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Open Source Computer Vision Library
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1525 lines
47 KiB
1525 lines
47 KiB
#include "test_precomp.hpp" |
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using namespace cv; |
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using namespace std; |
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namespace cvtest |
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{ |
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const int ARITHM_NTESTS = 1000; |
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const int ARITHM_RNG_SEED = -1; |
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const int ARITHM_MAX_CHANNELS = 4; |
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const int ARITHM_MAX_NDIMS = 4; |
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const int ARITHM_MAX_SIZE_LOG = 10; |
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struct BaseElemWiseOp |
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{ |
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enum { FIX_ALPHA=1, FIX_BETA=2, FIX_GAMMA=4, REAL_GAMMA=8, SUPPORT_MASK=16, SCALAR_OUTPUT=32 }; |
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BaseElemWiseOp(int _ninputs, int _flags, double _alpha, double _beta, |
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Scalar _gamma=Scalar::all(0), int _context=1) |
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: ninputs(_ninputs), flags(_flags), alpha(_alpha), beta(_beta), gamma(_gamma), context(_context) {} |
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BaseElemWiseOp() { flags = 0; alpha = beta = 0; gamma = Scalar::all(0); } |
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virtual ~BaseElemWiseOp() {} |
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virtual void op(const vector<Mat>&, Mat&, const Mat&) {} |
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virtual void refop(const vector<Mat>&, Mat&, const Mat&) {} |
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virtual void getValueRange(int depth, double& minval, double& maxval) |
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{ |
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minval = depth < CV_32S ? cvtest::getMinVal(depth) : depth == CV_32S ? -1000000 : -1000.; |
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maxval = depth < CV_32S ? cvtest::getMaxVal(depth) : depth == CV_32S ? 1000000 : 1000.; |
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} |
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virtual void getRandomSize(RNG& rng, vector<int>& size) |
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{ |
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cvtest::randomSize(rng, 2, ARITHM_MAX_NDIMS, cvtest::ARITHM_MAX_SIZE_LOG, size); |
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} |
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virtual int getRandomType(RNG& rng) |
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{ |
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return cvtest::randomType(rng, DEPTH_MASK_ALL_BUT_8S, 1, |
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ninputs > 1 ? ARITHM_MAX_CHANNELS : 4); |
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} |
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virtual double getMaxErr(int depth) { return depth < CV_32F ? 1 : depth == CV_32F ? 1e-5 : 1e-12; } |
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virtual void generateScalars(int depth, RNG& rng) |
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{ |
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const double m = 3.; |
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if( !(flags & FIX_ALPHA) ) |
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{ |
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alpha = exp(rng.uniform(-0.5, 0.1)*m*2*CV_LOG2); |
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alpha *= rng.uniform(0, 2) ? 1 : -1; |
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} |
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if( !(flags & FIX_BETA) ) |
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{ |
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beta = exp(rng.uniform(-0.5, 0.1)*m*2*CV_LOG2); |
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beta *= rng.uniform(0, 2) ? 1 : -1; |
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} |
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if( !(flags & FIX_GAMMA) ) |
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{ |
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for( int i = 0; i < 4; i++ ) |
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{ |
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gamma[i] = exp(rng.uniform(-1, 6)*m*CV_LOG2); |
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gamma[i] *= rng.uniform(0, 2) ? 1 : -1; |
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} |
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if( flags & REAL_GAMMA ) |
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gamma = Scalar::all(gamma[0]); |
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} |
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if( depth == CV_32F ) |
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{ |
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Mat fl, db; |
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db = Mat(1, 1, CV_64F, &alpha); |
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db.convertTo(fl, CV_32F); |
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fl.convertTo(db, CV_64F); |
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db = Mat(1, 1, CV_64F, &beta); |
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db.convertTo(fl, CV_32F); |
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fl.convertTo(db, CV_64F); |
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db = Mat(1, 4, CV_64F, &gamma[0]); |
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db.convertTo(fl, CV_32F); |
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fl.convertTo(db, CV_64F); |
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} |
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} |
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int ninputs; |
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int flags; |
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double alpha; |
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double beta; |
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Scalar gamma; |
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int maxErr; |
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int context; |
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}; |
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struct BaseAddOp : public BaseElemWiseOp |
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{ |
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BaseAddOp(int _ninputs, int _flags, double _alpha, double _beta, Scalar _gamma=Scalar::all(0)) |
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: BaseElemWiseOp(_ninputs, _flags, _alpha, _beta, _gamma) {} |
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void refop(const vector<Mat>& src, Mat& dst, const Mat& mask) |
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{ |
