void MultiBandBlender::feed(const Mat &img, const Mat &mask, Point tl)
{
CV_Assert(img.type() == CV_16SC3 || img.type() == CV_8UC3);
CV_Assert(mask.type() == CV_8U);
// Keep source image in memory with small border
int gap = 3 * (1 << num_bands_);
Point tl_new(std::max(dst_roi_.x, tl.x - gap),
std::max(dst_roi_.y, tl.y - gap));
Point br_new(std::min(dst_roi_.br().x, tl.x + img.cols + gap),
std::min(dst_roi_.br().y, tl.y + img.rows + gap));
// Ensure coordinates of top-left, bottom-right corners are divided by (1 << num_bands_).
// After that scale between layers is exactly 2.
//
// We do it to avoid interpolation problems when keeping sub-images only. There is no such problem when
// image is bordered to have size equal to the final image size, but this is too memory hungry approach.
tl_new.x = dst_roi_.x + (((tl_new.x - dst_roi_.x) >> num_bands_) << num_bands_);
tl_new.y = dst_roi_.y + (((tl_new.y - dst_roi_.y) >> num_bands_) << num_bands_);
int width = br_new.x - tl_new.x;
int height = br_new.y - tl_new.y;
width += ((1 << num_bands_) - width % (1 << num_bands_)) % (1 << num_bands_);
height += ((1 << num_bands_) - height % (1 << num_bands_)) % (1 << num_bands_);
br_new.x = tl_new.x + width;
br_new.y = tl_new.y + height;
int dy = std::max(br_new.y - dst_roi_.br().y, 0);
int dx = std::max(br_new.x - dst_roi_.br().x, 0);
tl_new.x -= dx; br_new.x -= dx;
tl_new.y -= dy; br_new.y -= dy;
int top = tl.y - tl_new.y;
int left = tl.x - tl_new.x;
int bottom = br_new.y - tl.y - img.rows;
int right = br_new.x - tl.x - img.cols;
// Create the source image Laplacian pyramid
Mat img_with_border;
copyMakeBorder(img, img_with_border, top, bottom, left, right,
BORDER_REFLECT);
std::vector<Mat> src_pyr_laplace;
if (can_use_gpu_ && img_with_border.depth() == CV_16S)
createLaplacePyrGpu(img_with_border, num_bands_, src_pyr_laplace);
else
createLaplacePyr(img_with_border, num_bands_, src_pyr_laplace);
// Create the weight map Gaussian pyramid
Mat weight_map;
std::vector<Mat> weight_pyr_gauss(num_bands_ + 1);
if(weight_type_ == CV_32F)
{
mask.convertTo(weight_map, CV_32F, 1./255.);
}
else// weight_type_ == CV_16S
{
mask.convertTo(weight_map, CV_16S);
add(weight_map, 1, weight_map, mask != 0);
}
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]);
int y_tl = tl_new.y - dst_roi_.y;
int y_br = br_new.y - dst_roi_.y;
int x_tl = tl_new.x - dst_roi_.x;
int x_br = br_new.x - dst_roi_.x;
// Add weighted layer of the source image to the final Laplacian pyramid layer
if(weight_type_ == CV_32F)
{
for (int i = 0; i <= num_bands_; ++i)
{
for (int y = y_tl; y < y_br; ++y)
{
int y_ = y - y_tl;
const Point3_<short>* src_row = src_pyr_laplace[i].ptr<Point3_<short> >(y_);
Point3_<short>* dst_row = dst_pyr_laplace_[i].ptr<Point3_<short> >(y);
const float* weight_row = weight_pyr_gauss[i].ptr<float>(y_);
float* dst_weight_row = dst_band_weights_[i].ptr<float>(y);
for (int x = x_tl; x < x_br; ++x)
{
int x_ = x - x_tl;
dst_row[x].x += static_cast<short>(src_row[x_].x * weight_row[x_]);
dst_row[x].y += static_cast<short>(src_row[x_].y * weight_row[x_]);
