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Shape module added
This commit is contained in:
Juan Manuel Perez
committed by
Vadim Pisarevsky
Vadim Pisarevsky
parent
4b203f7b1a
commit
61c27ac81e
@@ -0,0 +1,288 @@
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/*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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// 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 double 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(matches.size(),2,CV_32F); // transforming shape
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Mat shape2(matches.size(),2,CV_32F); // target shape
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for (size_t i=0; i<matches.size(); 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(matches.size(),matches.size(),CV_32F);
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Mat matP(matches.size(),3,CV_32F);
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for (size_t i=0; i<matches.size(); i++)
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{
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for (size_t j=0; j<matches.size(); 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)=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(matches.size()+3,matches.size()+3,CV_32F);
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Mat matLroi(matL, Rect(0,0,matches.size(),matches.size())); //roi for K
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matK.copyTo(matLroi);
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matLroi = Mat(matL,Rect(matches.size(),0,3,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,matches.size(),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(matches.size()+3,2,CV_32F);
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for (size_t i=0; i<matches.size(); 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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