );
if (!capture)
{
cout << "Can't load input images" << endl;
return -1;
}
}
cout << "Points count : " << points << endl << endl;
if (useCamera)
{
CvCapture* capture = 0;
Mat frame, frameCopy;
Mat frame0Gray, frame1Gray;
Mat ptr0, ptr1;
if(vdofile == "")
capture = cvCaptureFromCAM( inputName );
else
capture = cvCreateFileCapture(vdofile.c_str());
int c = inputName ;
if(!capture)
{
if(vdofile == "")
cout << "Capture from CAM " << c << " didn't work" << endl;
else
cout << "Capture from file " << vdofile << " failed" <<endl;
if (defaultPicturesFail)
{
return -1;
}
goto nocamera;
}
cout << "In capture ..." << endl;
for(int i = 0;; i++)
{
frame = cvQueryFrame( capture );
if( frame.empty() )
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();
cv::goodFeaturesToTrack(ptr0, pts, points, 0.01, 0.0);
if (pts.size() == 0)
{
continue;
}
if (useCPU)
{
cv::calcOpticalFlowPyrLK(ptr0, ptr1, pts, nextPts, status, err);
}
else
{
oclMat d_prevPts(1, points, CV_32FC2, (void*)&pts[0]);
d_pyrLK.sparse(oclMat(ptr0), oclMat(ptr1), d_prevPts, d_nextPts, d_status);
download(d_prevPts, pts);
download(d_nextPts, nextPts);
download(d_status, status);
}
if (i%2 == 1)
frame1.copyTo(frameCopy);
else
frame0.copyTo(frameCopy);
drawArrows(frameCopy, pts, nextPts, status, Scalar(255, 0, 0));
imshow("PyrLK [Sparse]", frameCopy);
}
if( waitKey( 10 ) >= 0 )
goto _cleanup_;
}
waitKey(0);
_cleanup_:
cvReleaseCapture( &capture );
}
else
{
nocamera:
for(int i = 0; i <= LOOP_NUM;i ++)
{
cout << "loop" << i << endl;
if (i > 0) workBegin();
cv::goodFeaturesToTrack(frame0, pts, points, 0.01, minDist);
if (useCPU)
{
cv::calcOpticalFlowPyrLK(frame0, frame1, pts, nextPts, status, err);
}
else
{
oclMat d_prevPts(1, points, CV_32FC2, (void*)&pts[0]);
d_pyrLK.sparse(oclMat(frame0), oclMat(frame1), d_prevPts, d_nextPts, d_status);
download(d_prevPts, pts);
download(d_nextPts, nextPts);
download(d_status, status);
}
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;
drawArrows(frame0, pts, nextPts, status, Scalar(255, 0, 0));
imshow("PyrLK [Sparse]", frame0);
}
}
}
waitKey();
return 0;
}
samples/ocl/stereo_match.cpp 0 → 100644
View file @ 6bb9342a
#include <iostream>
#include <string>
#include <sstream>
#include <iomanip>
#include <stdexcept>
#include "opencv2/ocl/ocl.hpp"
#include "opencv2/highgui/highgui.hpp"
using namespace cv;
using namespace std;
using namespace ocl;
bool help_showed = false;
struct Params
{
Params();
static Params read(int argc, char** argv);
string left;
string right;
string method_str() const
{
switch (method)
{
case BM: return "BM";
case BP: return "BP";
case CSBP: return "CSBP";
}
return "";
}
enum {BM, BP, CSBP} method;
int ndisp; // Max disparity + 1
enum {GPU, CPU} type;
};
struct App
{
App(const Params& p);
void run();
void handleKey(char key);
void printParams() const;
void workBegin() { work_begin = getTickCount(); }
void workEnd()
{
int64 d = getTickCount() - work_begin;
double f = getTickFrequency();
work_fps = f / d;
}
string text() const
{
stringstream ss;
ss << "(" << p.method_str() << ") FPS: " << setiosflags(ios::left)
<< setprecision(4) << work_fps;
return ss.str();
}
private:
Params p;
bool running;
Mat left_src, right_src;
Mat left, right;
oclMat d_left, d_right;
StereoBM_OCL bm;
StereoBeliefPropagation bp;
StereoConstantSpaceBP csbp;
int64 work_begin;
double work_fps;
};
static void printHelp()
{
cout << "Usage: stereo_match_gpu\n"
<< "\t--left <left_view> --right <right_view> # must be rectified\n"
