opencv 2.4.10 图像拼接实例演示

上一片中，安装了opencv2.4.10+vs2008的开发环境。并写了一个简单的实例进行测试。效果不是很好，所以接下来尝试一下opencv自带的stitching sample。效果感觉很不错。

stitching源码目录：opencv\sources\samples\cpp\stitching_detailed.cpp

先来看一下效果：



A1.jpg



A2.jpg



A3.jpg

拼接效果图：



还是创建一个win32控制台工程。

/*M///////////////////////////////////////////////////////////////////////////////////////
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#include "stdafx.h"
#include <iostream>
#include <fstream>
#include <string>
#include "opencv2/opencv_modules.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/stitching/detail/autocalib.hpp"
#include "opencv2/stitching/detail/blenders.hpp"
#include "opencv2/stitching/detail/camera.hpp"
#include "opencv2/stitching/detail/exposure_compensate.hpp"
#include "opencv2/stitching/detail/matchers.hpp"
#include "opencv2/stitching/detail/motion_estimators.hpp"
#include "opencv2/stitching/detail/seam_finders.hpp"
#include "opencv2/stitching/detail/util.hpp"
#include "opencv2/stitching/detail/warpers.hpp"
#include "opencv2/stitching/warpers.hpp"

using namespace std;
using namespace cv;
using namespace cv::detail;

static void printUsage()
{
cout <<
"Rotation model images stitcher.\n\n"
"stitching_detailed img1 img2 [...imgN] [flags]\n\n"
"Flags:\n"
" --preview\n"
" Run stitching in the preview mode. Works faster than usual mode,\n"
" but output image will have lower resolution.\n"
" --try_gpu (yes|no)\n"
" Try to use GPU. The default value is 'no'. All default values\n"
" are for CPU mode.\n"
"\nMotion Estimation Flags:\n"
" --work_megapix <float>\n"
" Resolution for image registration step. The default is 0.6 Mpx.\n"
" --features (surf|orb)\n"
" Type of features used for images matching. The default is surf.\n"
" --match_conf <float>\n"
" Confidence for feature matching step. The default is 0.65 for surf and 0.3 for orb.\n"
" --conf_thresh <float>\n"
" Threshold for two images are from the same panorama confidence.\n"
" The default is 1.0.\n"
" --ba (reproj|ray)\n"
" Bundle adjustment cost function. The default is ray.\n"
" --ba_refine_mask (mask)\n"
" Set refinement mask for bundle adjustment. It looks like 'x_xxx',\n"
" where 'x' means refine respective parameter and '_' means don't\n"
" refine one, and has the following format:\n"
" <fx><skew><ppx><aspect><ppy>. The default mask is 'xxxxx'. If bundle\n"
" adjustment doesn't support estimation of selected parameter then\n"
" the respective flag is ignored.\n"
" --wave_correct (no|horiz|vert)\n"
" Perform wave effect correction. The default is 'horiz'.\n"
" --save_graph <file_name>\n"
" Save matches graph represented in DOT language to <file_name> file.\n"
" Labels description: Nm is number of matches, Ni is number of inliers,\n"
" C is confidence.\n"
"\nCompositing Flags:\n"
" --warp (plane|cylindrical|spherical|fisheye|stereographic|compressedPlaneA2B1|compressedPlaneA1.5B1|compressedPlanePortraitA2B1|compressedPlanePortraitA1.5B1|paniniA2B1|paniniA1.5B1|paniniPortraitA2B1|paniniPortraitA1.5B1|mercator|transverseMercator)\n"
" Warp surface type. The default is 'spherical'.\n"
" --seam_megapix <float>\n"
" Resolution for seam estimation step. The default is 0.1 Mpx.\n"
" --seam (no|voronoi|gc_color|gc_colorgrad)\n"
" Seam estimation method. The default is 'gc_color'.\n"
" --compose_megapix <float>\n"
" Resolution for compositing step. Use -1 for original resolution.\n"
" The default is -1.\n"
" --expos_comp (no|gain|gain_blocks)\n"
" Exposure compensation method. The default is 'gain_blocks'.\n"
" --blend (no|feather|multiband)\n"
" Blending method. The default is 'multiband'.\n"
" --blend_strength <float>\n"
" Blending strength from [0,100] range. The default is 5.\n"
" --output <result_img>\n"
" The default is 'result.jpg'.\n";
}

