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opencv/modules/stitching/main.cpp

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#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "util.hpp"
#include "warpers.hpp"
#include "blenders.hpp"
#include "seam_finders.hpp"
#include "motion_estimators.hpp"
using namespace std;
using namespace cv;
void printUsage()
{
cout << "Rotation model images stitcher.\n\n";
cout << "Usage: opencv_stitching img1 img2 [...imgN]\n"
<< "\t[--trygpu (yes|no)]\n"
<< "\t[--work_megapix <float>]\n"
<< "\t[--compose_megapix <float>]\n"
<< "\t[--matchconf <float>]\n"
<< "\t[--ba (ray|focal_ray)]\n"
<< "\t[--conf_thresh <float>]\n"
<< "\t[--wavecorrect (no|yes)]\n"
<< "\t[--warp (plane|cylindrical|spherical)]\n"
<< "\t[--seam (no|voronoi|graphcut)]\n"
<< "\t[--blend (no|feather|multiband)]\n"
<< "\t[--numbands <int>]\n"
<< "\t[--output <result_img>]\n\n";
cout << "--matchconf\n"
<< "\tGood values are in [0.2, 0.8] range usually.\n\n";
cout << "HINT:\n"
<< "\tDefault parameters are for '--trygpu no' configuration.\n"
<< "\tTry bigger values for --work_megapix if something is wrong.\n\n";
}
// 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;
int numbands = 5;
string result_name = "result.png";
int parseCmdArgs(int argc, char** argv)
{
if (argc == 1)
{
printUsage();
return -1;
}
for (int i = 1; i < argc; ++i)
{
if (string(argv[i]) == "--work_megapix")
{
work_megapix = atof(argv[i + 1]);
break;
}
}
for (int i = 1; i < argc; ++i)
{
if (string(argv[i]) == "--trygpu")
{
if (string(argv[i + 1]) == "no")
trygpu = false;
else if (string(argv[i + 1]) == "yes")
trygpu = true;
else
{
cout << "Bad --trygpu flag value\n";
return -1;
}
i++;
}
else if (string(argv[i]) == "--work_megapix")
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]) == "--matchconf")
{
user_match_conf = true;
match_conf = static_cast<float>(atof(argv[i + 1]));
i++;
}
else if (string(argv[i]) == "--ba")
{
if (string(argv[i + 1]) == "ray")
ba_space = BundleAdjuster::RAY_SPACE;
else if (string(argv[i + 1]) == "focal_ray")
ba_space = BundleAdjuster::FOCAL_RAY_SPACE;
else
{
cout << "Bad bundle adjustment space\n";
return -1;
}
i++;
}
else if (string(argv[i]) == "--conf_thresh")
{
conf_thresh = static_cast<float>(atof(argv[i + 1]));
i++;
}
else if (string(argv[i]) == "--wavecorrect")
{
if (string(argv[i + 1]) == "no")
wave_correct = false;
else if (string(argv[i + 1]) == "yes")
wave_correct = true;
else
{
cout << "Bad --wavecorrect flag value\n";
return -1;
}
i++;
}
else if (string(argv[i]) == "--warp")
{
if (string(argv[i + 1]) == "plane")
warp_type = Warper::PLANE;
else if (string(argv[i + 1]) == "cylindrical")
warp_type = Warper::CYLINDRICAL;
else if (string(argv[i + 1]) == "spherical")
warp_type = Warper::SPHERICAL;
else
{
cout << "Bad warping method\n";
return -1;
}
i++;
}
else if (string(argv[i]) == "--seam")
{
if (string(argv[i + 1]) == "no")
seam_find_type = SeamFinder::NO;
else if (string(argv[i + 1]) == "voronoi")
seam_find_type = SeamFinder::VORONOI;
else if (string(argv[i + 1]) == "graphcut")
seam_find_type = SeamFinder::GRAPH_CUT;
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]) == "--numbands")
{
numbands = atoi(argv[i + 1]);
i++;
}
else if (string(argv[i]) == "--output")
{
result_name = argv[i + 1];
i++;
}
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)
{
cout << "Need more images\n";
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...");
int64 t = getTickCount();
vector<Mat> images(num_images);
vector<ImageFeatures> features(num_images);
SurfFeaturesFinder finder(trygpu);
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);
}
images[i] = img.clone();
finder(img, features[i]);
}
full_img.release();
img.release();
LOGLN("Reading images and finding features, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
LOGLN("Pairwise matching... ");
t = getTickCount();
vector<MatchesInfo> pairwise_matches;
BestOf2NearestMatcher matcher(trygpu);
if (user_match_conf)
matcher = BestOf2NearestMatcher(trygpu, match_conf);
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;
for (size_t i = 0; i < indices.size(); ++i)
{
img_subset.push_back(images[indices[i]]);
