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refactored opencv_stitching

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This commit is contained in:
Alexey Spizhevoy
2011-05-20 08:08:55 +00:00
parent 5b50d63754
commit 2de0e1fc66
7 changed files with 142 additions and 181 deletions
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90
modules/stitching/main.cpp
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@@ -37,7 +37,6 @@ int main(int argc, char* argv[])
cv::setBreakOnError(true);
vector<string> img_names;
vector<Mat> images;
// Default parameters
bool trygpu = false;
@@ -188,32 +187,11 @@ int main(int argc, char* argv[])
i++;
}
else
{
img_names.push_back(argv[i]);
Mat full_img = imread(argv[i]);
if (full_img.empty())
{
cout << "Can't open image " << argv[i] << endl;
return -1;
}
if (work_megapix < 0)
images.push_back(full_img);
else
{
if (!is_work_scale_set)
{
work_scale = min(1.0, sqrt(work_megapix * 1e6 / full_img.size().area()));
is_work_scale_set = true;
}
Mat img;
resize(full_img, img, Size(), work_scale, work_scale);
images.push_back(img);
}
}
}
LOGLN("Parsing params and reading images, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
int num_images = static_cast<int>(images.size());
int num_images = static_cast<int>(img_names.size());
if (num_images < 2)
{
cout << "Need more images\n";
@@ -222,9 +200,30 @@ int main(int argc, char* argv[])
t = getTickCount();
LOGLN("Finding features...");
vector<ImageFeatures> features;
vector<ImageFeatures> features(num_images);
SurfFeaturesFinder finder(trygpu);
finder(images, features);
Mat full_img, img;
for (int i = 0; i < num_images; ++i)
{
full_img = imread(img_names[i]);
if (full_img.empty())
{
cout << "Can't open image " << img_names[i] << endl;
return -1;
}
if (work_megapix < 0)
img = full_img;
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);
}
finder(img, features[i]);
}
LOGLN("Finding features, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
t = getTickCount();
@@ -233,16 +232,16 @@ int main(int argc, char* argv[])
BestOf2NearestMatcher matcher(trygpu);
if (user_match_conf)
matcher = BestOf2NearestMatcher(trygpu, match_conf);
matcher(images, features, pairwise_matches);
matcher(features, pairwise_matches);
LOGLN("Pairwise matching, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
vector<int> indices = leaveBiggestComponent(images, features, pairwise_matches, conf_thresh);
vector<int> indices = leaveBiggestComponent(features, pairwise_matches, conf_thresh);
vector<string> img_names_subset;
for (size_t i = 0; i < indices.size(); ++i)
img_names_subset.push_back(img_names[indices[i]]);
img_names = img_names_subset;
num_images = static_cast<int>(images.size());
num_images = static_cast<int>(img_names.size());
if (num_images < 2)
{
cout << "Need more images\n";
@@ -253,7 +252,7 @@ int main(int argc, char* argv[])
LOGLN("Estimating rotations...");
HomographyBasedEstimator estimator;
vector<CameraParams> cameras;
estimator(images, features, pairwise_matches, cameras);
estimator(features, pairwise_matches, cameras);
LOGLN("Estimating rotations, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
for (size_t i = 0; i < cameras.size(); ++i)
@@ -267,7 +266,7 @@ int main(int argc, char* argv[])
t = getTickCount();
LOGLN("Bundle adjustment... ");
BundleAdjuster adjuster(ba_space, conf_thresh);
adjuster(images, features, pairwise_matches, cameras);
adjuster(features, pairwise_matches, cameras);
LOGLN("Bundle adjustment, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
if (wave_correct)
@@ -293,27 +292,24 @@ int main(int argc, char* argv[])
nth_element(focals.begin(), focals.end(), focals.begin() + focals.size() / 2);
float camera_focal = static_cast<float>(focals[focals.size() / 2]);
if ((work_megapix > 0 || compose_megapix > 0)
&& abs(work_megapix - compose_megapix) > 1e-3)
t = getTickCount();
vector<Mat> images(num_images);
LOGLN("Compose scaling...");
for (int i = 0; i < num_images; ++i)
{
t = getTickCount();
LOGLN("Compose scaling...");
for (int i = 0; i < num_images; ++i)
Mat full_img = imread(img_names[i]);
if (!is_compose_scale_set)
{
Mat full_img = imread(img_names[i]);
if (!is_compose_scale_set)
{
compose_scale = min(1.0, sqrt(compose_megapix * 1e6 / full_img.size().area()));
is_compose_scale_set = true;
}
Mat img;
resize(full_img, img, Size(), compose_scale, compose_scale);
images[i] = img;
cameras[i].focal *= compose_scale / work_scale;
compose_scale = min(1.0, sqrt(compose_megapix * 1e6 / full_img.size().area()));
is_compose_scale_set = true;
}
camera_focal *= static_cast<float>(compose_scale / work_scale);
LOGLN("Compose scaling, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
Mat img;
resize(full_img, img, Size(), compose_scale, compose_scale);
images[i] = img;
cameras[i].focal *= compose_scale / work_scale;
}
camera_focal *= static_cast<float>(compose_scale / work_scale);
LOGLN("Compose scaling, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
vector<Mat> masks(num_images);
for (int i = 0; i < num_images; ++i)