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288 lines
10 KiB
288 lines
10 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 "precomp.hpp" |
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namespace cv |
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{ |
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class ThinPlateSplineShapeTransformerImpl : public ThinPlateSplineShapeTransformer |
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{ |
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public: |
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/* Constructors */ |
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ThinPlateSplineShapeTransformerImpl() |
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{ |
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regularizationParameter=0; |
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name_ = "ShapeTransformer.TPS"; |
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tpsComputed=false; |
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} |
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ThinPlateSplineShapeTransformerImpl(double _regularizationParameter) |
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{ |
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regularizationParameter=_regularizationParameter; |
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name_ = "ShapeTransformer.TPS"; |
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tpsComputed=false; |
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} |
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/* Destructor */ |
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~ThinPlateSplineShapeTransformerImpl() |
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{ |
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} |
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virtual AlgorithmInfo* info() const { return 0; } |
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//! the main operators |
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virtual void estimateTransformation(InputArray transformingShape, InputArray targetShape, std::vector<DMatch> &matches); |
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virtual float applyTransformation(InputArray inPts, OutputArray output=noArray()); |
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virtual void warpImage(InputArray transformingImage, OutputArray output, |
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int flags, int borderMode, const Scalar& borderValue) const; |
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//! Setters/Getters |
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virtual void setRegularizationParameter(double _regularizationParameter) {regularizationParameter=_regularizationParameter;} |
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virtual double getRegularizationParameter() const {return regularizationParameter;} |
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//! write/read |
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virtual void write(FileStorage& fs) const |
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{ |
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fs << "name" << name_ |
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<< "regularization" << regularizationParameter; |
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} |
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virtual void read(const FileNode& fn) |
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{ |
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CV_Assert( (String)fn["name"] == name_ ); |
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regularizationParameter = (int)fn["regularization"]; |
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} |
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private: |
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bool tpsComputed; |
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double regularizationParameter; |
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float transformCost; |
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Mat tpsParameters; |
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Mat shapeReference; |
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protected: |
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String name_; |
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}; |
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static float distance(Point2f p, Point2f q) |
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{ |
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Point2f diff = p - q; |
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float norma = diff.x*diff.x + diff.y*diff.y;// - 2*diff.x*diff.y; |
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if (norma<0) norma=0; |
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//else norma = std::sqrt(norma); |
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norma = norma*std::log(norma+FLT_EPSILON); |
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return norma; |
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} |
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static Point2f _applyTransformation(const Mat &shapeRef, const Point2f point, const Mat &tpsParameters) |
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{ |
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Point2f out; |
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for (int i=0; i<2; i++) |
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{ |
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float a1=tpsParameters.at<float>(tpsParameters.rows-3,i); |
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float ax=tpsParameters.at<float>(tpsParameters.rows-2,i); |
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float ay=tpsParameters.at<float>(tpsParameters.rows-1,i); |
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float affine=a1+ax*point.x+ay*point.y; |
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float nonrigid=0; |
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for (int j=0; j<shapeRef.rows; j++) |
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{ |
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nonrigid+=tpsParameters.at<float>(j,i)* |
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distance(Point2f(shapeRef.at<float>(j,0),shapeRef.at<float>(j,1)), |
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point); |
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} |
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if (i==0) |
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{ |
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out.x=affine+nonrigid; |
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} |
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if (i==1) |
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{ |
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out.y=affine+nonrigid; |
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} |
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} |
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return out; |
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} |
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/* public methods */ |
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void ThinPlateSplineShapeTransformerImpl::warpImage(InputArray transformingImage, OutputArray output, |
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int flags, int borderMode, const Scalar& borderValue) const |
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{ |
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CV_Assert(tpsComputed==true); |
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Mat theinput = transformingImage.getMat(); |
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Mat mapX(theinput.rows, theinput.cols, CV_32FC1); |
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Mat mapY(theinput.rows, theinput.cols, CV_32FC1); |
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for (int row = 0; row < theinput.rows; row++) |
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{ |
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for (int col = 0; col < theinput.cols; col++) |
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{ |
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Point2f pt = _applyTransformation(shapeReference, Point2f(float(col), float(row)), tpsParameters); |
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mapX.at<float>(row, col) = pt.x; |
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mapY.at<float>(row, col) = pt.y; |
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} |
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} |
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remap(transformingImage, output, mapX, mapY, flags, borderMode, borderValue); |
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} |
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float ThinPlateSplineShapeTransformerImpl::applyTransformation(InputArray inPts, OutputArray outPts) |
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{ |
