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376 lines
13 KiB
376 lines
13 KiB
/*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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