dst_row[x].z += static_cast<short>(src_row[x_].z * weight_row[x_]);
dst_weight_row[x] += weight_row[x_];
}
}
x_tl /= 2; y_tl /= 2;
x_br /= 2; y_br /= 2;
}
}
else// weight_type_ == CV_16S
{
for (int i = 0; i <= num_bands_; ++i)
{
for (int y = y_tl; y < y_br; ++y)
{
int y_ = y - y_tl;
const Point3_<short>* src_row = src_pyr_laplace[i].ptr<Point3_<short> >(y_);
Point3_<short>* dst_row = dst_pyr_laplace_[i].ptr<Point3_<short> >(y);
const short* weight_row = weight_pyr_gauss[i].ptr<short>(y_);
short* dst_weight_row = dst_band_weights_[i].ptr<short>(y);
for (int x = x_tl; x < x_br; ++x)
{
int x_ = x - x_tl;
dst_row[x].x += short((src_row[x_].x * weight_row[x_]) >> 8);
dst_row[x].y += short((src_row[x_].y * weight_row[x_]) >> 8);
dst_row[x].z += short((src_row[x_].z * weight_row[x_]) >> 8);
dst_weight_row[x] += weight_row[x_];
}
}
x_tl /= 2; y_tl /= 2;
x_br /= 2; y_br /= 2;
}
}
}
void MultiBandBlender::feed(InputArray _img, InputArray mask, Point tl)
{
#if ENABLE_LOG
int64 t = getTickCount();
#endif
UMat img = _img.getUMat();
CV_Assert(img.type() == CV_16SC3 || img.type() == CV_8UC3);
CV_Assert(mask.type() == CV_8U);
// Keep source image in memory with small border
int gap = 3 * (1 << num_bands_);
Point tl_new(std::max(dst_roi_.x, tl.x - gap),
std::max(dst_roi_.y, tl.y - gap));
Point br_new(std::min(dst_roi_.br().x, tl.x + img.cols + gap),
std::min(dst_roi_.br().y, tl.y + img.rows + gap));
// Ensure coordinates of top-left, bottom-right corners are divided by (1 << num_bands_).
// After that scale between layers is exactly 2.
//
// We do it to avoid interpolation problems when keeping sub-images only. There is no such problem when
// image is bordered to have size equal to the final image size, but this is too memory hungry approach.
tl_new.x = dst_roi_.x + (((tl_new.x - dst_roi_.x) >> num_bands_) << num_bands_);
tl_new.y = dst_roi_.y + (((tl_new.y - dst_roi_.y) >> num_bands_) << num_bands_);
int width = br_new.x - tl_new.x;
int height = br_new.y - tl_new.y;
width += ((1 << num_bands_) - width % (1 << num_bands_)) % (1 << num_bands_);
height += ((1 << num_bands_) - height % (1 << num_bands_)) % (1 << num_bands_);
br_new.x = tl_new.x + width;
br_new.y = tl_new.y + height;
int dy = std::max(br_new.y - dst_roi_.br().y, 0);
int dx = std::max(br_new.x - dst_roi_.br().x, 0);
tl_new.x -= dx; br_new.x -= dx;
tl_new.y -= dy; br_new.y -= dy;
int top = tl.y - tl_new.y;
int left = tl.x - tl_new.x;
int bottom = br_new.y - tl.y - img.rows;
int right = br_new.x - tl.x - img.cols;
// Create the source image Laplacian pyramid
UMat img_with_border;
copyMakeBorder(_img, img_with_border, top, bottom, left, right,
BORDER_REFLECT);
LOGLN(" Add border to the source image, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
#if ENABLE_LOG
t = getTickCount();
#endif
std::vector<UMat> src_pyr_laplace;
if (can_use_gpu_ && img_with_border.depth() == CV_16S)
createLaplacePyrGpu(img_with_border, num_bands_, src_pyr_laplace);
else
createLaplacePyr(img_with_border, num_bands_, src_pyr_laplace);
LOGLN(" Create the source image Laplacian pyramid, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
#if ENABLE_LOG
