Commit 16e6c45e authored by Alexey Spizhevoy's avatar Alexey Spizhevoy

changes blenders interface in opencv_stitching

parent fa0c8d95
...@@ -21,246 +21,206 @@ Ptr<Blender> Blender::createDefault(int type) ...@@ -21,246 +21,206 @@ Ptr<Blender> Blender::createDefault(int type)
} }
Point Blender::operator ()(const vector<Mat> &src, const vector<Point> &corners, const vector<Mat> &masks, void Blender::prepare(const vector<Point> &corners, const vector<Size> &sizes)
Mat& dst)
{ {
Mat dst_mask; prepare(resultRoi(corners, sizes));
return (*this)(src, corners, masks, dst, dst_mask);
} }
Point Blender::operator ()(const vector<Mat> &src, const vector<Point> &corners, const vector<Mat> &masks, void Blender::prepare(Rect dst_roi)
Mat &dst, Mat &dst_mask)
{ {
Point dst_tl = blend(src, corners, masks, dst, dst_mask); dst_.create(dst_roi.size(), CV_32FC3);
dst.setTo(Scalar::all(0), dst_mask == 0); dst_.setTo(Scalar::all(0));
return dst_tl; dst_mask_.create(dst_roi.size(), CV_8U);
dst_mask_.setTo(Scalar::all(0));
dst_roi_ = dst_roi;
} }
Point Blender::blend(const vector<Mat> &src, const vector<Point> &corners, const vector<Mat> &masks, void Blender::feed(const Mat &img, const Mat &mask, Point tl)
Mat &dst, Mat &dst_mask)
{ {
for (size_t i = 0; i < src.size(); ++i) CV_Assert(img.type() == CV_32FC3);
{ CV_Assert(mask.type() == CV_8U);
CV_Assert(src[i].type() == CV_32FC3);
CV_Assert(masks[i].type() == CV_8U);
}
const int image_type = src[0].type();
Rect dst_roi = resultRoi(src, corners);
dst.create(dst_roi.size(), image_type);
dst.setTo(Scalar::all(0));
dst_mask.create(dst_roi.size(), CV_8U); int dx = tl.x - dst_roi_.x;
dst_mask.setTo(Scalar::all(0)); int dy = tl.y - dst_roi_.y;
for (size_t i = 0; i < src.size(); ++i) for (int y = 0; y < img.rows; ++y)
{ {
int dx = corners[i].x - dst_roi.x; const Point3f *src_row = img.ptr<Point3f>(y);
int dy = corners[i].y - dst_roi.y; Point3f *dst_row = dst_.ptr<Point3f>(dy + y);
const uchar *mask_row = mask.ptr<uchar>(y);
uchar *dst_mask_row = dst_mask_.ptr<uchar>(dy + y);
for (int y = 0; y < src[i].rows; ++y) for (int x = 0; x < img.cols; ++x)
{ {
const Point3f *src_row = src[i].ptr<Point3f>(y); if (mask_row[x])
Point3f *dst_row = dst.ptr<Point3f>(dy + y); dst_row[dx + x] = src_row[x];
dst_mask_row[dx + x] |= mask_row[x];
const uchar *mask_row = masks[i].ptr<uchar>(y);
uchar *dst_mask_row = dst_mask.ptr<uchar>(dy + y);
for (int x = 0; x < src[i].cols; ++x)
{
if (mask_row[x])
dst_row[dx + x] = src_row[x];
dst_mask_row[dx + x] |= mask_row[x];
}
} }
} }
return dst_roi.tl();
} }
Point FeatherBlender::blend(const vector<Mat> &src, const vector<Point> &corners, const vector<Mat> &masks, void Blender::blend(Mat &dst, Mat &dst_mask)
Mat &dst, Mat &dst_mask)
{ {
vector<Mat> weights(masks.size()); dst_.setTo(Scalar::all(0), dst_mask_ == 0);
for (size_t i = 0; i < weights.size(); ++i) dst = dst_;
createWeightMap(masks[i], sharpness_, weights[i]); dst_mask = dst_mask_;
dst_.release();
dst_mask_.release();
}