// Default command line args
vector<string> img_names;
bool preview = false;
bool try_gpu = false;
double work_megapix = 0.6;
double seam_megapix = 0.1;
double compose_megapix = -1;
float conf_thresh = 1.f;
string features_type = "surf";
string ba_cost_func = "ray";
string ba_refine_mask = "xxxxx";
bool do_wave_correct = true;
WaveCorrectKind wave_correct = detail::WAVE_CORRECT_HORIZ;
bool save_graph = false;
std::string save_graph_to;
string warp_type = "spherical";
int expos_comp_type = ExposureCompensator::GAIN_BLOCKS;
float match_conf = 0.3f;
string seam_find_type = "gc_color";
int blend_type = Blender::MULTI_BAND;
float blend_strength = 5;
string result_name = "result.jpg";

static int parseCmdArgs(int argc, char** argv)
{
if (argc == 1)
{
printUsage();
return -1;
}
for (int i = 1; i < argc; ++i)
{
if (string(argv[i]) == "--help" || string(argv[i]) == "/?")
{
printUsage();
return -1;
}
else if (string(argv[i]) == "--preview")
{
preview = true;
}
else if (string(argv[i]) == "--try_gpu")
{
if (string(argv[i + 1]) == "no")
try_gpu = false;
else if (string(argv[i + 1]) == "yes")
try_gpu = true;
else
{
cout << "Bad --try_gpu flag value\n";
return -1;
}
i++;
}
else if (string(argv[i]) == "--work_megapix")
{
work_megapix = atof(argv[i + 1]);
i++;
}
else if (string(argv[i]) == "--seam_megapix")
{
seam_megapix = atof(argv[i + 1]);
i++;
}
else if (string(argv[i]) == "--compose_megapix")
{
compose_megapix = atof(argv[i + 1]);
i++;
}
else if (string(argv[i]) == "--result")
{
result_name = argv[i + 1];
i++;
}
else if (string(argv[i]) == "--features")
{
features_type = argv[i + 1];
if (features_type == "orb")
match_conf = 0.3f;
i++;
}
else if (string(argv[i]) == "--match_conf")
{
match_conf = static_cast<float>(atof(argv[i + 1]));
i++;
}
else if (string(argv[i]) == "--conf_thresh")
{
conf_thresh = static_cast<float>(atof(argv[i + 1]));
i++;
}
else if (string(argv[i]) == "--ba")
{
ba_cost_func = argv[i + 1];
i++;
}
else if (string(argv[i]) == "--ba_refine_mask")
{
ba_refine_mask = argv[i + 1];
if (ba_refine_mask.size() != 5)
{
cout << "Incorrect refinement mask length.\n";
return -1;
}
i++;
}
else if (string(argv[i]) == "--wave_correct")
{
if (string(argv[i + 1]) == "no")
do_wave_correct = false;
else if (string(argv[i + 1]) == "horiz")
{
do_wave_correct = true;
wave_correct = detail::WAVE_CORRECT_HORIZ;
}
else if (string(argv[i + 1]) == "vert")
{
do_wave_correct = true;
wave_correct = detail::WAVE_CORRECT_VERT;
}
else
{
cout << "Bad --wave_correct flag value\n";
return -1;
}
i++;
}
else if (string(argv[i]) == "--save_graph")
{
save_graph = true;
save_graph_to = argv[i + 1];
i++;
}
else if (string(argv[i]) == "--warp")
{
warp_type = string(argv[i + 1]);
i++;
}
else if (string(argv[i]) == "--expos_comp")
{
if (string(argv[i + 1]) == "no")
expos_comp_type = ExposureCompensator::NO;
else if (string(argv[i + 1]) == "gain")
expos_comp_type = ExposureCompensator::GAIN;
else if (string(argv[i + 1]) == "gain_blocks")
expos_comp_type = ExposureCompensator::GAIN_BLOCKS;
else
{
cout << "Bad exposure compensation method\n";
return -1;
}
i++;
}
else if (string(argv[i]) == "--seam")
{
if (string(argv[i + 1]) == "no" ||
string(argv[i + 1]) == "voronoi" ||
string(argv[i + 1]) == "gc_color" ||
string(argv[i + 1]) == "gc_colorgrad" ||
string(argv[i + 1]) == "dp_color" ||
string(argv[i + 1]) == "dp_colorgrad")
seam_find_type = argv[i + 1];
else
{
cout << "Bad seam finding method\n";
return -1;
}
i++;
}
else if (string(argv[i]) == "--blend")
{
if (string(argv[i + 1]) == "no")
blend_type = Blender::NO;
else if (string(argv[i + 1]) == "feather")
blend_type = Blender::FEATHER;
else if (string(argv[i + 1]) == "multiband")
blend_type = Blender::MULTI_BAND;
else
{
cout << "Bad blending method\n";
return -1;
}
i++;
}
else if (string(argv[i]) == "--blend_strength")
{
blend_strength = static_cast<float>(atof(argv[i + 1]));
i++;
}
else if (string(argv[i]) == "--output")
{
result_name = argv[i + 1];
i++;
}
else
img_names.push_back(argv[i]);
}
if (preview)
{
compose_megapix = 0.6;
}
return 0;
}

