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/*! \file ImageCompareModel.h
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Copyright (C) 2014 Hangzhou Leaper.
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Created by bang.jin at 2017/02/04.
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*/
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#pragma once
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#include <opencv2/opencv.hpp>
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#include <opencv2/opencv_modules.hpp>
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#include <string>
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#include <map>
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#include <set>
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#include <fstream>
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#include "MultiScaleObj.h"
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using std::set;
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using std::map;
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using std::fstream;
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using std::string;
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using namespace cv;
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class MultiScaleImageCompareModel;
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class ImageCompareModel
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{
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public:
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class RotateMatchResult
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{
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public:
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Mat mBestRImg;
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double mBestAngle;
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};
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class RotateData
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{
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public:
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RotateData() {};
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RotateData(const Mat &img, Point pt, double dAngleStep, int size)
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: mImgSrc(img)
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, mStartAngle(0)
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, mEndAngle(360)
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{
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init(img, pt, dAngleStep, size);
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};
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void init(const Mat& img, Point pt, double dAngleStep, int size)
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{
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mImgSrc = img;
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mStartAngle = 0;
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mEndAngle = 360.0;
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mRImgVec.clear();
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mRImgVec.resize(size);
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mDisValVec.clear();
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mDisValVec.resize(size, FLT_MAX);
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mCenter = pt;
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mAngleStep = dAngleStep;
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}
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double angle(int index)
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{
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return index*mAngleStep + mStartAngle;
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}
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double bestAngle()
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{
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if (mDisValVec.empty())
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{
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return -DBL_MAX;
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}
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size_t bestIndex = min_element(mDisValVec.begin(),
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mDisValVec.end()) - mDisValVec.begin();
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double bestAngle = angle(bestIndex);
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return bestAngle;
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}
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Mat bestRImg()
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{
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if (mRImgVec.empty())
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{
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return Mat();
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}
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size_t bestIndex = min_element(mDisValVec.begin(),
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mDisValVec.end()) - mDisValVec.begin();
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return mRImgVec[bestIndex];
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}
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double mAngleStep;
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Mat mImgSrc;
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Point mCenter;
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vector<Mat> mRImgVec;
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vector<float> mDisValVec;
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float mStartAngle, mEndAngle;
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};
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public:
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static cv::Point2f refineCircleCen(const Mat& img, Point2f cen);
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static Mat genWeightImage(const Mat& img, Point2f center, float innerR = -1,
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float outterR = -1);
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static void selfRotationSimilarityFeature(const Mat& img,
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vector<float>& vec, Point2f cen = Point2f(-1, -1));
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static Mat genMask(const Mat& img, Point2f center, float innerR = -1,
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float outterR = -1,
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int type = CV_32FC1);
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static void genCandidateRepeatNums(set<unsigned int>& canNums);
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static int computeRepeatNum(const Mat& img);
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static int recognizeLowerExtremes(const Mat& vec, set<unsigned int> canNums, int extremeRefineRange = 5, vector<int> *pExtemeIdxVec = 0);
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static int recognizeRepeatedLocalExtremas(const Mat& vec, const set<unsigned int>& canNums, int extremeRefineRange = 5, vector<int> *pExtremeIdxVec = 0);
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static void genUniformSepIdx(int num, int startIdx, int endIdx, vector<int>& cenVec);
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static void genAngleRanges(vector<int> cenVec, vector<Range>& rangeVec, int localRange);
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static void genCandidateAngleRanges(vector<float> disVec,
