提交 97530caa 编写于 作者: A Alexey Spizhevoy

more refactoring of opencv_stitching

上级 aadb1669
......@@ -31,34 +31,28 @@ void printUsage()
<< "\tTry bigger values for --work_megapix if something is wrong.\n\n";
}
int main(int argc, char* argv[])
{
int64 app_start_time = getTickCount();
cv::setBreakOnError(true);
vector<string> img_names;
// Default parameters
bool trygpu = false;
double work_megapix = 0.2;
double compose_megapix = 1;
int ba_space = BundleAdjuster::FOCAL_RAY_SPACE;
float conf_thresh = 1.f;
bool wave_correct = true;
int warp_type = Warper::SPHERICAL;
bool user_match_conf = false;
float match_conf = 0.6f;
int seam_find_type = SeamFinder::VORONOI;
int blend_type = Blender::MULTI_BAND;
string result_name = "result.png";
double work_scale = 1, compose_scale = 1;
bool is_work_scale_set = false, is_compose_scale_set = false;
// Command line args
vector<string> img_names;
bool trygpu = false;
double work_megapix = 0.2;
double compose_megapix = 1;
int ba_space = BundleAdjuster::FOCAL_RAY_SPACE;
float conf_thresh = 1.f;
bool wave_correct = true;
int warp_type = Warper::SPHERICAL;
bool user_match_conf = false;
float match_conf = 0.6f;
int seam_find_type = SeamFinder::VORONOI;
int blend_type = Blender::MULTI_BAND;
string result_name = "result.png";
int parseCmdArgs(int argc, char** argv)
{
if (argc == 1)
{
printUsage();
return 0;
return -1;
}
for (int i = 1; i < argc; ++i)
......@@ -70,7 +64,6 @@ int main(int argc, char* argv[])
}
}
int64 t = getTickCount();
for (int i = 1; i < argc; ++i)
{
if (string(argv[i]) == "--trygpu")
......@@ -188,7 +181,20 @@ int main(int argc, char* argv[])
else
img_names.push_back(argv[i]);
}
return 0;
}
int main(int argc, char* argv[])
{
int64 app_start_time = getTickCount();
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)
{
......@@ -196,8 +202,12 @@ int main(int argc, char* argv[])
return -1;
}
// We do all matching in work_scale sclae, and compositing in compose_scale scale
double work_scale = 1, compose_scale = 1;
bool is_work_scale_set = false, is_compose_scale_set = false;
LOGLN("Reading images and finding features...");
t = getTickCount();
int64 t = getTickCount();
vector<Mat> images(num_images);
vector<ImageFeatures> features(num_images);
SurfFeaturesFinder finder(trygpu);
......@@ -237,6 +247,7 @@ int main(int argc, char* argv[])
matcher(features, pairwise_matches);
LOGLN("Pairwise matching, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
// 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;
......@@ -248,6 +259,7 @@ int main(int argc, char* argv[])
images = img_subset;
img_names = img_names_subset;
// Check if we still have enough images
num_images = static_cast<int>(img_names.size());
if (num_images < 2)
{
......@@ -308,12 +320,14 @@ int main(int argc, char* argv[])
vector<Size> sizes(num_images);
vector<Mat> masks(num_images);
// Preapre original 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<Warper> warper = Warper::createByCameraFocal(camera_focal, warp_type);
for (int i = 0; i < num_images; ++i)
{
......@@ -324,6 +338,7 @@ int main(int argc, char* argv[])
INTER_NEAREST, BORDER_CONSTANT);
}
// Convert to float for blending
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);
......@@ -333,6 +348,7 @@ int main(int argc, char* argv[])
LOGLN("Finding seams...");
t = getTickCount();
// Find seams
Ptr<SeamFinder> seam_finder = SeamFinder::createDefault(seam_find_type);
seam_finder->find(images_warped_f, corners, masks_warped);
......
......@@ -169,11 +169,13 @@ void FeaturesMatcher::operator ()(const vector<ImageFeatures> &features, vector<
dists[j].idx = j;
}
// Leave near images
vector<bool> is_near(num_images, false);
for (int j = 0; j < num_images; ++j)
if (dists[j].dist < 0.6)
is_near[dists[j].idx] = true;
// Leave k-nearest images
int k = min(4, num_images);
nth_element(dists.begin(), dists.end(), dists.begin() + k);
for (int j = 0; j < k; ++j)
......@@ -181,6 +183,7 @@ void FeaturesMatcher::operator ()(const vector<ImageFeatures> &features, vector<
for (int j = i + 1; j < num_images; ++j)
{
// Ignore poor image pairs
if (!is_near[j])
continue;
......@@ -213,7 +216,6 @@ namespace
{
public:
inline CpuMatcher(float match_conf) : match_conf_(match_conf) {}
void match(const ImageFeatures &features1, const ImageFeatures &features2, MatchesInfo& matches_info);
private:
......@@ -257,15 +259,12 @@ namespace
{
public:
inline GpuMatcher(float match_conf) : match_conf_(match_conf) {}
void match(const ImageFeatures &features1, const ImageFeatures &features2, MatchesInfo& matches_info);
private:
float match_conf_;
GpuMat descriptors1_;
GpuMat descriptors2_;
GpuMat trainIdx_, distance_, allDist_;
};
......
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