reduced memory requirements for multi-band blending
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@ -1,4 +1,5 @@
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#include <opencv2/imgproc/imgproc.hpp>
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#include <opencv2/highgui/highgui.hpp>
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#include "blenders.hpp"
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#include "util.hpp"
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@ -101,64 +102,70 @@ Point MultiBandBlender::blend(const vector<Mat> &src, const vector<Point> &corne
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{
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CV_Assert(src.size() == corners.size() && src.size() == masks.size());
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const int num_images = src.size();
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const int img_type = src[0].type();
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Rect dst_roi = resultRoi(src, corners);
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vector<Mat> src_(num_images);
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vector<Point> corners_(num_images);
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vector<Mat> masks_(num_images);
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// TODO avoid creating extra border
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for (int i = 0; i < num_images; ++i)
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{
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copyMakeBorder(src[i], src_[i],
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corners[i].y - dst_roi.y, dst_roi.br().y - corners[i].y - src[i].rows,
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corners[i].x - dst_roi.x, dst_roi.br().x - corners[i].x - src[i].cols,
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BORDER_REFLECT);
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copyMakeBorder(masks[i], masks_[i],
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corners[i].y - dst_roi.y, dst_roi.br().y - corners[i].y - src[i].rows,
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corners[i].x - dst_roi.x, dst_roi.br().x - corners[i].x - src[i].cols,
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BORDER_CONSTANT);
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corners_[i] = Point(0, 0);
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}
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Mat weight_map;
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vector<Mat> src_pyr_gauss;
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vector< vector<Mat> > src_pyr_laplace(num_images);
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vector< vector<Mat> > weight_pyr_gauss(num_images);
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// Compute all pyramids
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for (int i = 0; i < num_images; ++i)
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{
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createGaussPyr(src_[i], num_bands_, src_pyr_gauss);
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createLaplacePyr(src_pyr_gauss, src_pyr_laplace[i]);
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masks_[i].convertTo(weight_map, CV_32F, 1. / 255.);
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createGaussPyr(weight_map, num_bands_, weight_pyr_gauss[i]);
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}
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computeResultMask(masks, corners, dst_mask);
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Mat dst_level_weight;
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vector<Mat> dst_pyr_laplace(num_bands_ + 1);
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vector<Mat> src_pyr_slice(num_images);
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vector<Mat> weight_pyr_slice(num_images);
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dst_pyr_laplace[0].create(dst_roi.size(), img_type);
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dst_pyr_laplace[0].setTo(Scalar::all(0));
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// Blend pyramids
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for (int level_id = 0; level_id <= num_bands_; ++level_id)
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vector<Mat> dst_band_weights(num_bands_ + 1);
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dst_band_weights[0].create(dst_roi.size(), CV_32F);
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dst_band_weights[0].setTo(0);
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for (int i = 1; i <= num_bands_; ++i)
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{
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for (int i = 0; i < num_images; ++i)
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{
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src_pyr_slice[i] = src_pyr_laplace[i][level_id];
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weight_pyr_slice[i] = weight_pyr_gauss[i][level_id];
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}
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blendLinear(src_pyr_slice, corners_, weight_pyr_slice,
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dst_pyr_laplace[level_id], dst_level_weight);
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dst_pyr_laplace[i].create((dst_pyr_laplace[i - 1].rows + 1) / 2,
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(dst_pyr_laplace[i - 1].cols + 1) / 2, img_type);
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dst_pyr_laplace[i].setTo(Scalar::all(0));
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dst_band_weights[i].create((dst_band_weights[i - 1].rows + 1) / 2,
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(dst_band_weights[i - 1].cols + 1) / 2, CV_32F);
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dst_band_weights[i].setTo(0);
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}
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for (int img_idx = 0; img_idx < num_images; ++img_idx)
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{
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int top = corners[img_idx].y - dst_roi.y;
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int bottom = dst_roi.br().y - corners[img_idx].y - src[img_idx].rows;
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int left = corners[img_idx].x - dst_roi.x;
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int right = dst_roi.br().x - corners[img_idx].x - src[img_idx].cols;
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Mat big_src;