img_names_subset.push_back(img_names[indices[i]]);
}
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)
{
cout << "Need more images\n";
return -1;
}
LOGLN("Estimating rotations...");
t = getTickCount();
HomographyBasedEstimator estimator;
vector<CameraParams> cameras;
estimator(features, pairwise_matches, cameras);
LOGLN("Estimating rotations, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
for (size_t i = 0; i < cameras.size(); ++i)
{
Mat R;
cameras[i].R.convertTo(R, CV_32F);
cameras[i].R = R;
LOGLN("Initial focal length " << i << ": " << cameras[i].focal);
}
LOGLN("Bundle adjustment... ");
t = getTickCount();
BundleAdjuster adjuster(ba_space, conf_thresh);
adjuster(features, pairwise_matches, cameras);
LOGLN("Bundle adjustment, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
if (wave_correct)
{
LOGLN("Wave correcting...");
t = getTickCount();
vector<Mat> rmats;
for (size_t i = 0; i < cameras.size(); ++i)
rmats.push_back(cameras[i].R);
waveCorrect(rmats);
for (size_t i = 0; i < cameras.size(); ++i)
cameras[i].R = rmats[i];
LOGLN("Wave correcting, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
}
// Find median focal length
vector<double> focals;
for (size_t i = 0; i < cameras.size(); ++i)
{
LOGLN("Camera focal length " << i << ": " << cameras[i].focal);
focals.push_back(cameras[i].focal);
}
nth_element(focals.begin(), focals.end(), focals.begin() + focals.size() / 2);
float camera_focal = static_cast<float>(focals[focals.size() / 2]);
LOGLN("Warping images (auxiliary)... ");
t = getTickCount();
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 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)
{
corners[i] = warper->warp(images[i], static_cast<float>(cameras[i].focal), cameras[i].R,
images_warped[i]);
sizes[i] = images_warped[i].size();
warper->warp(masks[i], static_cast<float>(cameras[i].focal), cameras[i].R, masks_warped[i],
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);
LOGLN("Warping images, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
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);
LOGLN("Finding seams, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
// Release unused memory
images.clear();
images_warped.clear();
images_warped_f.clear();
masks.clear();
LOGLN("Compositing...");
t = getTickCount();
Mat img_warped, img_warped_f;
Mat dilated_mask, seam_mask, mask, mask_warped;
Ptr<Blender> blender;
double compose_aspect = 1;
for (int img_idx = 0; img_idx < num_images; ++img_idx)
{
LOGLN("Compositing image #" << img_idx);
// 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;
compose_aspect = compose_scale / work_scale;
camera_focal *= static_cast<float>(compose_aspect);
warper = Warper::createByCameraFocal(camera_focal, warp_type);
}
if (abs(compose_scale - 1) > 1e-1)
resize(full_img, img, Size(), compose_scale, compose_scale);
else
img = full_img;
full_img.release();
// Update cameras paramters
cameras[img_idx].focal *= compose_aspect;
// Warp the current image
warper->warp(img, static_cast<float>(cameras[img_idx].focal), cameras[img_idx].R,
img_warped);
img_warped.convertTo(img_warped_f, CV_32F);
img_warped.release();
// Warp current image mask
mask.create(img.size(), CV_8U);
mask.setTo(Scalar::all(255));
warper->warp(mask, static_cast<float>(cameras[img_idx].focal), cameras[img_idx].R, mask_warped,
INTER_NEAREST, BORDER_CONSTANT);
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 (static_cast<Blender*>(blender) == 0)
{
blender = Blender::createDefault(blend_type);
if (blend_type == Blender::MULTI_BAND)
{
MultiBandBlender* mb = dynamic_cast<MultiBandBlender*>(static_cast<Blender*>(blender));
mb->setNumBands(numbands);
}
// Determine the final image size
Rect dst_roi = resultRoi(corners, sizes);
for (int i = 0; i < num_images; ++i)
{
corners[i] = dst_roi.tl() + (corners[i] - dst_roi.tl()) * compose_aspect;
sizes[i] = Size(static_cast<int>((sizes[i].width + 1) * compose_aspect),
static_cast<int>((sizes[i].height + 1) * compose_aspect));
}
blender->prepare(corners, sizes);
}
// Blend the current image
blender->feed(img_warped_f, 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;
}
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