Mat dst_weight;
Point dst_tl = blendLinear(src, corners, weights, dst, dst_weight);
dst_mask = dst_weight > WEIGHT_EPS;
return dst_tl; void FeatherBlender::prepare(Rect dst_roi)
{
Blender::prepare(dst_roi);
dst_weight_map_.create(dst_roi.size(), CV_32F);
dst_weight_map_.setTo(0);
} }
Point MultiBandBlender::blend(const vector<Mat> &src, const vector<Point> &corners, const vector<Mat> &masks, void FeatherBlender::feed(const Mat &img, const Mat &mask, Point tl)
Mat &dst, Mat &dst_mask)
{ {
CV_Assert(src.size() == corners.size() && src.size() == masks.size()); CV_Assert(img.type() == CV_32FC3);
const int num_images = src.size(); CV_Assert(mask.type() == CV_8U);
const int img_type = src[0].type();
Rect dst_roi = resultRoi(src, corners);
computeResultMask(masks, corners, dst_mask);
vector<Mat> dst_pyr_laplace(num_bands_ + 1); int dx = tl.x - dst_roi_.x;
dst_pyr_laplace[0].create(dst_roi.size(), img_type); int dy = tl.y - dst_roi_.y;
dst_pyr_laplace[0].setTo(Scalar::all(0));
vector<Mat> dst_band_weights(num_bands_ + 1); createWeightMap(mask, sharpness_, weight_map_);
dst_band_weights[0].create(dst_roi.size(), CV_32F);
dst_band_weights[0].setTo(0);
for (int i = 1; i <= num_bands_; ++i) for (int y = 0; y < img.rows; ++y)
{ {
dst_pyr_laplace[i].create((dst_pyr_laplace[i - 1].rows + 1) / 2, const Point3f* src_row = img.ptr<Point3f>(y);
(dst_pyr_laplace[i - 1].cols + 1) / 2, img_type); Point3f* dst_row = dst_.ptr<Point3f>(dy + y);
dst_pyr_laplace[i].setTo(Scalar::all(0));
dst_band_weights[i].create((dst_band_weights[i - 1].rows + 1) / 2, const float* weight_row = weight_map_.ptr<float>(y);
(dst_band_weights[i - 1].cols + 1) / 2, CV_32F); float* dst_weight_row = dst_weight_map_.ptr<float>(dy + y);
dst_band_weights[i].setTo(0);
}
for (int img_idx = 0; img_idx < num_images; ++img_idx) for (int x = 0; x < img.cols; ++x)
{
int top = corners[img_idx].y - dst_roi.y;
int bottom = dst_roi.br().y - corners[img_idx].y - src[img_idx].rows;
int left = corners[img_idx].x - dst_roi.x;
int right = dst_roi.br().x - corners[img_idx].x - src[img_idx].cols;
vector<Mat> src_pyr_gauss(num_bands_ + 1);
copyMakeBorder(src[img_idx], src_pyr_gauss[0], top, bottom, left, right, BORDER_REFLECT);
for (int i = 0; i < num_bands_; ++i)
pyrDown(src_pyr_gauss[i], src_pyr_gauss[i + 1]);
vector<Mat> src_pyr_laplace;
createLaplacePyr(src_pyr_gauss, src_pyr_laplace);
vector<Mat> weight_pyr_gauss(num_bands_ + 1);
Mat mask_f;
masks[img_idx].convertTo(mask_f, CV_32F, 1./255.);
copyMakeBorder(mask_f, weight_pyr_gauss[0], top, bottom, left, right, BORDER_CONSTANT);
for (int i = 0; i < num_bands_; ++i)
pyrDown(weight_pyr_gauss[i], weight_pyr_gauss[i + 1]);
for (int band_idx = 0; band_idx <= num_bands_; ++band_idx)
{ {
for (int y = 0; y < dst_pyr_laplace[band_idx].rows; ++y) dst_row[dx + x] += src_row[x] * weight_row[x];
{ dst_weight_row[dx + x] += weight_row[x];
const Point3f* src_row = src_pyr_laplace[band_idx].ptr<Point3f>(y);
const float* weight_row = weight_pyr_gauss[band_idx].ptr<float>(y);