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float angleStep, vector<Range>& rangeVec);
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static void genCandidateAngleRanges(const Mat& disMat, float angleStep,
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vector<Range>& rangeVec, float rangeScale = 1);
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static void selfRotateMin(const Mat& img, Mat& weightMat, int repeatNum);
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public:
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ImageCompareModel() :
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mMatchValScale(1.0),
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mTargetMeanVal(127),
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mTargetStddevVal(50),
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mHighlightsThreshold(256),
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mRepeatNum(0),
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mName("unnamed"),
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mDisThre(DBL_MAX),
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mTrueSampleDisMin(DBL_MAX),
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mTrueSampleDisMax(DBL_MIN),
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mTrueSampleDisMean(-1),
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mTrueSampleDisStddev(-1),
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mIsEnableCache(false),
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mpMultiScaleModel(NULL),
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meanDiameter(0)
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{};
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ImageCompareModel(const ImageCompareModel& model)
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: mAlignBaseImg(model.getBaseImg().clone())
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, mWeightMat(model.getWeightMat().clone())
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, mMatchValScale(model.getMatchValScale())
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{
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genMask();
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}
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~ImageCompareModel() {};
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void printInfo();
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void saveImages(string dirPath);
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bool save2file(string filePath);
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bool readFromFile(string filePath);
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void operator = (const ImageCompareModel& model)
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{
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mAlignBaseImg = model.getBaseImg().clone();
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mWeightMat = model.getWeightMat().clone();
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mMatchValScale = model.getMatchValScale();
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mTargetMeanVal = model.getTargetMeanVal();
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mTargetStddevVal = model.getTargetStddevVal();
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mName = model.getName();
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mTrueSampleDisStddev = model.getDisStdDev();
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mTrueSampleDisMean = model.getDisMean();
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mTrueSampleDisMax = model.getDisMax();
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mTrueSampleDisMin = model.getDisMin();
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meanDiameter = model.getMeanDiamter();
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}
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void genMask();
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void preProcessImage(Mat& img) const;
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void preProcessImage(Mat& img, const Mat& mask, double dstMean, double dstStddev, int highlightsThreshold) const;
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void preProcessImage(Mat& img, const Mat& mask, const Mat& weightMat, double dstMean,
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double dstStddev, int highlightsThreshold) const;
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void preProcessImage0(Mat& img) const;
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void weightOptimization(const vector<Mat>& falseSamples);
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//! <20><>һ<EFBFBD><D2BB>ͼ<EFBFBD><CDBC><EFBFBD>ͱ<EFBFBD>ͼmBaseImg<6D><67><EFBFBD><EFBFBD><EFBFBD><EFBFBD>תƥ<D7AA>䣬<EFBFBD><E4A3AC><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ò<EFBFBD><C3B2><EFBFBD>ֵ
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/*!
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\param Mat img <20><><EFBFBD><EFBFBD>ͼ<EFBFBD><CDBC>
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\param Mat * pRImg <20><><EFBFBD><EFBFBD>ͼ<EFBFBD><CDBC><EFBFBD><EFBFBD><EFBFBD><EFBFBD>תƥ<D7AA><C6A5><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
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\param bool isFilterSize <20>Ƿ<EFBFBD><C7B7><EFBFBD><EFBFBD><EFBFBD>ͼ<EFBFBD><CDBC><EFBFBD>ߴ<EFBFBD><DFB4><EFBFBD><EFBFBD><EFBFBD>
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\return double <20><><EFBFBD><EFBFBD>ֵ
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\see compare(Mat, Mat, Mat*, Mat*)
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*/
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double compare(Mat img, Mat* pRImg = NULL, int levelNum = 1, bool isFilterSize = true, int flag = 0);
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//! ѵ<><D1B5><EFBFBD>õ<EFBFBD><C3B5><EFBFBD>ͼ<D7BC><CDBC>mBaseImg
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/*!
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\param const vector<Mat> & imgVec <20><><EFBFBD><EFBFBD>ͬ<EFBFBD><CDAC><EFBFBD><EFBFBD>ѵ<EFBFBD><D1B5><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ͼ
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\return void
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*/
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void train(const vector<Mat>& imgVec);
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void calculateAllParams(const vector<Mat>& imgVec);
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void trueSampleWeightRecon(const vector<Mat>& resizedVec, vector<RotateMatchResult> rmrVec);
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void trueWeightRecon(const Mat& rImg, const Mat& baseImg);
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void weightMapping(const Mat& weight, double maxVal);
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//void falseWeightmapping(Mat &img);
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double descendFunction(double pixVal, double maxVal);
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double penltyCoeff(double matchedVal, int diameterMean, int targetDiameter) const;
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//! <20><><EFBFBD>ݸ<EFBFBD><DDB8><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ֵ<EFBFBD><D6B5><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ж<EFBFBD><D0B6><EFBFBD><EFBFBD><EFBFBD>һ<EFBFBD><D2BB><EFBFBD>µ<EFBFBD>ͼ<EFBFBD><CDBC><EFBFBD>Ƿ<EFBFBD><C7B7><EFBFBD><EFBFBD>ڸ<EFBFBD><DAB8><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
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/*!