<< "\t--method <stereo_match_method> # BM | BP | CSBP\n"
<< "\t--ndisp <number> # number of disparity levels\n"
<< "\t--type <device_type> # cpu | CPU | gpu | GPU\n";
help_showed = true;
}
int main(int argc, char** argv)
{
try
{
if (argc < 2)
{
printHelp();
return 1;
}
Params args = Params::read(argc, argv);
if (help_showed)
return -1;
int flags[2] = { CVCL_DEVICE_TYPE_GPU, CVCL_DEVICE_TYPE_CPU };
vector<Info> info;
if(getDevice(info, flags[args.type]) == 0)
{
throw runtime_error("Error: Did not find a valid OpenCL device!");
}
cout << "Device name:" << info[0].DeviceName[0] << endl;
App app(args);
app.run();
}
catch (const exception& e)
{
cout << "error: " << e.what() << endl;
}
return 0;
}
Params::Params()
{
method = BM;
ndisp = 64;
type = GPU;
}
Params Params::read(int argc, char** argv)
{
Params p;
for (int i = 1; i < argc; i++)
{
if (string(argv[i]) == "--left") p.left = argv[++i];
else if (string(argv[i]) == "--right") p.right = argv[++i];
else if (string(argv[i]) == "--method")
{
if (string(argv[i + 1]) == "BM") p.method = BM;
else if (string(argv[i + 1]) == "BP") p.method = BP;
else if (string(argv[i + 1]) == "CSBP") p.method = CSBP;
else throw runtime_error("unknown stereo match method: " + string(argv[i + 1]));
i++;
}
else if (string(argv[i]) == "--ndisp") p.ndisp = atoi(argv[++i]);
else if (string(argv[i]) == "--type")
{
string t(argv[++i]);
if (t == "cpu" || t == "CPU")
{
p.type = CPU;
}
else if (t == "gpu" || t == "GPU")
{
p.type = GPU;
}
else throw runtime_error("unknown device type: " + t);
}
else if (string(argv[i]) == "--help") printHelp();
else throw runtime_error("unknown key: " + string(argv[i]));
}
return p;
}
App::App(const Params& params)
: p(params), running(false)
{
cout << "stereo_match_ocl sample\n";
cout << "\nControls:\n"
<< "\tesc - exit\n"
<< "\tp - print current parameters\n"
<< "\tg - convert source images into gray\n"
<< "\tm - change stereo match method\n"
<< "\ts - change Sobel prefiltering flag (for BM only)\n"
<< "\t1/q - increase/decrease maximum disparity\n"
<< "\t2/w - increase/decrease window size (for BM only)\n"
<< "\t3/e - increase/decrease iteration count (for BP and CSBP only)\n"
<< "\t4/r - increase/decrease level count (for BP and CSBP only)\n";
}
void App::run()
{
// Load images
left_src = imread(p.left);
right_src = imread(p.right);
if (left_src.empty()) throw runtime_error("can't open file \"" + p.left + "\"");
if (right_src.empty()) throw runtime_error("can't open file \"" + p.right + "\"");
cvtColor(left_src, left, CV_BGR2GRAY);
cvtColor(right_src, right, CV_BGR2GRAY);
d_left.upload(left);
d_right.upload(right);
imshow("left", left);
imshow("right", right);
// Set common parameters
bm.ndisp = p.ndisp;
bp.ndisp = p.ndisp;
csbp.ndisp = p.ndisp;
cout << endl;
printParams();
running = true;
while (running)
{
// Prepare disparity map of specified type
Mat disp;
oclMat d_disp;
workBegin();
switch (p.method)
{
case Params::BM:
if (d_left.channels() > 1 || d_right.channels() > 1)
{
cout << "BM doesn't support color images\n";
cvtColor(left_src, left, CV_BGR2GRAY);
cvtColor(right_src, right, CV_BGR2GRAY);
cout << "image_channels: " << left.channels() << endl;
d_left.upload(left);
d_right.upload(right);
imshow("left", left);
imshow("right", right);
}
bm(d_left, d_right, d_disp);
break;
case Params::BP:
bp(d_left, d_right, d_disp);
break;
case Params::CSBP:
csbp(d_left, d_right, d_disp);
break;
}
ocl::finish();
workEnd();
// Show results
d_disp.download(disp);