int main(int argc, char* argv[])
{
#if ENABLE_LOG
int64 app_start_time = getTickCount();
#endif

cv::setBreakOnError(true);

int retval = parseCmdArgs(argc, argv);
if (retval)
return retval;

// Check if have enough images
int num_images = static_cast<int>(img_names.size());
if (num_images < 2)
{
LOGLN("Need more images");
return -1;
}

double work_scale = 1, seam_scale = 1, compose_scale = 1;
bool is_work_scale_set = false, is_seam_scale_set = false, is_compose_scale_set = false;

LOGLN("Finding features...");
#if ENABLE_LOG
int64 t = getTickCount();
#endif

Ptr<FeaturesFinder> finder;
if (features_type == "surf")
{
#if defined(HAVE_OPENCV_NONFREE) && defined(HAVE_OPENCV_GPU)
if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
finder = new SurfFeaturesFinderGpu();
else
#endif
finder = new SurfFeaturesFinder();
}
else if (features_type == "orb")
{
finder = new OrbFeaturesFinder();
}
else
{
cout << "Unknown 2D features type: '" << features_type << "'.\n";
return -1;
}

Mat full_img, img;
vector<ImageFeatures> features(num_images);
vector<Mat> images(num_images);
vector<Size> full_img_sizes(num_images);
double seam_work_aspect = 1;

for (int i = 0; i < num_images; ++i)
{
full_img = imread(img_names[i]);
full_img_sizes[i] = full_img.size();

if (full_img.empty())
{
LOGLN("Can't open image " << img_names[i]);
return -1;
}
if (work_megapix < 0)
{
img = full_img;
work_scale = 1;
is_work_scale_set = true;
}
else
{
if (!is_work_scale_set)
{
work_scale = min(1.0, sqrt(work_megapix * 1e6 / full_img.size().area()));
is_work_scale_set = true;
}
resize(full_img, img, Size(), work_scale, work_scale);
}
if (!is_seam_scale_set)
{
seam_scale = min(1.0, sqrt(seam_megapix * 1e6 / full_img.size().area()));
seam_work_aspect = seam_scale / work_scale;
is_seam_scale_set = true;
}

(*finder)(img, features[i]);
features[i].img_idx = i;
LOGLN("Features in image #" << i+1 << ": " << features[i].keypoints.size());

resize(full_img, img, Size(), seam_scale, seam_scale);
images[i] = img.clone();
}

finder->collectGarbage();
full_img.release();
img.release();

LOGLN("Finding features, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");

LOG("Pairwise matching");
#if ENABLE_LOG
t = getTickCount();
#endif
vector<MatchesInfo> pairwise_matches;
BestOf2NearestMatcher matcher(try_gpu, match_conf);
matcher(features, pairwise_matches);
matcher.collectGarbage();
LOGLN("Pairwise matching, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");

// Check if we should save matches graph
if (save_graph)
{
LOGLN("Saving matches graph...");
ofstream f(save_graph_to.c_str());
f << matchesGraphAsString(img_names, pairwise_matches, conf_thresh);
}