Point3f* dst_row = dst_pyr_laplace[band_idx].ptr<Point3f>(y);
for (int x = 0; x < dst_pyr_laplace[band_idx].cols; ++x)
dst_row[x] += src_row[x] * weight_row[x];
}
dst_band_weights[band_idx] += weight_pyr_gauss[band_idx];
} }
} }
}
for (int band_idx = 0; band_idx <= num_bands_; ++band_idx)
normalize(dst_band_weights[band_idx], dst_pyr_laplace[band_idx]);
restoreImageFromLaplacePyr(dst_pyr_laplace); void FeatherBlender::blend(Mat &dst, Mat &dst_mask)
dst = dst_pyr_laplace[0]; {
return dst_roi.tl(); normalize(dst_weight_map_, dst_);
dst_mask_ = dst_weight_map_ > WEIGHT_EPS;
Blender::blend(dst, dst_mask);
} }
////////////////////////////////////////////////////////////////////////////// void MultiBandBlender::prepare(Rect dst_roi)
// Auxiliary functions
Rect resultRoi(const vector<Mat> &src, const vector<Point> &corners)
{ {
Point tl(numeric_limits<int>::max(), numeric_limits<int>::max()); Blender::prepare(dst_roi);
Point br(numeric_limits<int>::min(), numeric_limits<int>::min());
dst_pyr_laplace_.resize(num_bands_ + 1);
dst_pyr_laplace_[0].create(dst_roi.size(), CV_32FC3);
dst_pyr_laplace_[0].setTo(Scalar::all(0));
CV_Assert(src.size() == corners.size()); dst_band_weights_.resize(num_bands_ + 1);
for (size_t i = 0; i < src.size(); ++i) dst_band_weights_[0].create(dst_roi.size(), CV_32F);
dst_band_weights_[0].setTo(0);
for (int i = 1; i <= num_bands_; ++i)
{ {
tl.x = min(tl.x, corners[i].x); dst_pyr_laplace_[i].create((dst_pyr_laplace_[i - 1].rows + 1) / 2,
tl.y = min(tl.y, corners[i].y); (dst_pyr_laplace_[i - 1].cols + 1) / 2, CV_32FC3);
br.x = max(br.x, corners[i].x + src[i].cols); dst_band_weights_[i].create((dst_band_weights_[i - 1].rows + 1) / 2,
br.y = max(br.y, corners[i].y + src[i].rows); (dst_band_weights_[i - 1].cols + 1) / 2, CV_32F);
dst_pyr_laplace_[i].setTo(Scalar::all(0));
dst_band_weights_[i].setTo(0);
} }
return Rect(tl, br);
} }
Point computeResultMask(const vector<Mat> &masks, const vector<Point> &corners, Mat &dst_mask) void MultiBandBlender::feed(const Mat &img, const Mat &mask, Point tl)
{ {
Rect dst_roi = resultRoi(masks, corners); CV_Assert(img.type() == CV_32FC3);
CV_Assert(mask.type() == CV_8U);
dst_mask.create(dst_roi.size(), CV_8U);
dst_mask.setTo(Scalar::all(0));
for (size_t i = 0; i < masks.size(); ++i) int top = tl.y - dst_roi_.y;
int left = tl.x - dst_roi_.x;
int bottom = dst_roi_.br().y - tl.y - img.rows;
int right = dst_roi_.br().x - tl.x - img.cols;
// Create the source image Laplacian pyramid
vector<Mat> src_pyr_gauss(num_bands_ + 1);
copyMakeBorder(img, src_pyr_gauss[0], top, bottom, left, right,
BORDER_REFLECT);
for (int i = 0; i < num_bands_; ++i)
pyrDown(src_pyr_gauss[i], src_pyr_gauss[i + 1]);
vector<Mat> src_pyr_laplace;
createLaplacePyr(src_pyr_gauss, src_pyr_laplace);
src_pyr_gauss.clear();
// Create the weight map Gaussian pyramid
Mat weight_map;
mask.convertTo(weight_map, CV_32F, 1./255.);
vector<Mat> weight_pyr_gauss(num_bands_ + 1);
