377 lines
13 KiB
C++
377 lines
13 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "blenders.hpp"
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#include "util.hpp"
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using namespace std;
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using namespace cv;
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static const float WEIGHT_EPS = 1e-5f;
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Ptr<Blender> Blender::createDefault(int type, bool try_gpu)
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{
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if (type == NO)
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return new Blender();
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if (type == FEATHER)
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return new FeatherBlender();
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if (type == MULTI_BAND)
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return new MultiBandBlender(try_gpu);
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CV_Error(CV_StsBadArg, "unsupported blending method");
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return NULL;
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}
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void Blender::prepare(const vector<Point> &corners, const vector<Size> &sizes)
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{
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prepare(resultRoi(corners, sizes));
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}
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void Blender::prepare(Rect dst_roi)
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{
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dst_.create(dst_roi.size(), CV_16SC3);
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dst_.setTo(Scalar::all(0));
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dst_mask_.create(dst_roi.size(), CV_8U);
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dst_mask_.setTo(Scalar::all(0));
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dst_roi_ = dst_roi;
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}
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void Blender::feed(const Mat &img, const Mat &mask, Point tl)
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{
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CV_Assert(img.type() == CV_16SC3);
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CV_Assert(mask.type() == CV_8U);
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int dx = tl.x - dst_roi_.x;
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int dy = tl.y - dst_roi_.y;
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for (int y = 0; y < img.rows; ++y)
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{
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const Point3_<short> *src_row = img.ptr<Point3_<short> >(y);
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Point3_<short> *dst_row = dst_.ptr<Point3_<short> >(dy + y);
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const uchar *mask_row = mask.ptr<uchar>(y);
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uchar *dst_mask_row = dst_mask_.ptr<uchar>(dy + y);
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for (int x = 0; x < img.cols; ++x)
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{
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if (mask_row[x])
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dst_row[dx + x] = src_row[x];
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dst_mask_row[dx + x] |= mask_row[x];
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}
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}
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}
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void Blender::blend(Mat &dst, Mat &dst_mask)
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{
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dst_.setTo(Scalar::all(0), dst_mask_ == 0);
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dst = dst_;
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dst_mask = dst_mask_;
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dst_.release();
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dst_mask_.release();
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}
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void FeatherBlender::prepare(Rect dst_roi)
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{
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Blender::prepare(dst_roi);
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dst_weight_map_.create(dst_roi.size(), CV_32F);
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dst_weight_map_.setTo(0);
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}
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void FeatherBlender::feed(const Mat &img, const Mat &mask, Point tl)
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{
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CV_Assert(img.type() == CV_16SC3);
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CV_Assert(mask.type() == CV_8U);
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createWeightMap(mask, sharpness_, weight_map_);
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int dx = tl.x - dst_roi_.x;
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int dy = tl.y - dst_roi_.y;
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for (int y = 0; y < img.rows; ++y)
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{
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const Point3_<short>* src_row = img.ptr<Point3_<short> >(y);
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Point3_<short>* dst_row = dst_.ptr<Point3_<short> >(dy + y);
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const float* weight_row = weight_map_.ptr<float>(y);
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float* dst_weight_row = dst_weight_map_.ptr<float>(dy + y);
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for (int x = 0; x < img.cols; ++x)
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{
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dst_row[dx + x].x += static_cast<short>(src_row[x].x * weight_row[x]);
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dst_row[dx + x].y += static_cast<short>(src_row[x].y * weight_row[x]);
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dst_row[dx + x].z += static_cast<short>(src_row[x].z * weight_row[x]);
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dst_weight_row[dx + x] += weight_row[x];
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}
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}
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}
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void FeatherBlender::blend(Mat &dst, Mat &dst_mask)
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{
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normalize(dst_weight_map_, dst_);
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dst_mask_ = dst_weight_map_ > WEIGHT_EPS;
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Blender::blend(dst, dst_mask);
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}
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MultiBandBlender::MultiBandBlender(int try_gpu, int num_bands)