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CV_Assert(tpsComputed); |
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Mat pts1 = inPts.getMat(); |
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CV_Assert((pts1.channels()==2) && (pts1.cols>0)); |
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//Apply transformation in the complete set of points |
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// Ensambling output // |
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if (outPts.needed()) |
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{ |
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outPts.create(1,pts1.cols, CV_32FC2); |
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Mat outMat = outPts.getMat(); |
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for (int i=0; i<pts1.cols; i++) |
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{ |
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Point2f pt=pts1.at<Point2f>(0,i); |
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outMat.at<Point2f>(0,i)=_applyTransformation(shapeReference, pt, tpsParameters); |
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} |
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} |
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return transformCost; |
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} |
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void ThinPlateSplineShapeTransformerImpl::estimateTransformation(InputArray _pts1, InputArray _pts2, |
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std::vector<DMatch>& _matches ) |
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{ |
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Mat pts1 = _pts1.getMat(); |
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Mat pts2 = _pts2.getMat(); |
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CV_Assert((pts1.channels()==2) && (pts1.cols>0) && (pts2.channels()==2) && (pts2.cols>0)); |
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CV_Assert(_matches.size()>1); |
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if (pts1.type() != CV_32F) |
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pts1.convertTo(pts1, CV_32F); |
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if (pts2.type() != CV_32F) |
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pts2.convertTo(pts2, CV_32F); |
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// Use only valid matchings // |
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std::vector<DMatch> matches; |
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for (size_t i=0; i<_matches.size(); i++) |
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{ |
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if (_matches[i].queryIdx<pts1.cols && |
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_matches[i].trainIdx<pts2.cols) |
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{ |
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matches.push_back(_matches[i]); |
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} |
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} |
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// Organizing the correspondent points in matrix style // |
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Mat shape1((int)matches.size(),2,CV_32F); // transforming shape |
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Mat shape2((int)matches.size(),2,CV_32F); // target shape |
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for (int i=0, end = (int)matches.size(); i<end; i++) |
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{ |
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Point2f pt1=pts1.at<Point2f>(0,matches[i].queryIdx); |
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shape1.at<float>(i,0) = pt1.x; |
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shape1.at<float>(i,1) = pt1.y; |
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Point2f pt2=pts2.at<Point2f>(0,matches[i].trainIdx); |
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shape2.at<float>(i,0) = pt2.x; |
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shape2.at<float>(i,1) = pt2.y; |
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} |
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shape1.copyTo(shapeReference); |
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// Building the matrices for solving the L*(w|a)=(v|0) problem with L={[K|P];[P'|0]} |
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//Building K and P (Neede to buil L) |
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Mat matK((int)matches.size(),(int)matches.size(),CV_32F); |
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Mat matP((int)matches.size(),3,CV_32F); |
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for (int i=0, end=(int)matches.size(); i<end; i++) |
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{ |
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for (int j=0; j<end; j++) |
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{ |
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if (i==j) |
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{ |
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matK.at<float>(i,j)=float(regularizationParameter); |
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} |
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else |
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{ |
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matK.at<float>(i,j) = distance(Point2f(shape1.at<float>(i,0),shape1.at<float>(i,1)), |
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Point2f(shape1.at<float>(j,0),shape1.at<float>(j,1))); |
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} |
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} |
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matP.at<float>(i,0) = 1; |
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matP.at<float>(i,1) = shape1.at<float>(i,0); |
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matP.at<float>(i,2) = shape1.at<float>(i,1); |
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} |
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//Building L |
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Mat matL=Mat::zeros((int)matches.size()+3,(int)matches.size()+3,CV_32F); |
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Mat matLroi(matL, Rect(0,0,(int)matches.size(),(int)matches.size())); //roi for K |
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matK.copyTo(matLroi); |
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matLroi = Mat(matL,Rect((int)matches.size(),0,3,(int)matches.size())); //roi for P |
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matP.copyTo(matLroi); |
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Mat matPt; |
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transpose(matP,matPt); |
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matLroi = Mat(matL,Rect(0,(int)matches.size(),(int)matches.size(),3)); //roi for P' |
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matPt.copyTo(matLroi); |
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//Building B (v|0) |
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Mat matB = Mat::zeros((int)matches.size()+3,2,CV_32F); |
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for (int i=0, end = (int)matches.size(); i<end; i++) |
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{ |
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matB.at<float>(i,0) = shape2.at<float>(i,0); //x's |
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matB.at<float>(i,1) = shape2.at<float>(i,1); //y's |
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} |
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//Obtaining transformation params (w|a) |
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solve(matL, matB, tpsParameters, DECOMP_LU); |
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//tpsParameters = matL.inv()*matB; |
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//Setting transform Cost and Shape reference |
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Mat w(tpsParameters, Rect(0,0,2,tpsParameters.rows-3)); |
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Mat Q=w.t()*matK*w; |
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transformCost=fabs(Q.at<float>(0,0)*Q.at<float>(1,1));//fabs(mean(Q.diag(0))[0]);//std::max(Q.at<float>(0,0),Q.at<float>(1,1)); |
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tpsComputed=true; |
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} |
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Ptr <ThinPlateSplineShapeTransformer> createThinPlateSplineShapeTransformer(double regularizationParameter) |
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{ |
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return Ptr<ThinPlateSplineShapeTransformer>( new ThinPlateSplineShapeTransformerImpl(regularizationParameter) ); |
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} |
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} // cv
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