copyMakeBorder(weight_map, weight_pyr_gauss[0], top, bottom, left, right,
BORDER_CONSTANT);
for (int i = 0; i < num_bands_; ++i)
pyrDown(weight_pyr_gauss[i], weight_pyr_gauss[i + 1]);
// Add weighted layer of the source image to the final Laplacian pyramid layer
for (int i = 0; i <= num_bands_; ++i)
{ {
int dx = corners[i].x - dst_roi.x; for (int y = 0; y < dst_pyr_laplace_[i].rows; ++y)
int dy = corners[i].y - dst_roi.y;
for (int y = 0; y < masks[i].rows; ++y)
{ {
const uchar *mask_row = masks[i].ptr<uchar>(y); const Point3f* src_row = src_pyr_laplace[i].ptr<Point3f>(y);
uchar *dst_mask_row = dst_mask.ptr<uchar>(dy + y); Point3f* dst_row = dst_pyr_laplace_[i].ptr<Point3f>(y);
for (int x = 0; x < masks[i].cols; ++x) const float* weight_row = weight_pyr_gauss[i].ptr<float>(y);
dst_mask_row[dx + x] |= mask_row[x];
}
}
return dst_roi.tl(); for (int x = 0; x < dst_pyr_laplace_[i].cols; ++x)
dst_row[x] += src_row[x] * weight_row[x];
}
dst_band_weights_[i] += weight_pyr_gauss[i];
}
} }
Point blendLinear(const vector<Mat> &src, const vector<Point> &corners, const vector<Mat> &weights, void MultiBandBlender::blend(Mat &dst, Mat &dst_mask)
Mat &dst, Mat& dst_weight)
{ {
for (size_t i = 0; i < src.size(); ++i) for (int i = 0; i <= num_bands_; ++i)
{ normalize(dst_band_weights_[i], dst_pyr_laplace_[i]);
CV_Assert(src[i].type() == CV_32FC3);
CV_Assert(weights[i].type() == CV_32F);
}
const int image_type = src[0].type();
Rect dst_roi = resultRoi(src, corners); restoreImageFromLaplacePyr(dst_pyr_laplace_);
dst.create(dst_roi.size(), image_type); dst_ = dst_pyr_laplace_[0];
dst.setTo(Scalar::all(0)); dst_mask_ = dst_band_weights_[0] > WEIGHT_EPS;
dst_pyr_laplace_.clear();
dst_band_weights_.clear();
dst_weight.create(dst_roi.size(), CV_32F); Blender::blend(dst, dst_mask);
dst_weight.setTo(Scalar::all(0)); }
// Compute colors sums and weights
for (size_t i = 0; i < src.size(); ++i)
{
int dx = corners[i].x - dst_roi.x;
int dy = corners[i].y - dst_roi.y;
for (int y = 0; y < src[i].rows; ++y) //////////////////////////////////////////////////////////////////////////////
{ // Auxiliary functions
const Point3f *src_row = src[i].ptr<Point3f>(y);
Point3f *dst_row = dst.ptr<Point3f>(dy + y);
const float *weight_row = weights[i].ptr<float>(y); Rect resultRoi(const vector<Point> &corners, const vector<Size> &sizes)
float *dst_weight_row = dst_weight.ptr<float>(dy + y); {
Point tl(numeric_limits<int>::max(), numeric_limits<int>::max());
Point br(numeric_limits<int>::min(), numeric_limits<int>::min());
for (int x = 0; x < src[i].cols; ++x) CV_Assert(sizes.size() == corners.size());
{ for (size_t i = 0; i < corners.size(); ++i)
dst_row[dx + x] += src_row[x] * weight_row[x]; {
dst_weight_row[dx + x] += weight_row[x]; tl.x = min(tl.x, corners[i].x);
} tl.y = min(tl.y, corners[i].y);
} br.x = max(br.x, corners[i].x + sizes[i].width);
br.y = max(br.y, corners[i].y + sizes[i].height);
} }
normalize(dst_weight, dst); return Rect(tl, br);
return dst_roi.tl();
} }
......