// Leave only images we are sure are from the same panorama
vector<int> indices = leaveBiggestComponent(features, pairwise_matches, conf_thresh);
vector<Mat> img_subset;
vector<string> img_names_subset;
vector<Size> full_img_sizes_subset;
for (size_t i = 0; i < indices.size(); ++i)
{
img_names_subset.push_back(img_names[indices[i]]);
img_subset.push_back(images[indices[i]]);
full_img_sizes_subset.push_back(full_img_sizes[indices[i]]);
}

images = img_subset;
img_names = img_names_subset;
full_img_sizes = full_img_sizes_subset;

// Check if we still have enough images
num_images = static_cast<int>(img_names.size());
if (num_images < 2)
{
LOGLN("Need more images");
return -1;
}

HomographyBasedEstimator estimator;
vector<CameraParams> cameras;
estimator(features, pairwise_matches, cameras);

for (size_t i = 0; i < cameras.size(); ++i)
{
Mat R;
cameras[i].R.convertTo(R, CV_32F);
cameras[i].R = R;
LOGLN("Initial intrinsics #" << indices[i]+1 << ":\n" << cameras[i].K());
}

Ptr<detail::BundleAdjusterBase> adjuster;
if (ba_cost_func == "reproj") adjuster = new detail::BundleAdjusterReproj();
else if (ba_cost_func == "ray") adjuster = new detail::BundleAdjusterRay();
else
{
cout << "Unknown bundle adjustment cost function: '" << ba_cost_func << "'.\n";
return -1;
}
adjuster->setConfThresh(conf_thresh);
Mat_<uchar> refine_mask = Mat::zeros(3, 3, CV_8U);
if (ba_refine_mask[0] == 'x') refine_mask(0,0) = 1;
if (ba_refine_mask[1] == 'x') refine_mask(0,1) = 1;
if (ba_refine_mask[2] == 'x') refine_mask(0,2) = 1;
if (ba_refine_mask[3] == 'x') refine_mask(1,1) = 1;
if (ba_refine_mask[4] == 'x') refine_mask(1,2) = 1;
adjuster->setRefinementMask(refine_mask);
(*adjuster)(features, pairwise_matches, cameras);

// Find median focal length

vector<double> focals;
for (size_t i = 0; i < cameras.size(); ++i)
{
LOGLN("Camera #" << indices[i]+1 << ":\n" << cameras[i].K());
focals.push_back(cameras[i].focal);
}

sort(focals.begin(), focals.end());
float warped_image_scale;
if (focals.size() % 2 == 1)
warped_image_scale = static_cast<float>(focals[focals.size() / 2]);
else
warped_image_scale = static_cast<float>(focals[focals.size() / 2 - 1] + focals[focals.size() / 2]) * 0.5f;

if (do_wave_correct)
{
vector<Mat> rmats;
for (size_t i = 0; i < cameras.size(); ++i)
rmats.push_back(cameras[i].R);
waveCorrect(rmats, wave_correct);
for (size_t i = 0; i < cameras.size(); ++i)
cameras[i].R = rmats[i];
}

LOGLN("Warping images (auxiliary)... ");
#if ENABLE_LOG
t = getTickCount();
#endif

vector<Point> corners(num_images);
vector<Mat> masks_warped(num_images);
vector<Mat> images_warped(num_images);
vector<Size> sizes(num_images);
vector<Mat> masks(num_images);

// Preapre images masks
for (int i = 0; i < num_images; ++i)
{
masks[i].create(images[i].size(), CV_8U);
masks[i].setTo(Scalar::all(255));
}