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{
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setNumBands(num_bands);
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can_use_gpu_ = try_gpu && gpu::getCudaEnabledDeviceCount();
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}
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void MultiBandBlender::prepare(Rect dst_roi)
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{
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dst_roi_final_ = dst_roi;
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// Crop unnecessary bands
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double max_len = static_cast<double>(max(dst_roi.width, dst_roi.height));
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num_bands_ = min(actual_num_bands_, static_cast<int>(ceil(log(max_len) / log(2.0))));
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// Add border to the final image, to ensure sizes are divided by (1 << num_bands_)
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dst_roi.width += ((1 << num_bands_) - dst_roi.width % (1 << num_bands_)) % (1 << num_bands_);
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dst_roi.height += ((1 << num_bands_) - dst_roi.height % (1 << num_bands_)) % (1 << num_bands_);
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Blender::prepare(dst_roi);
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dst_pyr_laplace_.resize(num_bands_ + 1);
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dst_pyr_laplace_[0] = dst_;
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dst_band_weights_.resize(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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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, CV_16SC3);
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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_pyr_laplace_[i].setTo(Scalar::all(0));
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dst_band_weights_[i].setTo(0);
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}
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}
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void MultiBandBlender::feed(const Mat &img, const Mat &mask, Point tl)
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{
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CV_Assert(img.type() == CV_16SC3);
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CV_Assert(mask.type() == CV_8U);
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// Keep source image in memory with small border
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int gap = 3 * (1 << num_bands_);
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Point tl_new(max(dst_roi_.x, tl.x - gap),
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max(dst_roi_.y, tl.y - gap));
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Point br_new(min(dst_roi_.br().x, tl.x + img.cols + gap),
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min(dst_roi_.br().y, tl.y + img.rows + gap));
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// Ensure coordinates of top-left, bottom-right corners are divided by (1 << num_bands_).
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// After that scale between layers is exactly 2.
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//
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// We do it to avoid interpolation problems when keeping sub-images only. There is no such problem when
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// image is bordered to have size equal to the final image size, but this is too memory hungry approach.
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tl_new.x = dst_roi_.x + (((tl_new.x - dst_roi_.x) >> num_bands_) << num_bands_);
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tl_new.y = dst_roi_.y + (((tl_new.y - dst_roi_.y) >> num_bands_) << num_bands_);
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int width = br_new.x - tl_new.x;
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int height = br_new.y - tl_new.y;
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width += ((1 << num_bands_) - width % (1 << num_bands_)) % (1 << num_bands_);
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height += ((1 << num_bands_) - height % (1 << num_bands_)) % (1 << num_bands_);
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br_new.x = tl_new.x + width;
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br_new.y = tl_new.y + height;
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int dy = max(br_new.y - dst_roi_.br().y, 0);
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int dx = max(br_new.x - dst_roi_.br().x, 0);
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tl_new.x -= dx; br_new.x -= dx;
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tl_new.y -= dy; br_new.y -= dy;
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int top = tl.y - tl_new.y;
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int left = tl.x - tl_new.x;
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int bottom = br_new.y - tl.y - img.rows;
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int right = br_new.x - tl.x - img.cols;
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// Create the source image Laplacian pyramid
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Mat img_with_border;
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copyMakeBorder(img, img_with_border, top, bottom, left, right,
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BORDER_REFLECT);
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vector<Mat> src_pyr_laplace;
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createLaplacePyr(img_with_border, num_bands_, src_pyr_laplace);
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// Create the weight map Gaussian pyramid
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Mat weight_map;
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mask.convertTo(weight_map, CV_32F, 1./255.);
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vector<Mat> weight_pyr_gauss(num_bands_ + 1);
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copyMakeBorder(weight_map, weight_pyr_gauss[0], top, bottom, left, right,
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BORDER_CONSTANT);
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for (int i = 0; i < num_bands_; ++i)
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pyrDown(weight_pyr_gauss[i], weight_pyr_gauss[i + 1]);
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int y_tl = tl_new.y - dst_roi_.y;
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int y_br = br_new.y - dst_roi_.y;
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int x_tl = tl_new.x - dst_roi_.x;
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int x_br = br_new.x - dst_roi_.x;
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// Add weighted layer of the source image to the final Laplacian pyramid layer
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for (int i = 0; i <= num_bands_; ++i)
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{
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for (int y = y_tl; y < y_br; ++y)
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{
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int y_ = y - y_tl;