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Mat temp; |
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if( !mask.empty() ) |
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{ |
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cvtest::add(src[0], alpha, src.size() > 1 ? src[1] : Mat(), beta, gamma, temp, src[0].type()); |
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cvtest::copy(temp, dst, mask); |
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} |
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else |
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cvtest::add(src[0], alpha, src.size() > 1 ? src[1] : Mat(), beta, gamma, dst, src[0].type()); |
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} |
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}; |
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struct AddOp : public BaseAddOp |
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{ |
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AddOp() : BaseAddOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA+SUPPORT_MASK, 1, 1, Scalar::all(0)) {}; |
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void op(const vector<Mat>& src, Mat& dst, const Mat& mask) |
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{ |
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if( mask.empty() ) |
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add(src[0], src[1], dst); |
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else |
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add(src[0], src[1], dst, mask); |
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} |
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}; |
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struct SubOp : public BaseAddOp |
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{ |
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SubOp() : BaseAddOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA+SUPPORT_MASK, 1, -1, Scalar::all(0)) {}; |
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void op(const vector<Mat>& src, Mat& dst, const Mat& mask) |
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{ |
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if( mask.empty() ) |
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subtract(src[0], src[1], dst); |
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else |
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subtract(src[0], src[1], dst, mask); |
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} |
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}; |
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struct AddSOp : public BaseAddOp |
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{ |
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AddSOp() : BaseAddOp(1, FIX_ALPHA+FIX_BETA+SUPPORT_MASK, 1, 0, Scalar::all(0)) {}; |
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void op(const vector<Mat>& src, Mat& dst, const Mat& mask) |
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{ |
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if( mask.empty() ) |
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add(src[0], gamma, dst); |
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else |
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add(src[0], gamma, dst, mask); |
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} |
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}; |
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struct SubRSOp : public BaseAddOp |
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{ |
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SubRSOp() : BaseAddOp(1, FIX_ALPHA+FIX_BETA+SUPPORT_MASK, -1, 0, Scalar::all(0)) {}; |
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void op(const vector<Mat>& src, Mat& dst, const Mat& mask) |
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{ |
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if( mask.empty() ) |
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subtract(gamma, src[0], dst); |
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else |
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subtract(gamma, src[0], dst, mask); |
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} |
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}; |
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struct ScaleAddOp : public BaseAddOp |
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{ |
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ScaleAddOp() : BaseAddOp(2, FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}; |
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void op(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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scaleAdd(src[0], alpha, src[1], dst); |
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} |
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double getMaxErr(int depth) |
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{ |
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return depth <= CV_32S ? 2 : depth < CV_64F ? 1e-4 : 1e-12; |
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} |
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}; |
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struct AddWeightedOp : public BaseAddOp |
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{ |
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AddWeightedOp() : BaseAddOp(2, REAL_GAMMA, 1, 1, Scalar::all(0)) {}; |
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void op(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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addWeighted(src[0], alpha, src[1], beta, gamma[0], dst); |
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} |
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double getMaxErr(int depth) |
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{ |
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return depth <= CV_32S ? 2 : depth < CV_64F ? 1e-5 : 1e-10; |
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} |
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}; |
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struct MulOp : public BaseElemWiseOp |
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{ |
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MulOp() : BaseElemWiseOp(2, FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}; |
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void getValueRange(int depth, double& minval, double& maxval) |
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{ |
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minval = depth < CV_32S ? cvtest::getMinVal(depth) : depth == CV_32S ? -1000000 : -1000.; |
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maxval = depth < CV_32S ? cvtest::getMaxVal(depth) : depth == CV_32S ? 1000000 : 1000.; |
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minval = std::max(minval, -30000.); |
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maxval = std::min(maxval, 30000.); |
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} |
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void op(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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cv::multiply(src[0], src[1], dst, alpha); |