// Warp images and their masks

Ptr<WarperCreator> warper_creator;
#if defined(HAVE_OPENCV_GPU)
if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
{
if (warp_type == "plane") warper_creator = new cv::PlaneWarperGpu();
else if (warp_type == "cylindrical") warper_creator = new cv::CylindricalWarperGpu();
else if (warp_type == "spherical") warper_creator = new cv::SphericalWarperGpu();
}
else
#endif
{
if (warp_type == "plane") warper_creator = new cv::PlaneWarper();
else if (warp_type == "cylindrical") warper_creator = new cv::CylindricalWarper();
else if (warp_type == "spherical") warper_creator = new cv::SphericalWarper();
else if (warp_type == "fisheye") warper_creator = new cv::FisheyeWarper();
else if (warp_type == "stereographic") warper_creator = new cv::StereographicWarper();
else if (warp_type == "compressedPlaneA2B1") warper_creator = new cv::CompressedRectilinearWarper(2, 1);
else if (warp_type == "compressedPlaneA1.5B1") warper_creator = new cv::CompressedRectilinearWarper(1.5, 1);
else if (warp_type == "compressedPlanePortraitA2B1") warper_creator = new cv::CompressedRectilinearPortraitWarper(2, 1);
else if (warp_type == "compressedPlanePortraitA1.5B1") warper_creator = new cv::CompressedRectilinearPortraitWarper(1.5, 1);
else if (warp_type == "paniniA2B1") warper_creator = new cv::PaniniWarper(2, 1);
else if (warp_type == "paniniA1.5B1") warper_creator = new cv::PaniniWarper(1.5, 1);
else if (warp_type == "paniniPortraitA2B1") warper_creator = new cv::PaniniPortraitWarper(2, 1);
else if (warp_type == "paniniPortraitA1.5B1") warper_creator = new cv::PaniniPortraitWarper(1.5, 1);
else if (warp_type == "mercator") warper_creator = new cv::MercatorWarper();
else if (warp_type == "transverseMercator") warper_creator = new cv::TransverseMercatorWarper();
}

if (warper_creator.empty())
{
cout << "Can't create the following warper '" << warp_type << "'\n";
return 1;
}

Ptr<RotationWarper> warper = warper_creator->create(static_cast<float>(warped_image_scale * seam_work_aspect));

for (int i = 0; i < num_images; ++i)
{
Mat_<float> K;
cameras[i].K().convertTo(K, CV_32F);
float swa = (float)seam_work_aspect;
K(0,0) *= swa; K(0,2) *= swa;
K(1,1) *= swa; K(1,2) *= swa;

corners[i] = warper->warp(images[i], K, cameras[i].R, INTER_LINEAR, BORDER_REFLECT, images_warped[i]);
sizes[i] = images_warped[i].size();

warper->warp(masks[i], K, cameras[i].R, INTER_NEAREST, BORDER_CONSTANT, masks_warped[i]);
}

vector<Mat> images_warped_f(num_images);
for (int i = 0; i < num_images; ++i)
images_warped[i].convertTo(images_warped_f[i], CV_32F);

LOGLN("Warping images, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");

Ptr<ExposureCompensator> compensator = ExposureCompensator::createDefault(expos_comp_type);
compensator->feed(corners, images_warped, masks_warped);

Ptr<SeamFinder> seam_finder;
if (seam_find_type == "no")
seam_finder = new detail::NoSeamFinder();
else if (seam_find_type == "voronoi")
seam_finder = new detail::VoronoiSeamFinder();
else if (seam_find_type == "gc_color")
{
#if defined(HAVE_OPENCV_GPU)
if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
seam_finder = new detail::GraphCutSeamFinderGpu(GraphCutSeamFinderBase::COST_COLOR);
else
#endif
seam_finder = new detail::GraphCutSeamFinder(GraphCutSeamFinderBase::COST_COLOR);
}
else if (seam_find_type == "gc_colorgrad")
{
#if defined(HAVE_OPENCV_GPU)
if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
seam_finder = new detail::GraphCutSeamFinderGpu(GraphCutSeamFinderBase::COST_COLOR_GRAD);
else
#endif
seam_finder = new detail::GraphCutSeamFinder(GraphCutSeamFinderBase::COST_COLOR_GRAD);
}
else if (seam_find_type == "dp_color")
seam_finder = new detail::DpSeamFinder(DpSeamFinder::COLOR);
else if (seam_find_type == "dp_colorgrad")
seam_finder = new detail::DpSeamFinder(DpSeamFinder::COLOR_GRAD);
if (seam_finder.empty())
{
cout << "Can't create the following seam finder '" << seam_find_type << "'\n";
return 1;
}

seam_finder->find(images_warped_f, corners, masks_warped);

// Release unused memory
images.clear();
images_warped.clear();
images_warped_f.clear();
masks.clear();

LOGLN("Compositing...");
#if ENABLE_LOG
t = getTickCount();
#endif

Mat img_warped, img_warped_s;
Mat dilated_mask, seam_mask, mask, mask_warped;
Ptr<Blender> blender;
//double compose_seam_aspect = 1;
double compose_work_aspect = 1;

for (int img_idx = 0; img_idx < num_images; ++img_idx)
{
LOGLN("Compositing image #" << indices[img_idx]+1);

