Open Source Computer Vision Library https://opencv.org/
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#include <opencv2/imgproc/imgproc.hpp>
#include "blenders.hpp"
#include "util.hpp"
using namespace std;
using namespace cv;
static const float WEIGHT_EPS = 1e-5f;
Ptr<Blender> Blender::createDefault(int type)
{
if (type == NO)
return new Blender();
if (type == FEATHER)
return new FeatherBlender();
if (type == MULTI_BAND)
return new MultiBandBlender();
CV_Error(CV_StsBadArg, "unsupported blending method");
return NULL;
}
Point Blender::operator ()(const vector<Mat> &src, const vector<Point> &corners, const vector<Mat> &masks,
Mat& dst)
{
Mat dst_mask;
return (*this)(src, corners, masks, dst, dst_mask);
}
Point Blender::operator ()(const vector<Mat> &src, const vector<Point> &corners, const vector<Mat> &masks,
Mat &dst, Mat &dst_mask)
{
Point dst_tl = blend(src, corners, masks, dst, dst_mask);
dst.setTo(Scalar::all(0), dst_mask == 0);
return dst_tl;
}
Point Blender::blend(const vector<Mat> &src, const vector<Point> &corners, const vector<Mat> &masks,
Mat &dst, Mat &dst_mask)
{
for (size_t i = 0; i < src.size(); ++i)
{
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);
dst_mask.setTo(Scalar::all(0));
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)
{
const Point3f *src_row = src[i].ptr<Point3f>(y);
Point3f *dst_row = dst.ptr<Point3f>(dy + y);
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,
Mat &dst, Mat &dst_mask)
{
vector<Mat> weights(masks.size());
for (size_t i = 0; i < weights.size(); ++i)
createWeightMap(masks[i], sharpness_, weights[i]);
Mat dst_weight;
Point dst_tl = blendLinear(src, corners, weights, dst, dst_weight);
dst_mask = dst_weight > WEIGHT_EPS;
return dst_tl;
}
Point MultiBandBlender::blend(const vector<Mat> &src, const vector<Point> &corners, const vector<Mat> &masks,
Mat &dst, Mat &dst_mask)
{
CV_Assert(src.size() == corners.size() && src.size() == masks.size());
const int num_images = src.size();
Rect dst_roi = resultRoi(src, corners);
vector<Mat> src_(num_images);
vector<Point> corners_(num_images);
vector<Mat> masks_(num_images);
// TODO avoid creating extra border
for (int i = 0; i < num_images; ++i)
{
copyMakeBorder(src[i], src_[i],
corners[i].y - dst_roi.y, dst_roi.br().y - corners[i].y - src[i].rows,
corners[i].x - dst_roi.x, dst_roi.br().x - corners[i].x - src[i].cols,
BORDER_REFLECT);
copyMakeBorder(masks[i], masks_[i],
corners[i].y - dst_roi.y, dst_roi.br().y - corners[i].y - src[i].rows,
corners[i].x - dst_roi.x, dst_roi.br().x - corners[i].x - src[i].cols,
BORDER_CONSTANT);
corners_[i] = Point(0, 0);
}
Mat weight_map;
vector<Mat> src_pyr_gauss;
vector< vector<Mat> > src_pyr_laplace(num_images);
vector< vector<Mat> > weight_pyr_gauss(num_images);
// Compute all pyramids
for (int i = 0; i < num_images; ++i)
{
createGaussPyr(src_[i], num_bands_, src_pyr_gauss);
createLaplacePyr(src_pyr_gauss, src_pyr_laplace[i]);
masks_[i].convertTo(weight_map, CV_32F, 1. / 255.);
createGaussPyr(weight_map, num_bands_, weight_pyr_gauss[i]);
}
computeResultMask(masks, corners, dst_mask);
Mat dst_level_weight;
vector<Mat> dst_pyr_laplace(num_bands_ + 1);
vector<Mat> src_pyr_slice(num_images);
vector<Mat> weight_pyr_slice(num_images);
// Blend pyramids
for (int level_id = 0; level_id <= num_bands_; ++level_id)
{