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} |
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void refop(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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cvtest::multiply(src[0], src[1], dst, alpha); |
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} |
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double getMaxErr(int depth) |
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{ |
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return depth <= CV_32S ? 2 : depth < CV_64F ? 1e-5 : 1e-12; |
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} |
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}; |
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struct DivOp : public BaseElemWiseOp |
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{ |
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DivOp() : BaseElemWiseOp(2, FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}; |
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void op(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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cv::divide(src[0], src[1], dst, alpha); |
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} |
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void refop(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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cvtest::divide(src[0], src[1], dst, alpha); |
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} |
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double getMaxErr(int depth) |
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{ |
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return depth <= CV_32S ? 2 : depth < CV_64F ? 1e-5 : 1e-12; |
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} |
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}; |
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struct RecipOp : public BaseElemWiseOp |
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{ |
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RecipOp() : BaseElemWiseOp(1, FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}; |
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void op(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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cv::divide(alpha, src[0], dst); |
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} |
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void refop(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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cvtest::divide(Mat(), src[0], dst, alpha); |
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} |
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double getMaxErr(int depth) |
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{ |
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return depth <= CV_32S ? 2 : depth < CV_64F ? 1e-5 : 1e-12; |
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} |
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}; |
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struct AbsDiffOp : public BaseAddOp |
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{ |
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AbsDiffOp() : BaseAddOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, -1, Scalar::all(0)) {}; |
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void op(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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absdiff(src[0], src[1], dst); |
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} |
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void refop(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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cvtest::add(src[0], 1, src[1], -1, Scalar::all(0), dst, src[0].type(), true); |
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} |
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}; |
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struct AbsDiffSOp : public BaseAddOp |
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{ |
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AbsDiffSOp() : BaseAddOp(1, FIX_ALPHA+FIX_BETA, 1, 0, Scalar::all(0)) {}; |
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void op(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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absdiff(src[0], gamma, dst); |
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} |
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void refop(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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cvtest::add(src[0], 1, Mat(), 0, -gamma, dst, src[0].type(), true); |
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} |
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}; |
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struct LogicOp : public BaseElemWiseOp |
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{ |
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LogicOp(char _opcode) : BaseElemWiseOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA+SUPPORT_MASK, 1, 1, Scalar::all(0)), opcode(_opcode) {}; |
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void op(const vector<Mat>& src, Mat& dst, const Mat& mask) |
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{ |
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if( opcode == '&' ) |
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bitwise_and(src[0], src[1], dst, mask); |
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else if( opcode == '|' ) |
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bitwise_or(src[0], src[1], dst, mask); |
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else |
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bitwise_xor(src[0], src[1], dst, mask); |
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} |
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void refop(const vector<Mat>& src, Mat& dst, const Mat& mask) |
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{ |
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Mat temp; |
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if( !mask.empty() ) |
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{ |
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cvtest::logicOp(src[0], src[1], temp, opcode); |
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cvtest::copy(temp, dst, mask); |
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} |
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else |
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cvtest::logicOp(src[0], src[1], dst, opcode); |
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} |
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double getMaxErr(int) |
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{ |
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return 0; |
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} |
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char opcode; |
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}; |
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struct LogicSOp : public BaseElemWiseOp |
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{ |
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LogicSOp(char _opcode) |