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\param const vector<Mat> & imgVec <20><><EFBFBD><EFBFBD><EFBFBD>ڸ<EFBFBD><DAB8><EFBFBD><EFBFBD><EFBFBD>ѵ<EFBFBD><D1B5><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ͼ
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\return void
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*/
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void computeDisThre(const vector<Mat>& imgVec, double* pMinDis = NULL);
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double filterTrainImage(const Mat &img);
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//! <20><><EFBFBD>м<EFBFBD><D0BC><EFBFBD>rotate
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/*!
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\param int index <20><>ǰ<EFBFBD><C7B0><EFBFBD><EFBFBD>index
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\param void *p <20><><EFBFBD><EFBFBD>ָ<EFBFBD><D6B8>
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*/
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void parallelDetect(int index, void *p) const;
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//! <20><>ȡ<EFBFBD><C8A1>ͼ<D7BC><CDBC>
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/*!
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\return cv::Mat <20><>ͼ<D7BC><CDBC>
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*/
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Mat getBaseImg() const { return mAlignBaseImg; }
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void setBaseImg(const Mat& img) { mAlignBaseImg = img; }
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Mat getWeightMat() const { return mWeightMat; }
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void setWeightMat(Mat val) { mWeightMat = val; }
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double getMatchValScale() const { return mMatchValScale; }
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void setMatchValScale(double val) { mMatchValScale = val; }
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int getTargetStddevVal() const { return mTargetStddevVal; }
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void setTargetStddevVal(int val) { mTargetStddevVal = val; }
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int getTargetMeanVal() const { return mTargetMeanVal; }
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void setTargetMeanVal(int val) { mTargetMeanVal = val; }
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int getRepeatNum() const { return mRepeatNum; }
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void setRepeatNum(int val) { mRepeatNum = val; }
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string getName() const { return mName; }
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void setName(string val) { mName = val; }
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double getDisStdDev() const { return mTrueSampleDisStddev; }
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double getDisMean() const { return mTrueSampleDisMean; }
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double getDisMin() const { return mTrueSampleDisMin; }
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double getDisMax() const { return mTrueSampleDisMax; }
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double getFalseSampleMinDis() const { return mFalseSampleMinDis; }
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double getMeanDiamter() const { return meanDiameter; }
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//! <20><>ȡ<EFBFBD><C8A1><EFBFBD><EFBFBD>һ<EFBFBD><D2BB>ִ<EFBFBD><D6B4>readFromFileʱ<65><CAB1><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ļ<EFBFBD>·<EFBFBD><C2B7>
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/*!
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\return string <20>ļ<EFBFBD>·<EFBFBD><C2B7>
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*/
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string getFilePath() const { return mFilePath; }
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double getDisThre() const { return mDisThre; }
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void setDisThre(double val) { mDisThre = val; }
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//! <20><><EFBFBD>û<EFBFBD><C3BB>档<EFBFBD><E6A1A3><EFBFBD><EFBFBD><EFBFBD>Ὣÿ<E1BDAB>ε<EFBFBD><CEB5><EFBFBD>compare<72>ӿ<EFBFBD><D3BF><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>img<6D><67><EFBFBD><EFBFBD><EFBFBD><EFBFBD>dataָ<61><D6B8><EFBFBD><EFBFBD>Ϊkey<65>洢
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// <20><><EFBFBD><EFBFBD>ֵ<EFBFBD><D6B5>
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/*!