...@@ -9,58 +9,59 @@ class Blender ...@@ -9,58 +9,59 @@ class Blender
{ {
public: public:
enum { NO, FEATHER, MULTI_BAND }; enum { NO, FEATHER, MULTI_BAND };
static cv::Ptr<Blender> createDefault(int type); static cv::Ptr<Blender> createDefault(int type);
cv::Point operator ()(const std::vector<cv::Mat> &src, const std::vector<cv::Point> &corners, const std::vector<cv::Mat> &masks, void prepare(const std::vector<cv::Point> &corners, const std::vector<cv::Size> &sizes);
cv::Mat& dst); virtual void prepare(cv::Rect dst_roi);
cv::Point operator ()(const std::vector<cv::Mat> &src, const std::vector<cv::Point> &corners, const std::vector<cv::Mat> &masks, virtual void feed(const cv::Mat &img, const cv::Mat &mask, cv::Point tl);
cv::Mat& dst, cv::Mat& dst_mask); virtual void blend(cv::Mat &dst, cv::Mat &dst_mask);
protected: protected:
virtual cv::Point blend(const std::vector<cv::Mat> &src, const std::vector<cv::Point> &corners, const std::vector<cv::Mat> &masks, cv::Mat dst_, dst_mask_;
cv::Mat& dst, cv::Mat& dst_mask); cv::Rect dst_roi_;
}; };
class FeatherBlender : public Blender class FeatherBlender : public Blender
{ {
public: public:
FeatherBlender(float sharpness = 0.02f) : sharpness_(sharpness) {} FeatherBlender(float sharpness = 0.02f) { setSharpness(sharpness); }
float sharpness() const { return sharpness_; }
void setSharpness(float val) { sharpness_ = val; }
private: void prepare(cv::Rect dst_roi);
cv::Point blend(const std::vector<cv::Mat> &src, const std::vector<cv::Point> &corners, const std::vector<cv::Mat> &masks, void feed(const cv::Mat &img, const cv::Mat &mask, cv::Point tl);
cv::Mat &dst, cv::Mat &dst_mask); void blend(cv::Mat &dst, cv::Mat &dst_mask);
private:
float sharpness_; float sharpness_;
cv::Mat weight_map_;
cv::Mat dst_weight_map_;
}; };
class MultiBandBlender : public Blender class MultiBandBlender : public Blender
{ {
public: public:
MultiBandBlender(int num_bands = 7) : num_bands_(num_bands) {} MultiBandBlender(int num_bands = 7) { setNumBands(num_bands); }
int numBands() const { return num_bands_; } int numBands() const { return num_bands_; }
void setNumBands(int val) { num_bands_ = val; } void setNumBands(int val) { num_bands_ = val; }
private: void prepare(cv::Rect dst_roi);
cv::Point blend(const std::vector<cv::Mat> &src, const std::vector<cv::Point> &corners, const std::vector<cv::Mat> &masks, void feed(const cv::Mat &img, const cv::Mat &mask, cv::Point tl);
cv::Mat& dst, cv::Mat& dst_mask); void blend(cv::Mat &dst, cv::Mat &dst_mask);
private:
int num_bands_; int num_bands_;
std::vector<cv::Mat> dst_pyr_laplace_;
std::vector<cv::Mat> dst_band_weights_;
}; };
////////////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////////
// Auxiliary functions // Auxiliary functions
cv::Rect resultRoi(const std::vector<cv::Mat> &src, const std::vector<cv::Point> &corners); cv::Rect resultRoi(const std::vector<cv::Point> &corners, const std::vector<cv::Size> &sizes);
cv::Point computeResultMask(const std::vector<cv::Mat> &masks, const std::vector<cv::Point> &corners, cv::Mat &mask);
cv::Point blendLinear(const std::vector<cv::Mat> &src, const std::vector<cv::Point> &corners, const std::vector<cv::Mat> &weights,
cv::Mat& dst, cv::Mat& dst_weight);
void normalize(const cv::Mat& weight, cv::Mat& src); void normalize(const cv::Mat& weight, cv::Mat& src);
......