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: BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+(_opcode != '~' ? SUPPORT_MASK : 0), 1, 1, Scalar::all(0)), opcode(_opcode) {}; |
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void op(const vector<Mat>& src, Mat& dst, const Mat& mask) |
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{ |
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if( opcode == '&' ) |
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bitwise_and(src[0], gamma, dst, mask); |
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else if( opcode == '|' ) |
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bitwise_or(src[0], gamma, dst, mask); |
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else if( opcode == '^' ) |
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bitwise_xor(src[0], gamma, dst, mask); |
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else |
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bitwise_not(src[0], dst); |
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} |
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void refop(const vector<Mat>& src, Mat& dst, const Mat& mask) |
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{ |
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Mat temp; |
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if( !mask.empty() ) |
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{ |
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cvtest::logicOp(src[0], gamma, temp, opcode); |
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cvtest::copy(temp, dst, mask); |
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} |
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else |
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cvtest::logicOp(src[0], gamma, dst, opcode); |
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} |
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double getMaxErr(int) |
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{ |
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return 0; |
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} |
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char opcode; |
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}; |
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struct MinOp : public BaseElemWiseOp |
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{ |
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MinOp() : BaseElemWiseOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}; |
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void op(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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cv::min(src[0], src[1], dst); |
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} |
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void refop(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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cvtest::min(src[0], src[1], dst); |
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} |
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double getMaxErr(int) |
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{ |
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return 0; |
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} |
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}; |
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struct MaxOp : public BaseElemWiseOp |
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{ |
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MaxOp() : BaseElemWiseOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}; |
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void op(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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cv::max(src[0], src[1], dst); |
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} |
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void refop(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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cvtest::max(src[0], src[1], dst); |
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} |
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double getMaxErr(int) |
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{ |
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return 0; |
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} |
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}; |
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struct MinSOp : public BaseElemWiseOp |
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{ |
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MinSOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+REAL_GAMMA, 1, 1, Scalar::all(0)) {}; |
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void op(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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cv::min(src[0], gamma[0], dst); |
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} |
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void refop(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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cvtest::min(src[0], gamma[0], dst); |
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} |
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double getMaxErr(int) |
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{ |
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return 0; |
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} |
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}; |
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struct MaxSOp : public BaseElemWiseOp |
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{ |
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MaxSOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+REAL_GAMMA, 1, 1, Scalar::all(0)) {}; |
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void op(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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cv::max(src[0], gamma[0], dst); |
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} |
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void refop(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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cvtest::max(src[0], gamma[0], dst); |
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} |
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double getMaxErr(int) |
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{ |
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return 0; |
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} |
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}; |
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struct CmpOp : public BaseElemWiseOp |
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{ |
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CmpOp() : BaseElemWiseOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}; |
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void generateScalars(int depth, RNG& rng) |
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{ |
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BaseElemWiseOp::generateScalars(depth, rng); |
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cmpop = rng.uniform(0, 6); |
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} |