t = getTickCount();
#endif
// Create the weight map Gaussian pyramid
UMat weight_map;
std::vector<UMat> weight_pyr_gauss(num_bands_ + 1);
if(weight_type_ == CV_32F)
{
mask.getUMat().convertTo(weight_map, CV_32F, 1./255.);
}
else // weight_type_ == CV_16S
{
mask.getUMat().convertTo(weight_map, CV_16S);
UMat add_mask;
compare(mask, 0, add_mask, CMP_NE);
add(weight_map, Scalar::all(1), weight_map, add_mask);
}
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]);
LOGLN(" Create the weight map Gaussian pyramid, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
#if ENABLE_LOG
t = getTickCount();
#endif
int y_tl = tl_new.y - dst_roi_.y;
int y_br = br_new.y - dst_roi_.y;
int x_tl = tl_new.x - dst_roi_.x;
int x_br = br_new.x - dst_roi_.x;
// Add weighted layer of the source image to the final Laplacian pyramid layer
for (int i = 0; i <= num_bands_; ++i)
{
Rect rc(x_tl, y_tl, x_br - x_tl, y_br - y_tl);
#ifdef HAVE_OPENCL
if ( !cv::ocl::useOpenCL() ||
!ocl_MultiBandBlender_feed(src_pyr_laplace[i], weight_pyr_gauss[i],
dst_pyr_laplace_[i](rc), dst_band_weights_[i](rc)) )
#endif
{
Mat _src_pyr_laplace = src_pyr_laplace[i].getMat(ACCESS_READ);
Mat _dst_pyr_laplace = dst_pyr_laplace_[i](rc).getMat(ACCESS_RW);
Mat _weight_pyr_gauss = weight_pyr_gauss[i].getMat(ACCESS_READ);
Mat _dst_band_weights = dst_band_weights_[i](rc).getMat(ACCESS_RW);
if(weight_type_ == CV_32F)
{
for (int y = 0; y < rc.height; ++y)
{
const Point3_<short>* src_row = _src_pyr_laplace.ptr<Point3_<short> >(y);
Point3_<short>* dst_row = _dst_pyr_laplace.ptr<Point3_<short> >(y);
const float* weight_row = _weight_pyr_gauss.ptr<float>(y);
float* dst_weight_row = _dst_band_weights.ptr<float>(y);
for (int x = 0; x < rc.width; ++x)
{
dst_row[x].x += static_cast<short>(src_row[x].x * weight_row[x]);
dst_row[x].y += static_cast<short>(src_row[x].y * weight_row[x]);
dst_row[x].z += static_cast<short>(src_row[x].z * weight_row[x]);
dst_weight_row[x] += weight_row[x];
}
}
}
else // weight_type_ == CV_16S
{
for (int y = 0; y < y_br - y_tl; ++y)
{
const Point3_<short>* src_row = _src_pyr_laplace.ptr<Point3_<short> >(y);
Point3_<short>* dst_row = _dst_pyr_laplace.ptr<Point3_<short> >(y);
const short* weight_row = _weight_pyr_gauss.ptr<short>(y);
short* dst_weight_row = _dst_band_weights.ptr<short>(y);
for (int x = 0; x < x_br - x_tl; ++x)
{
dst_row[x].x += short((src_row[x].x * weight_row[x]) >> 8);
dst_row[x].y += short((src_row[x].y * weight_row[x]) >> 8);
dst_row[x].z += short((src_row[x].z * weight_row[x]) >> 8);
dst_weight_row[x] += weight_row[x];
}
}
}
}
#ifdef HAVE_OPENCL
else
{
void MultiBandBlenderGpu::feed(const gpu::GpuMat &d_img, const gpu::GpuMat &d_mask, Point tl)
{
CV_Assert(d_img.type() == CV_16SC3);
CV_Assert(d_mask.type() == CV_8U);
// Keep source image in memory with small border
int gap = 3 * (1 << num_bands_);
Point tl_new(max(dst_roi_.x, tl.x - gap),
max(dst_roi_.y, tl.y - gap));
Point br_new(min(dst_roi_.br().x, tl.x + d_img.cols + gap),
min(dst_roi_.br().y, tl.y + d_img.rows + gap));
// Ensure coordinates of top-left, bottom-right corners are divided by (1 << num_bands_).