...@@ -71,7 +71,6 @@ int main(int argc, char* argv[]) ...@@ -71,7 +71,6 @@ int main(int argc, char* argv[])
} }
int64 t = getTickCount(); int64 t = getTickCount();
LOGLN("Parsing params and reading images...");
for (int i = 1; i < argc; ++i) for (int i = 1; i < argc; ++i)
{ {
if (string(argv[i]) == "--trygpu") if (string(argv[i]) == "--trygpu")
...@@ -189,7 +188,6 @@ int main(int argc, char* argv[]) ...@@ -189,7 +188,6 @@ int main(int argc, char* argv[])
else else
img_names.push_back(argv[i]); img_names.push_back(argv[i]);
} }
LOGLN("Parsing params and reading images, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
int num_images = static_cast<int>(img_names.size()); int num_images = static_cast<int>(img_names.size());
if (num_images < 2) if (num_images < 2)
...@@ -198,8 +196,8 @@ int main(int argc, char* argv[]) ...@@ -198,8 +196,8 @@ int main(int argc, char* argv[])
return -1; return -1;
} }
LOGLN("Reading images and finding features...");
t = getTickCount(); t = getTickCount();
LOGLN("Finding features...");
vector<ImageFeatures> features(num_images); vector<ImageFeatures> features(num_images);
SurfFeaturesFinder finder(trygpu); SurfFeaturesFinder finder(trygpu);
Mat full_img, img; Mat full_img, img;
...@@ -224,10 +222,10 @@ int main(int argc, char* argv[]) ...@@ -224,10 +222,10 @@ int main(int argc, char* argv[])
} }
finder(img, features[i]); finder(img, features[i]);
} }
LOGLN("Finding features, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); LOGLN("Reading images and finding features, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
t = getTickCount();
LOGLN("Pairwise matching... "); LOGLN("Pairwise matching... ");
t = getTickCount();
vector<MatchesInfo> pairwise_matches; vector<MatchesInfo> pairwise_matches;
BestOf2NearestMatcher matcher(trygpu); BestOf2NearestMatcher matcher(trygpu);
if (user_match_conf) if (user_match_conf)
...@@ -248,8 +246,8 @@ int main(int argc, char* argv[]) ...@@ -248,8 +246,8 @@ int main(int argc, char* argv[])
return -1; return -1;
} }
t = getTickCount();
LOGLN("Estimating rotations..."); LOGLN("Estimating rotations...");
t = getTickCount();
HomographyBasedEstimator estimator; HomographyBasedEstimator estimator;
vector<CameraParams> cameras; vector<CameraParams> cameras;
estimator(features, pairwise_matches, cameras); estimator(features, pairwise_matches, cameras);
...@@ -263,16 +261,16 @@ int main(int argc, char* argv[]) ...@@ -263,16 +261,16 @@ int main(int argc, char* argv[])
LOGLN("Initial focal length " << i << ": " << cameras[i].focal); LOGLN("Initial focal length " << i << ": " << cameras[i].focal);
} }
t = getTickCount();
LOGLN("Bundle adjustment... "); LOGLN("Bundle adjustment... ");
t = getTickCount();
BundleAdjuster adjuster(ba_space, conf_thresh); BundleAdjuster adjuster(ba_space, conf_thresh);
adjuster(features, pairwise_matches, cameras); adjuster(features, pairwise_matches, cameras);
LOGLN("Bundle adjustment, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); LOGLN("Bundle adjustment, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
if (wave_correct) if (wave_correct)
{ {
t = getTickCount();
LOGLN("Wave correcting..."); LOGLN("Wave correcting...");
t = getTickCount();
vector<Mat> rmats; vector<Mat> rmats;
for (size_t i = 0; i < cameras.size(); ++i) for (size_t i = 0; i < cameras.size(); ++i)
rmats.push_back(cameras[i].R); rmats.push_back(cameras[i].R);
...@@ -292,9 +290,10 @@ int main(int argc, char* argv[]) ...@@ -292,9 +290,10 @@ int main(int argc, char* argv[])
nth_element(focals.begin(), focals.end(), focals.begin() + focals.size() / 2); nth_element(focals.begin(), focals.end(), focals.begin() + focals.size() / 2);
float camera_focal = static_cast<float>(focals[focals.size() / 2]); float camera_focal = static_cast<float>(focals[focals.size() / 2]);