for (int i = 0; i < num_images; ++i)
{
src_pyr_slice[i] = src_pyr_laplace[i][level_id];
weight_pyr_slice[i] = weight_pyr_gauss[i][level_id];
}
blendLinear(src_pyr_slice, corners_, weight_pyr_slice,
dst_pyr_laplace[level_id], dst_level_weight);
}
restoreImageFromLaplacePyr(dst_pyr_laplace);
dst = dst_pyr_laplace[0];
return dst_roi.tl();
}
//////////////////////////////////////////////////////////////////////////////
// Auxiliary functions
Rect resultRoi(const vector<Mat> &src, const vector<Point> &corners)
{
Point tl(numeric_limits<int>::max(), numeric_limits<int>::max());
Point br(numeric_limits<int>::min(), numeric_limits<int>::min());
CV_Assert(src.size() == corners.size());
for (size_t i = 0; i < src.size(); ++i)
{
tl.x = min(tl.x, corners[i].x);
tl.y = min(tl.y, corners[i].y);
br.x = max(br.x, corners[i].x + src[i].cols);
br.y = max(br.y, corners[i].y + src[i].rows);
}
return Rect(tl, br);
}
Point computeResultMask(const vector<Mat> &masks, const vector<Point> &corners, Mat &dst_mask)
{
Rect dst_roi = resultRoi(masks, corners);
dst_mask.create(dst_roi.size(), CV_8U);
dst_mask.setTo(Scalar::all(0));
for (size_t i = 0; i < masks.size(); ++i)
{
int dx = corners[i].x - dst_roi.x;
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);
uchar *dst_mask_row = dst_mask.ptr<uchar>(dy + y);
for (int x = 0; x < masks[i].cols; ++x)
dst_mask_row[dx + x] |= mask_row[x];
}
}
return dst_roi.tl();
}
Point blendLinear(const vector<Mat> &src, const vector<Point> &corners, const vector<Mat> &weights,
Mat &dst, Mat& dst_weight)
{
for (size_t i = 0; i < src.size(); ++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);
dst.create(dst_roi.size(), image_type);
dst.setTo(Scalar::all(0));
dst_weight.create(dst_roi.size(), CV_32F);
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)
{
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);
float *dst_weight_row = dst_weight.ptr<float>(dy + y);
for (int x = 0; x < src[i].cols; ++x)
{
dst_row[dx + x] += src_row[x] * weight_row[x];
dst_weight_row[dx + x] += weight_row[x];
}
}
}
// Normalize sums
for (int y = 0; y < dst.rows; ++y)
{
Point3f *dst_row = dst.ptr<Point3f>(y);
float *dst_weight_row = dst_weight.ptr<float>(y);
for (int x = 0; x < dst.cols; ++x)
{
dst_weight_row[x] += WEIGHT_EPS;
dst_row[x] *= 1.f / dst_weight_row[x];
}
}
return dst_roi.tl();
}
void createWeightMap(const Mat &mask, float sharpness, Mat &weight)
{
CV_Assert(mask.type() == CV_8U);
distanceTransform(mask, weight, CV_DIST_L1, 3);
threshold(weight * sharpness, weight, 1.f, 1.f, THRESH_TRUNC);
}
void createGaussPyr(const Mat &img, int num_layers, vector<Mat> &pyr)
{
pyr.resize(num_layers + 1);
pyr[0] = img.clone();
for (int i = 0; i < num_layers; ++i)
pyrDown(pyr[i], pyr[i + 1]);
}
void createLaplacePyr(const vector<Mat> &pyr_gauss, vector<Mat> &pyr_laplace)
{
if (pyr_gauss.size() == 0)
return;
pyr_laplace.resize(pyr_gauss.size());
Mat tmp;
for (size_t i = 0; i < pyr_laplace.size() - 1; ++i)
{
pyrUp(pyr_gauss[i + 1], tmp, pyr_gauss[i].size());
pyr_laplace[i] = pyr_gauss[i] - tmp;
}
pyr_laplace[pyr_laplace.size() - 1] = pyr_gauss[pyr_laplace.size() - 1].clone();
}
void restoreImageFromLaplacePyr(vector<Mat> &pyr)
{
if (pyr.size() == 0)
return;
Mat tmp;
for (size_t i = pyr.size() - 1; i > 0; --i)
{
pyrUp(pyr[i], tmp, pyr[i - 1].size());
pyr[i - 1] += tmp;
}
}