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copyMakeBorder(src[img_idx], big_src, top, bottom, left, right, BORDER_REFLECT);
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vector<Mat> src_pyr_gauss;
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vector<Mat> src_pyr_laplace;
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createGaussPyr(big_src, num_bands_, src_pyr_gauss);
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createLaplacePyr(src_pyr_gauss, src_pyr_laplace);
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Mat big_mask;
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copyMakeBorder(masks[img_idx], big_mask, top, bottom, left, right, BORDER_CONSTANT);
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Mat weight_map;
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big_mask.convertTo(weight_map, CV_32F, 1./255.);
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vector<Mat> weight_pyr_gauss;
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createGaussPyr(weight_map, num_bands_, weight_pyr_gauss);
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for (int band_idx = 0; band_idx <= num_bands_; ++band_idx)
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{
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for (int y = 0; y < dst_pyr_laplace[band_idx].rows; ++y)
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{
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const Point3f* src_row = src_pyr_laplace[band_idx].ptr<Point3f>(y);
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const float* weight_row = weight_pyr_gauss[band_idx].ptr<float>(y);
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Point3f* dst_row = dst_pyr_laplace[band_idx].ptr<Point3f>(y);
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for (int x = 0; x < dst_pyr_laplace[band_idx].cols; ++x)
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dst_row[x] += src_row[x] * weight_row[x];
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}
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dst_band_weights[band_idx] += weight_pyr_gauss[band_idx];
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}
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}
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for (int band_idx = 0; band_idx <= num_bands_; ++band_idx)
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normalize(dst_band_weights[band_idx], dst_pyr_laplace[band_idx]);
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restoreImageFromLaplacePyr(dst_pyr_laplace);
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dst = dst_pyr_laplace[0];
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return dst_roi.tl();
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}
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@ -250,23 +257,27 @@ Point blendLinear(const vector<Mat> &src, const vector<Point> &corners, const ve
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}
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}
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// Normalize sums
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for (int y = 0; y < dst.rows; ++y)
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{
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Point3f *dst_row = dst.ptr<Point3f>(y);
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float *dst_weight_row = dst_weight.ptr<float>(y);
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for (int x = 0; x < dst.cols; ++x)
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{
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dst_weight_row[x] += WEIGHT_EPS;
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dst_row[x] *= 1.f / dst_weight_row[x];
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}
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}
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normalize(dst_weight, dst);
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return dst_roi.tl();
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}
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void normalize(const Mat& weight, Mat& src)
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{
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CV_Assert(weight.type() == CV_32F);
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CV_Assert(src.type() == CV_32FC3);
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for (int y = 0; y < src.rows; ++y)
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{
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Point3f *row = src.ptr<Point3f>(y);
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const float *weight_row = weight.ptr<float>(y);
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for (int x = 0; x < src.cols; ++x)
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row[x] *= 1.f / (weight_row[x] + WEIGHT_EPS);
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}
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}
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void createWeightMap(const Mat &mask, float sharpness, Mat &weight)
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{
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CV_Assert(mask.type() == CV_8U);
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@ -59,13 +59,15 @@ cv::Point computeResultMask(const std::vector<cv::Mat> &masks, const std::vector
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cv::Point blendLinear(const std::vector<cv::Mat> &src, const std::vector<cv::Point> &corners, const std::vector<cv::Mat> &weights,
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cv::Mat& dst, cv::Mat& dst_weight);
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void normalize(const cv::Mat& weight, cv::Mat& src);
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void createWeightMap(const cv::Mat& mask, float sharpness, cv::Mat& weight);
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void createGaussPyr(const cv::Mat& img, int num_layers, std::vector<cv::Mat>& pyr);
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void createLaplacePyr(const std::vector<cv::Mat>& pyr_gauss, std::vector<cv::Mat>& pyr_laplace);
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// Restores source image in-place. Result will be in pyr[0].
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// Restores source image in-place. Result will be stored in pyr[0].
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void restoreImageFromLaplacePyr(std::vector<cv::Mat>& pyr);
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#endif // __OPENCV_BLENDERS_HPP__
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