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void op(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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cv::compare(src[0], src[1], dst, cmpop); |
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} |
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void refop(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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cvtest::compare(src[0], src[1], dst, cmpop); |
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} |
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int getRandomType(RNG& rng) |
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{ |
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return cvtest::randomType(rng, DEPTH_MASK_ALL_BUT_8S, 1, 1); |
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} |
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double getMaxErr(int) |
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{ |
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return 0; |
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} |
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int cmpop; |
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}; |
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struct CmpSOp : public BaseElemWiseOp |
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{ |
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CmpSOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+REAL_GAMMA, 1, 1, Scalar::all(0)) {}; |
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void generateScalars(int depth, RNG& rng) |
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{ |
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BaseElemWiseOp::generateScalars(depth, rng); |
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cmpop = rng.uniform(0, 6); |
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if( depth < CV_32F ) |
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gamma[0] = cvRound(gamma[0]); |
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} |
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void op(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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cv::compare(src[0], gamma[0], dst, cmpop); |
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} |
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void refop(const vector<Mat>& src, Mat& dst, const Mat&) |
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{ |
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cvtest::compare(src[0], gamma[0], dst, cmpop); |
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} |
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int getRandomType(RNG& rng) |
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{ |
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return cvtest::randomType(rng, DEPTH_MASK_ALL_BUT_8S, 1, 1); |
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} |
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double getMaxErr(int) |
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{ |
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return 0; |
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} |
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int cmpop; |
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}; |
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struct CopyOp : public BaseElemWiseOp |
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{ |
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CopyOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA+SUPPORT_MASK, 1, 1, Scalar::all(0)) {}; |
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void op(const vector<Mat>& src, Mat& dst, const Mat& mask) |
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{ |
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src[0].copyTo(dst, mask); |
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} |
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void refop(const vector<Mat>& src, Mat& dst, const Mat& mask) |
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{ |
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cvtest::copy(src[0], dst, mask); |
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} |
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int getRandomType(RNG& rng) |
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{ |
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return cvtest::randomType(rng, DEPTH_MASK_ALL, 1, ARITHM_MAX_CHANNELS); |
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} |
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double getMaxErr(int) |
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{ |
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return 0; |
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} |
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int cmpop; |
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}; |
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struct SetOp : public BaseElemWiseOp |
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{ |
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SetOp() : BaseElemWiseOp(0, FIX_ALPHA+FIX_BETA+SUPPORT_MASK, 1, 1, Scalar::all(0)) {}; |
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void op(const vector<Mat>&, Mat& dst, const Mat& mask) |
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{ |
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dst.setTo(gamma, mask); |
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} |
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void refop(const vector<Mat>&, Mat& dst, const Mat& mask) |
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{ |
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cvtest::set(dst, gamma, mask); |
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} |
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int getRandomType(RNG& rng) |
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{ |
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return cvtest::randomType(rng, DEPTH_MASK_ALL, 1, ARITHM_MAX_CHANNELS); |
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} |
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double getMaxErr(int) |
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{ |
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return 0; |
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} |
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}; |
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template<typename _Tp, typename _WTp> static void |
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inRangeS_(const _Tp* src, const _WTp* a, const _WTp* b, uchar* dst, size_t total, int cn) |
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{ |
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size_t i; |
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int c; |
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for( i = 0; i < total; i++ ) |
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{ |
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_Tp val = src[i*cn]; |
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dst[i] = (a[0] <= val && val <= b[0]) ? uchar(255) : 0; |
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} |
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for( c = 1; c < cn; c++ ) |