t = getTickCount();
vector<Mat> images(num_images); vector<Mat> images(num_images);
LOGLN("Compose scaling..."); LOGLN("Compose scaling...");
t = getTickCount();
for (int i = 0; i < num_images; ++i) for (int i = 0; i < num_images; ++i)
{ {
Mat full_img = imread(img_names[i]); Mat full_img = imread(img_names[i]);
...@@ -319,38 +318,54 @@ int main(int argc, char* argv[]) ...@@ -319,38 +318,54 @@ int main(int argc, char* argv[])
} }
vector<Point> corners(num_images); vector<Point> corners(num_images);
vector<Size> sizes(num_images);
vector<Mat> masks_warped(num_images); vector<Mat> masks_warped(num_images);
vector<Mat> images_warped(num_images); vector<Mat> images_warped(num_images);
t = getTickCount();
LOGLN("Warping images... "); LOGLN("Warping images... ");
t = getTickCount();
Ptr<Warper> warper = Warper::createByCameraFocal(camera_focal, warp_type); Ptr<Warper> warper = Warper::createByCameraFocal(camera_focal, warp_type);
for (int i = 0; i < num_images; ++i) for (int i = 0; i < num_images; ++i)
{ {
corners[i] = (*warper)(images[i], static_cast<float>(cameras[i].focal), cameras[i].R, images_warped[i]); corners[i] = (*warper)(images[i], static_cast<float>(cameras[i].focal), cameras[i].R,
(*warper)(masks[i], static_cast<float>(cameras[i].focal), cameras[i].R, masks_warped[i], INTER_NEAREST, BORDER_CONSTANT); images_warped[i]);
sizes[i] = images_warped[i].size();
(*warper)(masks[i], static_cast<float>(cameras[i].focal), cameras[i].R, masks_warped[i],
INTER_NEAREST, BORDER_CONSTANT);
} }
vector<Mat> images_f(num_images); vector<Mat> images_f(num_images);
for (int i = 0; i < num_images; ++i) for (int i = 0; i < num_images; ++i)
images_warped[i].convertTo(images_f[i], CV_32F); images_warped[i].convertTo(images_f[i], CV_32F);
LOGLN("Warping images, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); LOGLN("Warping images, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
t = getTickCount();
LOGLN("Finding seams..."); LOGLN("Finding seams...");
t = getTickCount();
Ptr<SeamFinder> seam_finder = SeamFinder::createDefault(seam_find_type); Ptr<SeamFinder> seam_finder = SeamFinder::createDefault(seam_find_type);
(*seam_finder)(images_f, corners, masks_warped); (*seam_finder)(images_f, corners, masks_warped);
LOGLN("Finding seams, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); LOGLN("Finding seams, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
t = getTickCount();
LOGLN("Blending images..."); LOGLN("Blending images...");
t = getTickCount();
Ptr<Blender> blender = Blender::createDefault(blend_type); Ptr<Blender> blender = Blender::createDefault(blend_type);
if (blend_type == Blender::MULTI_BAND) if (blend_type == Blender::MULTI_BAND)
{
// Ensure last pyramid layer area is about 1 pix // Ensure last pyramid layer area is about 1 pix
dynamic_cast<MultiBandBlender*>((Blender*)(blender)) MultiBandBlender* mb = dynamic_cast<MultiBandBlender*>((Blender*)(blender));
->setNumBands(static_cast<int>(ceil(log(static_cast<double>(images_f[0].size().area())) mb->setNumBands(static_cast<int>(ceil(log(static_cast<double>(images_f[0].size().area())) / log(4.0))));
/ log(4.0)))); LOGLN("Multi-band blending num. bands: " << mb->numBands());
}
blender->prepare(corners, sizes);
for (int i = 0; i < num_images; ++i)
blender->feed(images_f[i], masks_warped[i], corners[i]);
Mat result, result_mask; Mat result, result_mask;
(*blender)(images_f, corners, masks_warped, result, result_mask); blender->blend(result, result_mask);
LOGLN("Blending images, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); LOGLN("Blending images, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
imwrite(result_name, result); imwrite(result_name, result);
......
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