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added block-based gain compensator (opencv_stitching), added --preview flag.
This commit is contained in:
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@ -52,8 +52,10 @@ Ptr<ExposureCompensator> ExposureCompensator::createDefault(int type)
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{
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if (type == NO)
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return new NoExposureCompensator();
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if (type == OVERLAP)
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return new OverlapExposureCompensator();
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if (type == GAIN)
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return new GainCompensator();
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if (type == GAIN_BLOCKS)
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return new BlocksGainCompensator();
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CV_Error(CV_StsBadArg, "unsupported exposure compensation method");
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return NULL;
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}
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@ -69,7 +71,7 @@ void ExposureCompensator::feed(const vector<Point> &corners, const vector<Mat> &
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}
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void OverlapExposureCompensator::feed(const vector<Point> &corners, const vector<Mat> &images,
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void GainCompensator::feed(const vector<Point> &corners, const vector<Mat> &images,
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const vector<pair<Mat,uchar> > &masks)
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{
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CV_Assert(corners.size() == images.size() && images.size() == masks.size());
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@ -96,7 +98,7 @@ void OverlapExposureCompensator::feed(const vector<Point> &corners, const vector
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submask2 = masks[j].first(Rect(roi.tl() - corners[j], roi.br() - corners[j]));
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intersect = (submask1 == masks[i].second) & (submask2 == masks[j].second);
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N(i, j) = N(j, i) = countNonZero(intersect);
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N(i, j) = N(j, i) = max(1, countNonZero(intersect));
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double Isum1 = 0, Isum2 = 0;
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for (int y = 0; y < roi.height; ++y)
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@ -112,8 +114,8 @@ void OverlapExposureCompensator::feed(const vector<Point> &corners, const vector
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}
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}
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}
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I(i, j) = Isum1 / max(N(i, j), 1);
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I(j, i) = Isum2 / max(N(i, j), 1);
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I(i, j) = Isum1 / N(i, j);
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I(j, i) = Isum2 / N(i, j);
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}
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}
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}
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@ -135,11 +137,103 @@ void OverlapExposureCompensator::feed(const vector<Point> &corners, const vector
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}
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}
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solve(A, b, gains);
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solve(A, b, gains_);
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}
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void OverlapExposureCompensator::apply(int index, Point /*corner*/, Mat &image, const Mat &/*mask*/)
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void GainCompensator::apply(int index, Point /*corner*/, Mat &image, const Mat &/*mask*/)
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{
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image *= gains(index, 0);
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image *= gains_(index, 0);
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}
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vector<double> GainCompensator::gains() const
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{
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vector<double> gains_vec(gains_.rows);
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for (int i = 0; i < gains_.rows; ++i)
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gains_vec[i] = gains_(i, 0);
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return gains_vec;
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}
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void BlocksGainCompensator::feed(const vector<Point> &corners, const vector<Mat> &images,
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const vector<pair<Mat,uchar> > &masks)
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{
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CV_Assert(corners.size() == images.size() && images.size() == masks.size());
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const int num_images = static_cast<int>(images.size());
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vector<Size> bl_per_imgs(num_images);
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vector<Point> block_corners;
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vector<Mat> block_images;
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vector<pair<Mat,uchar> > block_masks;
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// Construct blocks for gain compensator
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for (int img_idx = 0; img_idx < num_images; ++img_idx)
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{
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Size bl_per_img((images[img_idx].cols + bl_width_ - 1) / bl_width_,
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(images[img_idx].rows + bl_height_ - 1) / bl_height_);
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int bl_width = (images[img_idx].cols + bl_per_img.width - 1) / bl_per_img.width;
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int bl_height = (images[img_idx].rows + bl_per_img.height - 1) / bl_per_img.height;
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bl_per_imgs[img_idx] = bl_per_img;
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for (int by = 0; by < bl_per_img.height; ++by)
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{
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for (int bx = 0; bx < bl_per_img.width; ++bx)
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{
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Point bl_tl(bx * bl_width, by * bl_height);
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Point bl_br(min(bl_tl.x + bl_width, images[img_idx].cols),
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min(bl_tl.y + bl_height, images[img_idx].rows));
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block_corners.push_back(corners[img_idx] + bl_tl);
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block_images.push_back(images[img_idx](Rect(bl_tl, bl_br)));