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{ |
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for( i = 0; i < total; i++ ) |
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{ |
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_Tp val = src[i*cn + c]; |
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dst[i] = a[c] <= val && val <= b[c] ? dst[i] : 0; |
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} |
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} |
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} |
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template<typename _Tp> static void inRange_(const _Tp* src, const _Tp* a, const _Tp* b, uchar* dst, size_t total, int cn) |
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{ |
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size_t i; |
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int c; |
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for( i = 0; i < total; i++ ) |
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{ |
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_Tp val = src[i*cn]; |
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dst[i] = a[i*cn] <= val && val <= b[i*cn] ? 255 : 0; |
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} |
|
for( c = 1; c < cn; c++ ) |
|
{ |
|
for( i = 0; i < total; i++ ) |
|
{ |
|
_Tp val = src[i*cn + c]; |
|
dst[i] = a[i*cn + c] <= val && val <= b[i*cn + c] ? dst[i] : 0; |
|
} |
|
} |
|
} |
|
|
|
|
|
static void inRange(const Mat& src, const Mat& lb, const Mat& rb, Mat& dst) |
|
{ |
|
CV_Assert( src.type() == lb.type() && src.type() == rb.type() && |
|
src.size == lb.size && src.size == rb.size ); |
|
dst.create( src.dims, &src.size[0], CV_8U ); |
|
const Mat *arrays[]={&src, &lb, &rb, &dst, 0}; |
|
Mat planes[4]; |
|
|
|
NAryMatIterator it(arrays, planes); |
|
size_t total = planes[0].total(); |
|
size_t i, nplanes = it.nplanes; |
|
int depth = src.depth(), cn = src.channels(); |
|
|
|
for( i = 0; i < nplanes; i++, ++it ) |
|
{ |
|
const uchar* sptr = planes[0].data; |
|
const uchar* aptr = planes[1].data; |
|
const uchar* bptr = planes[2].data; |
|
uchar* dptr = planes[3].data; |
|
|
|
switch( depth ) |
|
{ |
|
case CV_8U: |
|
inRange_((const uchar*)sptr, (const uchar*)aptr, (const uchar*)bptr, dptr, total, cn); |
|
break; |
|
case CV_8S: |
|
inRange_((const schar*)sptr, (const schar*)aptr, (const schar*)bptr, dptr, total, cn); |
|
break; |
|
case CV_16U: |
|
inRange_((const ushort*)sptr, (const ushort*)aptr, (const ushort*)bptr, dptr, total, cn); |
|
break; |
|
case CV_16S: |
|
inRange_((const short*)sptr, (const short*)aptr, (const short*)bptr, dptr, total, cn); |
|
break; |
|
case CV_32S: |
|
inRange_((const int*)sptr, (const int*)aptr, (const int*)bptr, dptr, total, cn); |
|
break; |
|
case CV_32F: |
|
inRange_((const float*)sptr, (const float*)aptr, (const float*)bptr, dptr, total, cn); |
|
break; |
|
case CV_64F: |
|
inRange_((const double*)sptr, (const double*)aptr, (const double*)bptr, dptr, total, cn); |
|
break; |
|
default: |
|
CV_Error(CV_StsUnsupportedFormat, ""); |
|
} |
|
} |
|
} |
|
|
|
|
|
static void inRangeS(const Mat& src, const Scalar& lb, const Scalar& rb, Mat& dst) |
|
{ |
|
dst.create( src.dims, &src.size[0], CV_8U ); |
|
const Mat *arrays[]={&src, &dst, 0}; |
|
Mat planes[2]; |
|
|
|
NAryMatIterator it(arrays, planes); |
|
size_t total = planes[0].total(); |
|
size_t i, nplanes = it.nplanes; |
|
int depth = src.depth(), cn = src.channels(); |
|
union { double d[4]; float f[4]; int i[4];} lbuf, rbuf; |
|
int wtype = CV_MAKETYPE(depth <= CV_32S ? CV_32S : depth, cn); |
|
scalarToRawData(lb, lbuf.d, wtype, cn); |
|
scalarToRawData(rb, rbuf.d, wtype, cn); |
|
|
|
for( i = 0; i < nplanes; i++, ++it ) |
|
{ |
|
const uchar* sptr = planes[0].data; |
|
uchar* dptr = planes[1].data; |
|
|
|
switch( depth ) |
|
{ |
|
case CV_8U: |
|
inRangeS_((const uchar*)sptr, lbuf.i, rbuf.i, dptr, total, cn); |
|
break; |
|
case CV_8S: |
|
inRangeS_((const schar*)sptr, lbuf.i, rbuf.i, dptr, total, cn); |
|
break; |
|
case CV_16U: |
|
inRangeS_((const ushort*)sptr, lbuf.i, rbuf.i, dptr, total, cn); |
|
break; |
|
case CV_16S: |
|
inRangeS_((const short*)sptr, lbuf.i, rbuf.i, dptr, total, cn); |
|
break; |
|
case CV_32S: |
|
inRangeS_((const int*)sptr, lbuf.i, rbuf.i, dptr, total, cn); |
|
break; |
|
case CV_32F: |
|
inRangeS_((const float*)sptr, lbuf.f, rbuf.f, dptr, total, cn); |
|
break; |
|
case CV_64F: |
|
inRangeS_((const double*)sptr, lbuf.d, rbuf.d, dptr, total, cn); |
|
break; |
|
default: |
|
CV_Error(CV_StsUnsupportedFormat, ""); |
|
} |
|
} |
|
} |
|
|
|
|
|
struct InRangeSOp : public BaseElemWiseOp |
|
{ |
|
InRangeSOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA, 1, 1, Scalar::all(0)) {}; |
|
void op(const vector<Mat>& src, Mat& dst, const Mat&) |
|
{ |
|
cv::inRange(src[0], gamma, gamma1, dst); |
|
} |
|
void refop(const vector<Mat>& src, Mat& dst, const Mat&) |
|
{ |
|
cvtest::inRangeS(src[0], gamma, gamma1, dst); |
|
} |
|
double getMaxErr(int) |
|
{ |
|
return 0; |
|
} |
|
void generateScalars(int depth, RNG& rng) |
|
{ |
|
BaseElemWiseOp::generateScalars(depth, rng); |
|
Scalar temp = gamma; |
|
BaseElemWiseOp::generateScalars(depth, rng); |
|
for( int i = 0; i < 4; i++ ) |
|
{ |
|
gamma1[i] = std::max(gamma[i], temp[i]); |
|
gamma[i] = std::min(gamma[i], temp[i]); |
|
} |
|
} |
|
Scalar gamma1; |
|
}; |
|
|
|
|
|
struct InRangeOp : public BaseElemWiseOp |
|
{ |
|
InRangeOp() : BaseElemWiseOp(3, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}; |
|
void op(const vector<Mat>& src, Mat& dst, const Mat&) |
|
{ |
|
Mat lb, rb; |
|
cvtest::min(src[1], src[2], lb); |
|
cvtest::max(src[1], src[2], rb); |
|
|
|
cv::inRange(src[0], lb, rb, dst); |
|
} |
|
void refop(const vector<Mat>& src, Mat& dst, const Mat&) |
|
{ |
|
Mat lb, rb; |
|
cvtest::min(src[1], src[2], lb); |
|
cvtest::max(src[1], src[2], rb); |
|
|
|
cvtest::inRange(src[0], lb, rb, dst); |
|
} |
|
double getMaxErr(int) |
|
{ |
|
return 0; |
|
} |
|
}; |
|
|
|
|
|
struct ConvertScaleOp : public BaseElemWiseOp |
|
{ |
|
ConvertScaleOp() : BaseElemWiseOp(1, FIX_BETA+REAL_GAMMA, 1, 1, Scalar::all(0)), ddepth(0) { }; |
|
void op(const vector<Mat>& src, Mat& dst, const Mat&) |
|
{ |
|
src[0].convertTo(dst, ddepth, alpha, gamma[0]); |
|
} |
|
void refop(const vector<Mat>& src, Mat& dst, const Mat&) |
|
{ |
|
cvtest::convert(src[0], dst, CV_MAKETYPE(ddepth, src[0].channels()), alpha, gamma[0]); |
|
} |
|
int getRandomType(RNG& rng) |
|
{ |
|
int srctype = cvtest::randomType(rng, DEPTH_MASK_ALL, 1, ARITHM_MAX_CHANNELS); |
|
ddepth = cvtest::randomType(rng, DEPTH_MASK_ALL, 1, 1); |
|
return srctype; |
|
} |
|
double getMaxErr(int) |
|
{ |
|
return ddepth <= CV_32S ? 2 : ddepth < CV_64F ? 1e-3 : 1e-12; |
|
} |
|
void generateScalars(int depth, RNG& rng) |
|
{ |
|
if( rng.uniform(0, 2) ) |
|
BaseElemWiseOp::generateScalars(depth, rng); |
|
else |
|
{ |
|
alpha = 1; |
|
gamma = Scalar::all(0); |
|
} |
|
} |
|
int ddepth; |
|
}; |
|
|
|
|
|
struct ConvertScaleAbsOp : public BaseElemWiseOp |
|
{ |
|
ConvertScaleAbsOp() : BaseElemWiseOp(1, FIX_BETA+REAL_GAMMA, 1, 1, Scalar::all(0)) {}; |
|
void op(const vector<Mat>& src, Mat& dst, const Mat&) |
|
{ |
|
cv::convertScaleAbs(src[0], dst, alpha, gamma[0]); |
|
} |
|
void refop(const vector<Mat>& src, Mat& dst, const Mat&) |
|
{ |
|
cvtest::add(src[0], alpha, Mat(), 0, Scalar::all(gamma[0]), dst, CV_8UC(src[0].channels()), true); |
