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[~] Refactored, cleaned up, and consolidated the code of GPU examples (cascadeclassifier and cascadeclassifier_nvidia_api)

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This commit is contained in:
Anton Obukhov
2011-04-07 12:59:01 +00:00
parent daac469b83
commit 07d19c2c6f
4 changed files with 293 additions and 259 deletions
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80
samples/gpu/cascadeclassifier.cpp
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@@ -1,19 +1,29 @@
// WARNING: this sample is under construction! Use it on your own risk.
#pragma warning(disable : 4100)
#include "cvconfig.h"
#include <iostream>
#include <iomanip>
#include <opencv2/contrib/contrib.hpp>
#include <opencv2/objdetect/objdetect.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/gpu/gpu.hpp>
#include <iostream>
#include <iomanip>
using namespace std;
using namespace cv;
using namespace cv::gpu;
#if !defined(HAVE_CUDA)
int main(int argc, const char **argv)
{
cout << "Please compile the library with CUDA support" << endl;
return -1;
}
#else
void help()
{
cout << "Usage: ./cascadeclassifier <cascade_file> <image_or_video_or_cameraid>\n"
@@ -21,14 +31,8 @@ void help()
}
void DetectAndDraw(Mat& img, CascadeClassifier_GPU& cascade);
String cascadeName = "../../data/haarcascades/haarcascade_frontalface_alt.xml";
String nestedCascadeName = "../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml";
template<class T> void convertAndResize(const T& src, T& gray, T& resized, double scale)
template<class T>
void convertAndResize(const T& src, T& gray, T& resized, double scale)
{
if (src.channels() == 3)
{
@@ -54,15 +58,16 @@ template<class T> void convertAndResize(const T& src, T& gray, T& resized, doubl
void matPrint(Mat &img, int lineOffsY, Scalar fontColor, const ostringstream &ss)
{
int fontFace = FONT_HERSHEY_PLAIN;
double fontScale = 1.5;
int fontFace = FONT_HERSHEY_DUPLEX;
double fontScale = 0.8;
int fontThickness = 2;
Size fontSize = cv::getTextSize("T[]", fontFace, fontScale, fontThickness, 0);
Point org;
org.x = 1;
org.y = 3 * fontSize.height * (lineOffsY + 1) / 2;
putText(img, ss.str(), org, fontFace, fontScale, fontColor, fontThickness);
putText(img, ss.str(), org, fontFace, fontScale, CV_RGB(0,0,0), 5*fontThickness/2, 16);
putText(img, ss.str(), org, fontFace, fontScale, fontColor, fontThickness, 16);
}
@@ -72,25 +77,26 @@ void displayState(Mat &canvas, bool bHelp, bool bGpu, bool bLargestFace, bool bF
Scalar fontColorNV = CV_RGB(118,185,0);
ostringstream ss;
ss << "FPS = " << setprecision(1) << fixed << fps;
matPrint(canvas, 0, fontColorRed, ss);
ss.str("");
ss << "[" << canvas.cols << "x" << canvas.rows << "], " <<
(bGpu ? "GPU, " : "CPU, ") <<
(bLargestFace ? "OneFace, " : "MultiFace, ") <<
(bFilter ? "Filter:ON, " : "Filter:OFF, ") <<
"FPS = " << setprecision(1) << fixed << fps;
matPrint(canvas, 0, fontColorRed, ss);
(bFilter ? "Filter:ON" : "Filter:OFF");
matPrint(canvas, 1, fontColorRed, ss);
if (bHelp)
{
matPrint(canvas, 1, fontColorNV, ostringstream("Space - switch GPU / CPU"));
matPrint(canvas, 2, fontColorNV, ostringstream("M - switch OneFace / MultiFace"));
matPrint(canvas, 3, fontColorNV, ostringstream("F - toggle rectangles Filter (only in MultiFace)"));
matPrint(canvas, 4, fontColorNV, ostringstream("H - toggle hotkeys help"));
matPrint(canvas, 5, fontColorNV, ostringstream("1/Q - increase/decrease scale"));
matPrint(canvas, 2, fontColorNV, ostringstream("Space - switch GPU / CPU"));
matPrint(canvas, 3, fontColorNV, ostringstream("M - switch OneFace / MultiFace"));
matPrint(canvas, 4, fontColorNV, ostringstream("F - toggle rectangles Filter"));
matPrint(canvas, 5, fontColorNV, ostringstream("H - toggle hotkeys help"));
matPrint(canvas, 6, fontColorNV, ostringstream("1/Q - increase/decrease scale"));
}
else
{
matPrint(canvas, 1, fontColorNV, ostringstream("H - toggle hotkeys help"));
matPrint(canvas, 2, fontColorNV, ostringstream("H - toggle hotkeys help"));
}
}
@@ -130,8 +136,10 @@ int main(int argc, const char *argv[])
{
if (!capture.open(inputName))
{
int camid = 0;
sscanf(inputName.c_str(), "%d", &camid);
int camid = -1;
istringstream iss(inputName);
iss >> camid;
if (!capture.open(camid))
{
cout << "Can't open source" << endl;
@@ -180,24 +188,26 @@ int main(int argc, const char *argv[])
cascade_gpu.visualizeInPlace = true;
cascade_gpu.findLargestObject = findLargestObject;
detections_num = cascade_gpu.detectMultiScale(resized_gpu, facesBuf_gpu, 1.2, filterRects ? 4 : 0);
detections_num = cascade_gpu.detectMultiScale(resized_gpu, facesBuf_gpu, 1.2,
(filterRects || findLargestObject) ? 4 : 0);
facesBuf_gpu.colRange(0, detections_num).download(faces_downloaded);
}
else
{
Size minSize = cascade_gpu.getClassifierSize();
cascade_cpu.detectMultiScale(resized_cpu, facesBuf_cpu, 1.2, filterRects ? 4 : 0, (findLargestObject ? CV_HAAR_FIND_BIGGEST_OBJECT : 0) | CV_HAAR_SCALE_IMAGE, minSize);
cascade_cpu.detectMultiScale(resized_cpu, facesBuf_cpu, 1.2,
(filterRects || findLargestObject) ? 4 : 0,
(findLargestObject ? CV_HAAR_FIND_BIGGEST_OBJECT : 0)
| CV_HAAR_SCALE_IMAGE,
minSize);
detections_num = (int)facesBuf_cpu.size();
}
if (!useGPU)
if (!useGPU && detections_num)
{
if (detections_num)
for (int i = 0; i < detections_num; ++i)
{
for (int i = 0; i < detections_num; ++i)
{
rectangle(resized_cpu, facesBuf_cpu[i], Scalar(255));
}
rectangle(resized_cpu, facesBuf_cpu[i], Scalar(255));
}
}
@@ -265,3 +275,5 @@ int main(int argc, const char *argv[])
return 0;
}
#endif //!defined(HAVE_CUDA)