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block_masks.push_back(make_pair(masks[img_idx].first(Rect(bl_tl, bl_br)),
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masks[img_idx].second));
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}
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}
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}
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GainCompensator compensator;
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compensator.feed(block_corners, block_images, block_masks);
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vector<double> gains = compensator.gains();
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gain_maps_.resize(num_images);
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int bl_idx = 0;
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for (int img_idx = 0; img_idx < num_images; ++img_idx)
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{
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Size bl_per_img = bl_per_imgs[img_idx];
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gain_maps_[img_idx].create(bl_per_img);
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for (int by = 0; by < bl_per_img.height; ++by)
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for (int bx = 0; bx < bl_per_img.width; ++bx, ++bl_idx)
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gain_maps_[img_idx](by, bx) = static_cast<float>(gains[bl_idx]);
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Mat_<float> ker(1, 3);
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ker(0,0) = 0.25; ker(0,1) = 0.5; ker(0,2) = 0.25;
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sepFilter2D(gain_maps_[img_idx], gain_maps_[img_idx], CV_32F, ker, ker);
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sepFilter2D(gain_maps_[img_idx], gain_maps_[img_idx], CV_32F, ker, ker);
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}
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}
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void BlocksGainCompensator::apply(int index, Point /*corner*/, Mat &image, const Mat &/*mask*/)
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{
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CV_Assert(image.type() == CV_8UC3);
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Mat_<float> gain_map;
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if (gain_maps_[index].size() == image.size())
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gain_map = gain_maps_[index];
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else
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resize(gain_maps_[index], gain_map, image.size(), 0, 0, INTER_LINEAR);
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for (int y = 0; y < image.rows; ++y)
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{
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const float* gain_row = gain_map.ptr<float>(y);
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Point3_<uchar>* row = image.ptr<Point3_<uchar> >(y);
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for (int x = 0; x < image.cols; ++x)
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{
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row[x].x = saturate_cast<uchar>(row[x].x * gain_row[x]);
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row[x].y = saturate_cast<uchar>(row[x].y * gain_row[x]);
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row[x].z = saturate_cast<uchar>(row[x].z * gain_row[x]);
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}
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}
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}
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@ -48,7 +48,7 @@
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class ExposureCompensator
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{
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public:
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enum { NO, OVERLAP, SEGMENT };
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enum { NO, GAIN, GAIN_BLOCKS };
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static cv::Ptr<ExposureCompensator> createDefault(int type);
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void feed(const std::vector<cv::Point> &corners, const std::vector<cv::Mat> &images,
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@ -68,14 +68,31 @@ public:
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};
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class OverlapExposureCompensator : public ExposureCompensator
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class GainCompensator : public ExposureCompensator
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{
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public:
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void feed(const std::vector<cv::Point> &corners, const std::vector<cv::Mat> &images,
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const std::vector<std::pair<cv::Mat,uchar> > &masks);
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void apply(int index, cv::Point corner, cv::Mat &image, const cv::Mat &mask);
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std::vector<double> gains() const;
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cv::Mat_<double> gains;
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private:
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cv::Mat_<double> gains_;
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};
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class BlocksGainCompensator : public ExposureCompensator
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{
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public:
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BlocksGainCompensator(int bl_width = 32, int bl_height = 32)
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: bl_width_(bl_width), bl_height_(bl_height) {}
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void feed(const std::vector<cv::Point> &corners, const std::vector<cv::Mat> &images,
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const std::vector<std::pair<cv::Mat,uchar> > &masks);
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void apply(int index, cv::Point corner, cv::Mat &image, const cv::Mat &mask);
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private:
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int bl_width_, bl_height_;
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std::vector<cv::Mat_<float> > gain_maps_;
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};
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#endif // __OPENCV_EXPOSURE_COMPENSATE_HPP__
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@ -41,10 +41,12 @@
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//M*/
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// We follow to methods described in these two papers:
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// - Heung-Yeung Shum and Richard Szeliski.
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// Construction of panoramic mosaics with global and local alignment. 2000.
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// - Matthew Brown and David G. Lowe.
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// Automatic Panoramic Image Stitching using Invariant Features. 2007.
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// 1) Construction of panoramic mosaics with global and local alignment.
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// Heung-Yeung Shum and Richard Szeliski. 2000.