|
} |
|
double getMaxErr(int) |
|
{ |
|
return 1; |
|
} |
|
void generateScalars(int depth, RNG& rng) |
|
{ |
|
if( rng.uniform(0, 2) ) |
|
BaseElemWiseOp::generateScalars(depth, rng); |
|
else |
|
{ |
|
alpha = 1; |
|
gamma = Scalar::all(0); |
|
} |
|
} |
|
}; |
|
|
|
|
|
static void flip(const Mat& src, Mat& dst, int flipcode) |
|
{ |
|
CV_Assert(src.dims == 2); |
|
dst.create(src.size(), src.type()); |
|
int i, j, k, esz = (int)src.elemSize(), width = src.cols*esz; |
|
|
|
for( i = 0; i < dst.rows; i++ ) |
|
{ |
|
const uchar* sptr = src.ptr(flipcode == 1 ? i : dst.rows - i - 1); |
|
uchar* dptr = dst.ptr(i); |
|
if( flipcode == 0 ) |
|
memcpy(dptr, sptr, width); |
|
else |
|
{ |
|
for( j = 0; j < width; j += esz ) |
|
for( k = 0; k < esz; k++ ) |
|
dptr[j + k] = sptr[width - j - esz + k]; |
|
} |
|
} |
|
} |
|
|
|
|
|
static void setIdentity(Mat& dst, const Scalar& s) |
|
{ |
|
CV_Assert( dst.dims == 2 && dst.channels() <= 4 ); |
|
double buf[4]; |
|
scalarToRawData(s, buf, dst.type(), 0); |
|
int i, k, esz = (int)dst.elemSize(), width = dst.cols*esz; |
|
|
|
for( i = 0; i < dst.rows; i++ ) |
|
{ |
|
uchar* dptr = dst.ptr(i); |
|
memset( dptr, 0, width ); |
|
if( i < dst.cols ) |
|
for( k = 0; k < esz; k++ ) |
|
dptr[i*esz + k] = ((uchar*)buf)[k]; |
|
} |
|
} |
|
|
|
|
|
struct FlipOp : public BaseElemWiseOp |
|
{ |
|
FlipOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}; |
|
void getRandomSize(RNG& rng, vector<int>& size) |
|
{ |
|
cvtest::randomSize(rng, 2, 2, cvtest::ARITHM_MAX_SIZE_LOG, size); |
|
} |
|
void op(const vector<Mat>& src, Mat& dst, const Mat&) |
|
{ |
|
cv::flip(src[0], dst, flipcode); |
|
} |
|
void refop(const vector<Mat>& src, Mat& dst, const Mat&) |
|
{ |
|
cvtest::flip(src[0], dst, flipcode); |
|
} |
|
void generateScalars(int, RNG& rng) |
|
{ |
|
flipcode = rng.uniform(0, 3) - 1; |
|
} |
|
double getMaxErr(int) |
|
{ |
|
return 0; |
|
} |
|
int flipcode; |
|
}; |
|
|
|
struct TransposeOp : public BaseElemWiseOp |
|
{ |
|
TransposeOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}; |
|
void getRandomSize(RNG& rng, vector<int>& size) |
|
{ |
|
cvtest::randomSize(rng, 2, 2, cvtest::ARITHM_MAX_SIZE_LOG, size); |
|
} |
|
void op(const vector<Mat>& src, Mat& dst, const Mat&) |
|
{ |
|
cv::transpose(src[0], dst); |
|
} |
|
void refop(const vector<Mat>& src, Mat& dst, const Mat&) |
|
{ |
|
cvtest::transpose(src[0], dst); |
|
} |
|
double getMaxErr(int) |
|
{ |
|
return 0; |
|
} |
|
}; |
|
|
|
struct SetIdentityOp : public BaseElemWiseOp |
|
{ |
|
SetIdentityOp() : BaseElemWiseOp(0, FIX_ALPHA+FIX_BETA, 1, 1, Scalar::all(0)) {}; |
|
void getRandomSize(RNG& rng, vector<int>& size) |
|
{ |
|
cvtest::randomSize(rng, 2, 2, cvtest::ARITHM_MAX_SIZE_LOG, size); |
|
} |
|
void op(const vector<Mat>&, Mat& dst, const Mat&) |
|
{ |
|
cv::setIdentity(dst, gamma); |
|
} |
|
void refop(const vector<Mat>&, Mat& dst, const Mat&) |
|
{ |
|
cvtest::setIdentity(dst, gamma); |
|
} |
|
double getMaxErr(int) |
|
{ |
|
return 0; |
|
} |
|
}; |
|
|
|
struct SetZeroOp : public BaseElemWiseOp |
|
{ |
|
SetZeroOp() : BaseElemWiseOp(0, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}; |
|
void op(const vector<Mat>&, Mat& dst, const Mat&) |
|
{ |
|
dst = Scalar::all(0); |
|
} |
|
void refop(const vector<Mat>&, Mat& dst, const Mat&) |
|
{ |
|
cvtest::set(dst, Scalar::all(0)); |
|
} |
|
double getMaxErr(int) |
|
{ |
|
return 0; |
|
} |
|
}; |
|
|
|
|
|
static void exp(const Mat& src, Mat& dst) |
|
{ |
|
dst.create( src.dims, &src.size[0], src.type() ); |
|
const Mat *arrays[]={&src, &dst, 0}; |
|
Mat planes[2]; |
|
|
|
NAryMatIterator it(arrays, planes); |
|
size_t j, total = planes[0].total()*src.channels(); |
|
size_t i, nplanes = it.nplanes; |
|
int depth = src.depth(); |
|
|
|
for( i = 0; i < nplanes; i++, ++it ) |
|
{ |
|
const uchar* sptr = planes[0].data; |
|
uchar* dptr = planes[1].data; |
|
|
|
if( depth == CV_32F ) |
|
{ |
|
for( j = 0; j < total; j++ ) |
|
((float*)dptr)[j] = std::exp(((const float*)sptr)[j]); |
|
} |
|
else if( depth == CV_64F ) |
|
{ |
|
for( j = 0; j < total; j++ ) |
|
((double*)dptr)[j] = std::exp(((const double*)sptr)[j]); |
|
} |
|
} |
|
} |
|
|
|
static void log(const Mat& src, Mat& dst) |
|
{ |
|
dst.create( src.dims, &src.size[0], src.type() ); |
|
const Mat *arrays[]={&src, &dst, 0}; |
|
Mat planes[2]; |
|
|
|
NAryMatIterator it(arrays, planes); |
|
size_t j, total = planes[0].total()*src.channels(); |
|
size_t i, nplanes = it.nplanes; |
|
int depth = src.depth(); |
|
|
|
for( i = 0; i < nplanes; i++, ++it ) |
|
{ |
|
const uchar* sptr = planes[0].data; |
|
uchar* dptr = planes[1].data; |
|
|
|
if( depth == CV_32F ) |
|
{ |
|
for( j = 0; j < total; j++ ) |
|
((float*)dptr)[j] = (float)std::log(fabs(((const float*)sptr)[j])); |
|
} |
|
else if( depth == CV_64F ) |
|
{ |
|
for( j = 0; j < total; j++ ) |
|
((double*)dptr)[j] = std::log(fabs(((const double*)sptr)[j])); |
|
} |
|
} |
|
} |
|
|
|
struct ExpOp : public BaseElemWiseOp |
|
{ |
|
ExpOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}; |
|
int getRandomType(RNG& rng) |
|
{ |
|
return cvtest::randomType(rng, DEPTH_MASK_FLT, 1, ARITHM_MAX_CHANNELS); |
|
} |
|
void getValueRange(int depth, double& minval, double& maxval) |
|
{ |
|
maxval = depth == CV_32F ? 50 : 100; |
|
minval = -maxval; |
|
} |
|
void op(const vector<Mat>& src, Mat& dst, const Mat&) |
|
{ |
|
cv::exp(src[0], dst); |
|
} |
|
void refop(const vector<Mat>& src, Mat& dst, const Mat&) |
|
{ |
|
cvtest::exp(src[0], dst); |
|
} |
|
double getMaxErr(int depth) |
|
{ |
|
return depth == CV_32F ? 1e-5 : 1e-12; |
|
} |
|
}; |
|
|
|
|
|
struct LogOp : public BaseElemWiseOp |
|
{ |
|
LogOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) {}; |
|
int getRandomType(RNG& rng) |
|
{ |
|
return cvtest::randomType(rng, DEPTH_MASK_FLT, 1, ARITHM_MAX_CHANNELS); |
|
} |
|
void getValueRange(int depth, double& minval, double& maxval) |
|
{ |
|
maxval = depth == CV_32F ? 50 : 100; |
|
minval = -maxval; |
|
} |
|
void op(const vector<Mat>& src, Mat& dst, const Mat&) |
|
{ |
|
Mat temp; |
|
cvtest::exp(src[0], temp); |
|
cv::log(temp, dst); |
|
} |
|
void refop(const vector<Mat>& src, Mat& dst, const Mat&) |
|
{ |
|
Mat temp; |
|
cvtest::exp(src[0], temp); |
|
cvtest::log(temp, dst); |
|
} |
|
double getMaxErr(int depth) |
|
{ |
|
return depth == CV_32F ? 1e-5 : 1e-12; |
|
} |
|
}; |
|
|
|
|
|
static void cartToPolar(const Mat& mx, const Mat& my, Mat& mmag, Mat& mangle, bool angleInDegrees) |
|
{ |
|
CV_Assert( (mx.type() == CV_32F || mx.type() == CV_64F) && |
|
mx.type() == my.type() && mx.size == my.size ); |
|
mmag.create( mx.dims, &mx.size[0], mx.type() ); |
|
mangle.create( mx.dims, &mx.size[0], mx.type() ); |
|
const Mat *arrays[]={&mx, &my, &mmag, &mangle, 0}; |
|
Mat planes[4]; |
|
|
|
NAryMatIterator it(arrays, planes); |
|
size_t j, total = planes[0].total(); |
|
size_t i, nplanes = it.nplanes; |
|
int depth = mx.depth(); |
|
double scale = angleInDegrees ? 180/CV_PI : 1; |
|
|
|
for( i = 0; i < nplanes; i++, ++it ) |
|
{ |
|
if( depth == CV_32F ) |
|
{ |
|
const float* xptr = (const float*)planes[0].data; |
|
const float* yptr = (const float*)planes[1].data; |
|
float* mptr = (float*)planes[2].data; |
|
float* aptr = (float*)planes[3].data; |
|
|
|
for( j = 0; j < total; j++ ) |
|
{ |
|
mptr[j] = std::sqrt(xptr[j]*xptr[j] + yptr[j]*yptr[j]); |
|
double a = atan2((double)yptr[j], (double)xptr[j]); |
|
if( a < 0 ) a += CV_PI*2; |
|