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\return void
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*/
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void setIsEnableCache(bool val) { mIsEnableCache = val; }
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bool getIsEnableCache() const { return mIsEnableCache; }
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void clearDisCache() { mDisCache.clear(); }
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ImageCompareModel* scale(float s);
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RotateMatchResult rotateMatch(const Mat& img, int levelNum = 1, float angleStep = 1.0,
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float startAngle = 0, float endAngle = 360) const;
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void rotateMatchData(const Mat& img, RotateData* pData, const vector<Range>& angleRangeVec, float angleStep,
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Mat& disMat) const;
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void rotateMatchData(const Mat& img, RotateData* pData, float angleStep = 1.0,
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float startAngle = 0, float endAngle = 360) const;
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void rotateMatchData(const Mat& img, RotateData* pData, float angleStep,
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const vector<Range>& angleRangeVec) const;
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cv::Mat getM8uMaskImg() const { return m8uMaskImg; }
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void setM8uMaskImg(cv::Mat val) { m8uMaskImg = val; }
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cv::Mat getM32fMaskImg() const { return m32fMaskImg; }
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void setM32fMaskImg(cv::Mat val) { m32fMaskImg = val; }
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int computeRepeatNum();
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protected:
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//! <20><><EFBFBD><EFBFBD>δ<EFBFBD><CEB4><EFBFBD>ɣ<EFBFBD><C9A3><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ͼ<EFBFBD><CDBC><EFBFBD>ֱ<EFBFBD><D6B1>ͱ<EFBFBD>ͼmBaseImg<6D><67><EFBFBD><EFBFBD><EFBFBD><EFBFBD>תƥ<D7AA>䣬<EFBFBD><E4A3AC><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ò<EFBFBD><C3B2><EFBFBD>ֵ
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/*!
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\param Mat img0 <20><><EFBFBD>Ƚϵ<C8BD>ͼ<EFBFBD><CDBC>img0
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\param Mat img1 <20><><EFBFBD>Ƚϵ<C8BD>ͼ<EFBFBD><CDBC>img1
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\param Mat * pRImg0 <20><>img0<67>ͱ<EFBFBD>ͼmBaseImg<6D><67>תƥ<D7AA><C6A5><EFBFBD>Ľ<EFBFBD><C4BD><EFBFBD>rimg0
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\param Mat * pRImg1 <20><>img1<67>ͱ<EFBFBD>ͼmBaseImg<6D><67>תƥ<D7AA><C6A5><EFBFBD>Ľ<EFBFBD><C4BD><EFBFBD>rimg1
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\return double <20><><EFBFBD><EFBFBD>ֵ<EFBFBD><D6B5>ȡֵ<C8A1><D6B5>СΪmMatchValScale*norm(rimg0 - rimg1)/(cols*rows)
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*/
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double compare(Mat img0, Mat img1, Mat* pRImg0 = NULL, Mat* pRImg1 = NULL);
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void setFilePath(string val) { mFilePath = val; }
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double genMatchValue(const Mat& rImg, const Mat& baseImg, const Mat& maskImg, int flag, int diameter) const;
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double genMatchValue(const Mat& dMat) const;
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double scaleMatchValue(double val) const;
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void weightReconstruction(const Mat& rImg, const Mat& baseImg, const Mat& maskImg, Mat &reConImg);
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void preWeightReconstruction(Mat img, Mat &reConImg);
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void setFalseSampleMinDis(double iVal) { mFalseSampleMinDis = iVal; }
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double mMatchValScale;
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int mTargetMeanVal, mTargetStddevVal, mHighlightsThreshold;
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int mRepeatNum;
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Mat mAlignBaseImg, mCompareBaseImg;
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Mat mWeightMat;
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Mat m32fMaskImg, m8uMaskImg;
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Mat mDisMat;
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Mat reConMat;
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Mat falseReConMat;
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double mDisThre;
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string mName;
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double falseMinDis;
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int meanDiameter;
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// some training data
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double mTrueSampleDisStddev, mTrueSampleDisMean, mTrueSampleDisMax, mTrueSampleDisMin;
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double mFalseSampleMinDis;
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// temp data
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string mFilePath;
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void initMultiScaleModel();
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MultiScaleImageCompareModel* mpMultiScaleModel;
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// cache
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bool mIsEnableCache;
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map<uchar*, double> mDisCache;
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private:
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};
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class ImageCompareModelInvoker : public cv::ParallelLoopBody
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{
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public:
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ImageCompareModelInvoker(const ImageCompareModel *pModel, void* pData)
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: m_pModel(pModel), m_pData(pData)
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{}
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private:
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const ImageCompareModel *m_pModel;
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void *m_pData;
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virtual void operator() (const cv::Range& range) const;
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}; |