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// 2) Eliminating Ghosting and Exposure Artifacts in Image Mosaics.
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// Matthew Uyttendaele, Ashley Eden and Richard Szeliski. 2001.
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// 3) Automatic Panoramic Image Stitching using Invariant Features.
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// Matthew Brown and David G. Lowe. 2007.
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#include "precomp.hpp"
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#include "util.hpp"
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@ -59,45 +61,63 @@ using namespace cv;
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void printUsage()
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{
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cout << "Rotation model images stitcher.\n\n";
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cout << "Usage: opencv_stitching img1 img2 [...imgN]\n"
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<< "\t[--trygpu (yes|no)]\n"
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<< "\t[--work_megapix <float>]\n"
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<< "\t[--seam_megapix <float>]\n"
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<< "\t[--compose_megapix <float>]\n"
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<< "\t[--match_conf <float>]\n"
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<< "\t[--ba (ray|focal_ray)]\n"
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<< "\t[--conf_thresh <float>]\n"
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<< "\t[--wavecorrect (no|yes)]\n"
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<< "\t[--warp (plane|cylindrical|spherical)]\n"
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<< "\t[--exposcomp (no|overlap)]\n"
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<< "\t[--seam (no|voronoi|gc_color|gc_colorgrad)]\n"
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<< "\t[--blend (no|feather|multiband)]\n"
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<< "\t[--numbands <int>]\n"
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<< "\t[--output <result_img>]\n\n";
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cout << "--match_conf\n"
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<< "\tGood values are in [0.2, 0.8] range usually.\n\n";
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cout << "HINT:\n"
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<< "\tTry bigger values for --work_megapix if something is wrong.\n\n";
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cout <<
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"Rotation model images stitcher.\n\n"
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"opencv_stitching img1 img2 [...imgN] [flags]\n\n"
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"Flags:\n"
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" --preview\n"
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" Run stitching in the preview mode. Works faster than usual mode,\n"
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" but output image will have lower resolution.\n"
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" --try_gpu (yes|no)\n"
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" Try to use GPU. The default value is 'no'. All default values\n"
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" are for CPU mode.\n"
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" --work_megapix <float>\n"
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" Resolution for image registration step. The default is 0.6.\n"
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" --seam_megapix <float>\n"
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" Resolution for seam estimation step. The default is 0.1.\n"
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" --compose_megapix <float>\n"
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" Resolution for compositing step. Use -1 for original resolution.\n"
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" The default is -1.\n"
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" --match_conf <float>\n"
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" Confidence for feature matching step. The default is 0.6.\n"
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" --ba (ray|focal_ray)\n"
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" Bundle adjustment cost function. The default is 'focal_ray'.\n"
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" --conf_thresh <float>\n"
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" Threshold for two images are from the same panorama confidence.\n"
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" The default is 'focal_ray'.\n"
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" --wave_correct (no|yes)\n"
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" Perform wave effect correction. The default is 'yes'.\n"
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" --warp (plane|cylindrical|spherical)\n"
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" Warp surface type. The default is 'spherical'.\n"
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" --expos_comp (no|gain|gain_blocks)\n"
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" Exposure compensation method. The default is 'gain'.\n"
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" --seam (no|voronoi|gc_color|gc_colorgrad)\n"
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" Seam estimation method. The default is 'gc_color'.\n"
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" --blend (no|feather|multiband)\n"
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" Blending method. The default is 'multiband'.\n"
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" --num_bands <int>\n"
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" Number of bands for multi-band blending method. The default is 5.\n"
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" --output <result_img>\n";
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}
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// Default command line args
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vector<string> img_names;
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bool trygpu = false;
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bool preview = false;
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bool try_gpu = false;
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double work_megapix = 0.6;
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double seam_megapix = 0.1;
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double compose_megapix = 1;
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double compose_megapix = -1;
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int ba_space = BundleAdjuster::FOCAL_RAY_SPACE;
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float conf_thresh = 1.f;
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bool wave_correct = true;
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int warp_type = Warper::SPHERICAL;
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int expos_comp_type = ExposureCompensator::OVERLAP;
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int expos_comp_type = ExposureCompensator::GAIN;
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bool user_match_conf = false;
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float match_conf = 0.6f;
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int seam_find_type = SeamFinder::GC_COLOR;
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int blend_type = Blender::MULTI_BAND;
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int numbands = 5;
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int num_bands = 5;
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string result_name = "result.png";
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int parseCmdArgs(int argc, char** argv)
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@ -107,18 +127,21 @@ int parseCmdArgs(int argc, char** argv)
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printUsage();
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return -1;
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}
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for (int i = 1; i < argc; ++i)