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const Point3_<short>* src_row = src_pyr_laplace[i].ptr<Point3_<short> >(y_);
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Point3_<short>* dst_row = dst_pyr_laplace_[i].ptr<Point3_<short> >(y);
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const float* weight_row = weight_pyr_gauss[i].ptr<float>(y_);
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float* dst_weight_row = dst_band_weights_[i].ptr<float>(y);
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for (int x = x_tl; x < x_br; ++x)
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{
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int x_ = x - x_tl;
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dst_row[x].x += static_cast<short>(src_row[x_].x * weight_row[x_]);
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dst_row[x].y += static_cast<short>(src_row[x_].y * weight_row[x_]);
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dst_row[x].z += static_cast<short>(src_row[x_].z * weight_row[x_]);
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dst_weight_row[x] += weight_row[x_];
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}
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}
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x_tl /= 2; y_tl /= 2;
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x_br /= 2; y_br /= 2;
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}
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}
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void MultiBandBlender::blend(Mat &dst, Mat &dst_mask)
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{
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for (int i = 0; i <= num_bands_; ++i)
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normalize(dst_band_weights_[i], dst_pyr_laplace_[i]);
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restoreImageFromLaplacePyr(dst_pyr_laplace_);
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dst_ = dst_pyr_laplace_[0];
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dst_ = dst_(Range(0, dst_roi_final_.height), Range(0, dst_roi_final_.width));
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dst_mask_ = dst_band_weights_[0] > WEIGHT_EPS;
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dst_mask_ = dst_mask_(Range(0, dst_roi_final_.height), Range(0, dst_roi_final_.width));
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dst_pyr_laplace_.clear();
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dst_band_weights_.clear();
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Blender::blend(dst, dst_mask);
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}
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//////////////////////////////////////////////////////////////////////////////
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// Auxiliary functions
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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_16SC3);
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for (int y = 0; y < src.rows; ++y)
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{
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Point3_<short> *row = src.ptr<Point3_<short> >(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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{
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row[x].x = static_cast<short>(row[x].x / (weight_row[x] + WEIGHT_EPS));
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row[x].y = static_cast<short>(row[x].y / (weight_row[x] + WEIGHT_EPS));
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row[x].z = static_cast<short>(row[x].z / (weight_row[x] + WEIGHT_EPS));
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}
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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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distanceTransform(mask, weight, CV_DIST_L1, 3);
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threshold(weight * sharpness, weight, 1.f, 1.f, THRESH_TRUNC);
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}
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void createLaplacePyr(const Mat &img, int num_levels, vector<Mat> &pyr)
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{
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pyr.resize(num_levels + 1);
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pyr[0] = img;
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for (int i = 0; i < num_levels; ++i)
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pyrDown(pyr[i], pyr[i + 1]);
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Mat tmp;
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for (int i = 0; i < num_levels; ++i)
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{
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pyrUp(pyr[i + 1], tmp, pyr[i].size());
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subtract(pyr[i], tmp, pyr[i]);
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}
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}
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#if 0
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void createLaplacePyrGpu(const Mat &img, int num_levels, vector<Mat> &pyr)
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{
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pyr.resize(num_levels + 1);
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vector<gpu::GpuMat> gpu_pyr(num_levels + 1);
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gpu_pyr[0] = img;
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for (int i = 0; i < num_levels; ++i)
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gpu::pyrDown(gpu_pyr[i], gpu_pyr[i + 1]);
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gpu::GpuMat tmp;
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for (int i = 0; i < num_levels; ++i)
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{
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gpu::pyrUp(gpu_pyr[i + 1], tmp);
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gpu::subtract(gpu_pyr[i], tmp, gpu_pyr[i]);
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pyr[i] = gpu_pyr[i];
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}
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pyr[num_levels] = gpu_pyr[num_levels];
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}
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#endif
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void restoreImageFromLaplacePyr(vector<Mat> &pyr)
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{
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if (pyr.size() == 0)
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return;
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Mat tmp;
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for (size_t i = pyr.size() - 1; i > 0; --i)
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{
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pyrUp(pyr[i], tmp, pyr[i - 1].size());
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add(tmp, pyr[i - 1], pyr[i - 1]);
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}
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}
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