// After that scale between layers is exactly 2.
//
// We do it to avoid interpolation problems when keeping sub-images only. There is no such problem when
// image is bordered to have size equal to the final image size, but this is too memory hungry approach.
tl_new.x = dst_roi_.x + (((tl_new.x - dst_roi_.x) >> num_bands_) << num_bands_);
tl_new.y = dst_roi_.y + (((tl_new.y - dst_roi_.y) >> num_bands_) << num_bands_);
int width = br_new.x - tl_new.x;
int height = br_new.y - tl_new.y;
width += ((1 << num_bands_) - width % (1 << num_bands_)) % (1 << num_bands_);
height += ((1 << num_bands_) - height % (1 << num_bands_)) % (1 << num_bands_);
br_new.x = tl_new.x + width;
br_new.y = tl_new.y + height;
int dy = max(br_new.y - dst_roi_.br().y, 0);
int dx = max(br_new.x - dst_roi_.br().x, 0);
tl_new.x -= dx; br_new.x -= dx;
tl_new.y -= dy; br_new.y -= dy;
int top = tl.y - tl_new.y;
int left = tl.x - tl_new.x;
int bottom = br_new.y - tl.y - d_img.rows;
int right = br_new.x - tl.x - d_img.cols;
// Create the source image Laplacian pyramid
gpu::GpuMat d_img_with_border;
gpu::copyMakeBorder(d_img, d_img_with_border, top, bottom, left, right, BORDER_REFLECT, Scalar(), stream_);
vector<gpu::GpuMat> d_src_pyr_laplace;
createLaplacePyrGpu(d_img_with_border, num_bands_, d_src_pyr_laplace);
// Create the weight map Gaussian pyramid
gpu::GpuMat d_weight_map;
stream_.enqueueConvert(d_mask, d_weight_map, CV_32F, 1./255.);
vector<gpu::GpuMat> d_weight_pyr_gauss(num_bands_ + 1);
gpu::copyMakeBorder(d_weight_map, d_weight_pyr_gauss[0], top, bottom, left, right, BORDER_CONSTANT, Scalar(), stream_);
for (int i = 0; i < num_bands_; ++i)
gpu::pyrDown(d_weight_pyr_gauss[i], d_weight_pyr_gauss[i + 1], stream_);
int y_tl = tl_new.y - dst_roi_.y;
int y_br = br_new.y - dst_roi_.y;
int x_tl = tl_new.x - dst_roi_.x;
int x_br = br_new.x - dst_roi_.x;
// Add weighted layer of the source image to the final Laplacian pyramid layer
gpu::GpuMat d_tmp;
for (int i = 0; i <= num_bands_; ++i)
{
gpu::GpuMat d_src_roi = d_src_pyr_laplace[i](cv::Rect(0, 0, x_br-x_tl, y_br-y_tl));
gpu::GpuMat d_dst_roi = d_dst_pyr_laplace_[i](cv::Rect(x_tl, y_tl, x_br-x_tl, y_br-y_tl));
gpu::GpuMat d_weight_roi = d_weight_pyr_gauss[i](cv::Rect(0, 0, x_br-x_tl, y_br-y_tl));
gpu::GpuMat d_dst_weight_roi = d_dst_band_weights_[i](cv::Rect(x_tl, y_tl, x_br-x_tl, y_br-y_tl));
// dst_roi += src_roi * weight_roi;
// dst_weight_roi += weight_roi;
gpu::multiply(d_src_roi, d_weight_roi, d_tmp, 1, -1, stream_);
gpu::add(d_dst_roi, d_tmp, d_dst_roi, gpu::GpuMat(), -1, stream_);
gpu::add(d_dst_weight_roi, d_weight_roi, d_dst_weight_roi, gpu::GpuMat(), -1, stream_);
x_tl /= 2; y_tl /= 2;
x_br /= 2; y_br /= 2;
}
stream_.waitForCompletion();
}