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{
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if (string(argv[i]) == "--trygpu")
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if (string(argv[i]) == "--preview")
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{
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preview = true;
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}
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else if (string(argv[i]) == "--try_gpu")
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{
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if (string(argv[i + 1]) == "no")
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trygpu = false;
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try_gpu = false;
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else if (string(argv[i + 1]) == "yes")
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trygpu = true;
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try_gpu = true;
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else
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{
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cout << "Bad --trygpu flag value\n";
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cout << "Bad --try_gpu flag value\n";
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return -1;
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}
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i++;
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@ -167,7 +190,7 @@ int parseCmdArgs(int argc, char** argv)
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conf_thresh = static_cast<float>(atof(argv[i + 1]));
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i++;
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}
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else if (string(argv[i]) == "--wavecorrect")
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else if (string(argv[i]) == "--wave_correct")
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{
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if (string(argv[i + 1]) == "no")
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wave_correct = false;
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@ -175,7 +198,7 @@ int parseCmdArgs(int argc, char** argv)
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wave_correct = true;
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else
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{
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cout << "Bad --wavecorrect flag value\n";
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cout << "Bad --wave_correct flag value\n";
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return -1;
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}
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i++;
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@ -195,12 +218,14 @@ int parseCmdArgs(int argc, char** argv)
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}
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i++;
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}
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else if (string(argv[i]) == "--exposcomp")
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else if (string(argv[i]) == "--expos_comp")
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{
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if (string(argv[i + 1]) == "no")
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expos_comp_type = ExposureCompensator::NO;
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else if (string(argv[i + 1]) == "overlap")
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expos_comp_type = ExposureCompensator::OVERLAP;
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else if (string(argv[i + 1]) == "gain")
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expos_comp_type = ExposureCompensator::GAIN;
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else if (string(argv[i + 1]) == "gain_blocks")
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expos_comp_type = ExposureCompensator::GAIN_BLOCKS;
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else
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{
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cout << "Bad exposure compensation method\n";
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@ -240,9 +265,9 @@ int parseCmdArgs(int argc, char** argv)
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}
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i++;
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}
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else if (string(argv[i]) == "--numbands")
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else if (string(argv[i]) == "--num_bands")
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{
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numbands = atoi(argv[i + 1]);
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num_bands = atoi(argv[i + 1]);
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i++;
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}
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else if (string(argv[i]) == "--output")
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@ -253,6 +278,10 @@ int parseCmdArgs(int argc, char** argv)
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else
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img_names.push_back(argv[i]);
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}
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if (preview)
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{
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compose_megapix = work_megapix;
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}
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return 0;
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}
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@ -281,7 +310,7 @@ int main(int argc, char* argv[])
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int64 t = getTickCount();
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vector<ImageFeatures> features(num_images);
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SurfFeaturesFinder finder(trygpu);
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SurfFeaturesFinder finder(try_gpu);
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Mat full_img, img;
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vector<Mat> images(num_images);
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@ -333,9 +362,9 @@ int main(int argc, char* argv[])
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LOGLN("Pairwise matching... ");
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t = getTickCount();
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vector<MatchesInfo> pairwise_matches;
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BestOf2NearestMatcher matcher(trygpu);
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BestOf2NearestMatcher matcher(try_gpu);
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if (user_match_conf)
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matcher = BestOf2NearestMatcher(trygpu, match_conf);
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matcher = BestOf2NearestMatcher(try_gpu, match_conf);
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matcher(features, pairwise_matches);
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LOGLN("Pairwise matching, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
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@ -533,7 +562,7 @@ int main(int argc, char* argv[])
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if (blend_type == Blender::MULTI_BAND)
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{
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MultiBandBlender* mb = dynamic_cast<MultiBandBlender*>(static_cast<Blender*>(blender));
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mb->setNumBands(numbands);
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mb->setNumBands(num_bands);
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}
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blender->prepare(corners, sizes);
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}
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|
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Reference in New Issue
Block a user