if (p.method != Params::BM)
{
disp.convertTo(disp, 0);
}
putText(disp, text(), Point(5, 25), FONT_HERSHEY_SIMPLEX, 1.0, Scalar::all(255));
imshow("disparity", disp);
handleKey((char)waitKey(3));
}
}
void App::printParams() const
{
cout << "--- Parameters ---\n";
cout << "image_size: (" << left.cols << ", " << left.rows << ")\n";
cout << "image_channels: " << left.channels() << endl;
cout << "method: " << p.method_str() << endl
<< "ndisp: " << p.ndisp << endl;
switch (p.method)
{
case Params::BM:
cout << "win_size: " << bm.winSize << endl;
cout << "prefilter_sobel: " << bm.preset << endl;
break;
case Params::BP:
cout << "iter_count: " << bp.iters << endl;
cout << "level_count: " << bp.levels << endl;
break;
case Params::CSBP:
cout << "iter_count: " << csbp.iters << endl;
cout << "level_count: " << csbp.levels << endl;
break;
}
cout << endl;
}
void App::handleKey(char key)
{
switch (key)
{
case 27:
running = false;
break;
case 'p': case 'P':
printParams();
break;
case 'g': case 'G':
if (left.channels() == 1 && p.method != Params::BM)
{
left = left_src;
right = right_src;
}
else
{
cvtColor(left_src, left, CV_BGR2GRAY);
cvtColor(right_src, right, CV_BGR2GRAY);
}
d_left.upload(left);
d_right.upload(right);
cout << "image_channels: " << left.channels() << endl;
imshow("left", left);
imshow("right", right);
break;
case 'm': case 'M':
switch (p.method)
{
case Params::BM:
p.method = Params::BP;
break;
case Params::BP:
p.method = Params::CSBP;
break;
case Params::CSBP:
p.method = Params::BM;
break;
}
cout << "method: " << p.method_str() << endl;
break;
case 's': case 'S':
if (p.method == Params::BM)
{
switch (bm.preset)
{
case StereoBM_OCL::BASIC_PRESET:
bm.preset = StereoBM_OCL::PREFILTER_XSOBEL;
break;
case StereoBM_OCL::PREFILTER_XSOBEL:
bm.preset = StereoBM_OCL::BASIC_PRESET;
break;
}
cout << "prefilter_sobel: " << bm.preset << endl;
}
break;
case '1':
p.ndisp = p.ndisp == 1 ? 8 : p.ndisp + 8;
cout << "ndisp: " << p.ndisp << endl;
bm.ndisp = p.ndisp;
bp.ndisp = p.ndisp;
csbp.ndisp = p.ndisp;
break;
case 'q': case 'Q':
p.ndisp = max(p.ndisp - 8, 1);
cout << "ndisp: " << p.ndisp << endl;
bm.ndisp = p.ndisp;
bp.ndisp = p.ndisp;
csbp.ndisp = p.ndisp;
break;
case '2':
if (p.method == Params::BM)
{
bm.winSize = min(bm.winSize + 1, 51);
cout << "win_size: " << bm.winSize << endl;
}
break;
case 'w': case 'W':
if (p.method == Params::BM)
{
bm.winSize = max(bm.winSize - 1, 2);
cout << "win_size: " << bm.winSize << endl;
}
break;
case '3':
if (p.method == Params::BP)
{
bp.iters += 1;
cout << "iter_count: " << bp.iters << endl;
}
else if (p.method == Params::CSBP)
{
csbp.iters += 1;
cout << "iter_count: " << csbp.iters << endl;
}
break;
case 'e': case 'E':
if (p.method == Params::BP)
{
bp.iters = max(bp.iters - 1, 1);
cout << "iter_count: " << bp.iters << endl;
}
else if (p.method == Params::CSBP)
{
csbp.iters = max(csbp.iters - 1, 1);
cout << "iter_count: " << csbp.iters << endl;
}
break;
case '4':
if (p.method == Params::BP)
{
bp.levels += 1;
cout << "level_count: " << bp.levels << endl;
}
else if (p.method == Params::CSBP)
{
csbp.levels += 1;
cout << "level_count: " << csbp.levels << endl;
}
break;
case 'r': case 'R':
if (p.method == Params::BP)
{
bp.levels = max(bp.levels - 1, 1);
cout << "level_count: " << bp.levels << endl;
}
else if (p.method == Params::CSBP)
{
csbp.levels = max(csbp.levels - 1, 1);
cout << "level_count: " << csbp.levels << endl;
}
break;
}
}
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