// Read image and resize it if necessary
full_img = imread(img_names[img_idx]);
if (!is_compose_scale_set)
{
if (compose_megapix > 0)
compose_scale = min(1.0, sqrt(compose_megapix * 1e6 / full_img.size().area()));
is_compose_scale_set = true;

// Compute relative scales
//compose_seam_aspect = compose_scale / seam_scale;
compose_work_aspect = compose_scale / work_scale;

// Update warped image scale
warped_image_scale *= static_cast<float>(compose_work_aspect);
warper = warper_creator->create(warped_image_scale);

// Update corners and sizes
for (int i = 0; i < num_images; ++i)
{
// Update intrinsics
cameras[i].focal *= compose_work_aspect;
cameras[i].ppx *= compose_work_aspect;
cameras[i].ppy *= compose_work_aspect;

// Update corner and size
Size sz = full_img_sizes[i];
if (std::abs(compose_scale - 1) > 1e-1)
{
sz.width = cvRound(full_img_sizes[i].width * compose_scale);
sz.height = cvRound(full_img_sizes[i].height * compose_scale);
}

Mat K;
cameras[i].K().convertTo(K, CV_32F);
Rect roi = warper->warpRoi(sz, K, cameras[i].R);
corners[i] = roi.tl();
sizes[i] = roi.size();
}
}
if (abs(compose_scale - 1) > 1e-1)
resize(full_img, img, Size(), compose_scale, compose_scale);
else
img = full_img;
full_img.release();
Size img_size = img.size();

Mat K;
cameras[img_idx].K().convertTo(K, CV_32F);

// Warp the current image
warper->warp(img, K, cameras[img_idx].R, INTER_LINEAR, BORDER_REFLECT, img_warped);

// Warp the current image mask
mask.create(img_size, CV_8U);
mask.setTo(Scalar::all(255));
warper->warp(mask, K, cameras[img_idx].R, INTER_NEAREST, BORDER_CONSTANT, mask_warped);

// Compensate exposure
compensator->apply(img_idx, corners[img_idx], img_warped, mask_warped);

img_warped.convertTo(img_warped_s, CV_16S);
img_warped.release();
img.release();
mask.release();

dilate(masks_warped[img_idx], dilated_mask, Mat());
resize(dilated_mask, seam_mask, mask_warped.size());
mask_warped = seam_mask & mask_warped;

if (blender.empty())
{
blender = Blender::createDefault(blend_type, try_gpu);
Size dst_sz = resultRoi(corners, sizes).size();
float blend_width = sqrt(static_cast<float>(dst_sz.area())) * blend_strength / 100.f;
if (blend_width < 1.f)
blender = Blender::createDefault(Blender::NO, try_gpu);
else if (blend_type == Blender::MULTI_BAND)
{
MultiBandBlender* mb = dynamic_cast<MultiBandBlender*>(static_cast<Blender*>(blender));
mb->setNumBands(static_cast<int>(ceil(log(blend_width)/log(2.)) - 1.));
LOGLN("Multi-band blender, number of bands: " << mb->numBands());
}
else if (blend_type == Blender::FEATHER)
{
FeatherBlender* fb = dynamic_cast<FeatherBlender*>(static_cast<Blender*>(blender));
fb->setSharpness(1.f/blend_width);
LOGLN("Feather blender, sharpness: " << fb->sharpness());
}
blender->prepare(corners, sizes);
}

// Blend the current image
blender->feed(img_warped_s, mask_warped, corners[img_idx]);
}

Mat result, result_mask;
blender->blend(result, result_mask);

LOGLN("Compositing, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");

imwrite(result_name, result);

LOGLN("Finished, total time: " << ((getTickCount() - app_start_time) / getTickFrequency()) << " sec");
return 0;
}


编译完成后，运行start->cmd.  切换到工程生成的exe目录下，可以将以上图片保存到该目录下。执行命令：
ImageStitching.exe A1.jpg A2.jpg A3.jpg --preview.  执行简单的拼接，会生成result.jpg。 查看到拼接的效果，如果想直接在窗口输出在源码中加入

imshow(result_name,result);