aptr[j] = (float)(a*scale); |
|
} |
|
} |
|
else |
|
{ |
|
const double* xptr = (const double*)planes[0].data; |
|
const double* yptr = (const double*)planes[1].data; |
|
double* mptr = (double*)planes[2].data; |
|
double* aptr = (double*)planes[3].data; |
|
|
|
for( j = 0; j < total; j++ ) |
|
{ |
|
mptr[j] = std::sqrt(xptr[j]*xptr[j] + yptr[j]*yptr[j]); |
|
double a = atan2(yptr[j], xptr[j]); |
|
if( a < 0 ) a += CV_PI*2; |
|
aptr[j] = a*scale; |
|
} |
|
} |
|
} |
|
} |
|
|
|
|
|
struct CartToPolarToCartOp : public BaseElemWiseOp |
|
{ |
|
CartToPolarToCartOp() : BaseElemWiseOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA, 1, 1, Scalar::all(0)) |
|
{ |
|
context = 3; |
|
angleInDegrees = true; |
|
} |
|
int getRandomType(RNG& rng) |
|
{ |
|
return cvtest::randomType(rng, DEPTH_MASK_FLT, 1, 1); |
|
} |
|
void op(const vector<Mat>& src, Mat& dst, const Mat&) |
|
{ |
|
Mat mag, angle, x, y; |
|
|
|
cv::cartToPolar(src[0], src[1], mag, angle, angleInDegrees); |
|
cv::polarToCart(mag, angle, x, y, angleInDegrees); |
|
|
|
Mat msrc[] = {mag, angle, x, y}; |
|
int pairs[] = {0, 0, 1, 1, 2, 2, 3, 3}; |
|
dst.create(src[0].dims, src[0].size, CV_MAKETYPE(src[0].depth(), 4)); |
|
cv::mixChannels(msrc, 4, &dst, 1, pairs, 4); |
|
} |
|
void refop(const vector<Mat>& src, Mat& dst, const Mat&) |
|
{ |
|
Mat mag, angle; |
|
cvtest::cartToPolar(src[0], src[1], mag, angle, angleInDegrees); |
|
Mat msrc[] = {mag, angle, src[0], src[1]}; |
|
int pairs[] = {0, 0, 1, 1, 2, 2, 3, 3}; |
|
dst.create(src[0].dims, src[0].size, CV_MAKETYPE(src[0].depth(), 4)); |
|
cv::mixChannels(msrc, 4, &dst, 1, pairs, 4); |
|
} |
|
void generateScalars(int, RNG& rng) |
|
{ |
|
angleInDegrees = rng.uniform(0, 2) != 0; |
|
} |
|
double getMaxErr(int) |
|
{ |
|
return 1e-3; |
|
} |
|
bool angleInDegrees; |
|
}; |
|
|
|
|
|
struct MeanOp : public BaseElemWiseOp |
|
{ |
|
MeanOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA+SUPPORT_MASK+SCALAR_OUTPUT, 1, 1, Scalar::all(0)) |
|
{ |
|
context = 3; |
|
}; |
|
void op(const vector<Mat>& src, Mat& dst, const Mat& mask) |
|
{ |
|
dst.create(1, 1, CV_64FC4); |
|
dst.at<Scalar>(0,0) = cv::mean(src[0], mask); |
|
} |
|
void refop(const vector<Mat>& src, Mat& dst, const Mat& mask) |
|
{ |
|
dst.create(1, 1, CV_64FC4); |
|
dst.at<Scalar>(0,0) = cvtest::mean(src[0], mask); |
|
} |
|
double getMaxErr(int) |
|
{ |
|
return 1e-6; |
|
} |
|
}; |
|
|
|
|
|
struct SumOp : public BaseElemWiseOp |
|
{ |
|
SumOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA+SCALAR_OUTPUT, 1, 1, Scalar::all(0)) |
|
{ |
|
context = 3; |
|
}; |
|
void op(const vector<Mat>& src, Mat& dst, const Mat&) |
|
{ |
|
dst.create(1, 1, CV_64FC4); |
|
dst.at<Scalar>(0,0) = cv::sum(src[0]); |
|
} |
|
void refop(const vector<Mat>& src, Mat& dst, const Mat&) |
|
{ |
|
dst.create(1, 1, CV_64FC4); |
|
dst.at<Scalar>(0,0) = cvtest::mean(src[0])*(double)src[0].total(); |
|
} |
|
double getMaxErr(int) |
|
{ |
|
return 1e-5; |
|
} |
|
}; |
|
|
|
|
|
struct CountNonZeroOp : public BaseElemWiseOp |
|
{ |
|
CountNonZeroOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA+SCALAR_OUTPUT+SUPPORT_MASK, 1, 1, Scalar::all(0)) |
|
{} |
|
int getRandomType(RNG& rng) |
|
{ |
|
return cvtest::randomType(rng, DEPTH_MASK_ALL, 1, 1); |
|
} |
|
void op(const vector<Mat>& src, Mat& dst, const Mat& mask) |
|
{ |
|
Mat temp; |
|
src[0].copyTo(temp); |
|
if( !mask.empty() ) |
|
temp.setTo(Scalar::all(0), mask); |
|
dst.create(1, 1, CV_32S); |
|
dst.at<int>(0,0) = cv::countNonZero(temp); |
|
} |
|
void refop(const vector<Mat>& src, Mat& dst, const Mat& mask) |
|
{ |
|
Mat temp; |
|
cvtest::compare(src[0], 0, temp, CMP_NE); |
|
if( !mask.empty() ) |
|
cvtest::set(temp, Scalar::all(0), mask); |
|
dst.create(1, 1, CV_32S); |
|
dst.at<int>(0,0) = saturate_cast<int>(cvtest::mean(temp)[0]/255*temp.total()); |
|
} |
|
double getMaxErr(int) |
|
{ |
|
return 0; |
|
} |
|
}; |
|
|
|
|
|
struct MeanStdDevOp : public BaseElemWiseOp |
|
{ |
|
Scalar sqmeanRef; |
|
int cn; |
|
|
|
MeanStdDevOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA+SUPPORT_MASK+SCALAR_OUTPUT, 1, 1, Scalar::all(0)) |
|
{ |
|
cn = 0; |
|
context = 7; |
|
}; |
|
void op(const vector<Mat>& src, Mat& dst, const Mat& mask) |
|
{ |
|
dst.create(1, 2, CV_64FC4); |
|
cv::meanStdDev(src[0], dst.at<Scalar>(0,0), dst.at<Scalar>(0,1), mask); |
|
} |
|
void refop(const vector<Mat>& src, Mat& dst, const Mat& mask) |
|
{ |
|
Mat temp; |
|
cvtest::convert(src[0], temp, CV_64F); |
|
cvtest::multiply(temp, temp, temp); |
|
Scalar mean = cvtest::mean(src[0], mask); |
|
Scalar sqmean = cvtest::mean(temp, mask); |
|
|
|
sqmeanRef = sqmean; |
|
cn = temp.channels(); |
|
|
|
for( int c = 0; c < 4; c++ ) |
|
sqmean[c] = std::sqrt(std::max(sqmean[c] - mean[c]*mean[c], 0.)); |
|
|
|
dst.create(1, 2, CV_64FC4); |
|
dst.at<Scalar>(0,0) = mean; |
|
dst.at<Scalar>(0,1) = sqmean; |
|
} |
|
double getMaxErr(int) |
|
{ |
|
CV_Assert(cn > 0); |
|
double err = sqmeanRef[0]; |
|
for(int i = 1; i < cn; ++i) |
|
err = std::max(err, sqmeanRef[i]); |
|
return 3e-7 * err; |
|
} |
|
}; |
|
|
|
|
|
struct NormOp : public BaseElemWiseOp |
|
{ |
|
NormOp() : BaseElemWiseOp(2, FIX_ALPHA+FIX_BETA+FIX_GAMMA+SUPPORT_MASK+SCALAR_OUTPUT, 1, 1, Scalar::all(0)) |
|
{ |
|
context = 1; |
|
normType = 0; |
|
}; |
|
int getRandomType(RNG& rng) |
|
{ |
|
int type = cvtest::randomType(rng, DEPTH_MASK_ALL_BUT_8S, 1, 4); |
|
for(;;) |
|
{ |
|
normType = rng.uniform(1, 8); |
|
if( normType == NORM_INF || normType == NORM_L1 || |
|
normType == NORM_L2 || normType == NORM_L2SQR || |
|
normType == NORM_HAMMING || normType == NORM_HAMMING2 ) |
|
break; |
|
} |
|
if( normType == NORM_HAMMING || normType == NORM_HAMMING2 ) |
|
{ |
|
type = CV_8U; |
|
} |
|
return type; |
|
} |
|
void op(const vector<Mat>& src, Mat& dst, const Mat& mask) |
|
{ |
|
dst.create(1, 2, CV_64FC1); |
|
dst.at<double>(0,0) = cv::norm(src[0], normType, mask); |
|
dst.at<double>(0,1) = cv::norm(src[0], src[1], normType, mask); |
|
} |
|
void refop(const vector<Mat>& src, Mat& dst, const Mat& mask) |
|
{ |
|
dst.create(1, 2, CV_64FC1); |
|
dst.at<double>(0,0) = cvtest::norm(src[0], normType, mask); |
|
dst.at<double>(0,1) = cvtest::norm(src[0], src[1], normType, mask); |
|
} |
|
void generateScalars(int, RNG& rng) |
|
{ |
|
} |
|
double getMaxErr(int) |
|
{ |
|
return 1e-6; |
|
} |
|
int normType; |
|
}; |
|
|
|
|
|
struct MinMaxLocOp : public BaseElemWiseOp |
|
{ |
|
MinMaxLocOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA+SUPPORT_MASK+SCALAR_OUTPUT, 1, 1, Scalar::all(0)) |
|
{ |
|
context = ARITHM_MAX_NDIMS*2 + 2; |
|
}; |
|
int getRandomType(RNG& rng) |
|
{ |
|
return cvtest::randomType(rng, DEPTH_MASK_ALL_BUT_8S, 1, 1); |
|
} |
|
void saveOutput(const vector<int>& minidx, const vector<int>& maxidx, |
|
double minval, double maxval, Mat& dst) |
|
{ |
|
int i, ndims = (int)minidx.size(); |
|
dst.create(1, ndims*2 + 2, CV_64FC1); |
|
|
|
for( i = 0; i < ndims; i++ ) |
|
{ |
|
dst.at<double>(0,i) = minidx[i]; |
|
dst.at<double>(0,i+ndims) = maxidx[i]; |
|
} |
|
dst.at<double>(0,ndims*2) = minval; |
|
dst.at<double>(0,ndims*2+1) = maxval; |
|
} |
|
void op(const vector<Mat>& src, Mat& dst, const Mat& mask) |
|
{ |
|
int ndims = src[0].dims; |
|
vector<int> minidx(ndims), maxidx(ndims); |
|
double minval=0, maxval=0; |
|
cv::minMaxIdx(src[0], &minval, &maxval, &minidx[0], &maxidx[0], mask); |
|
saveOutput(minidx, maxidx, minval, maxval, dst); |
|
} |
|
void refop(const vector<Mat>& src, Mat& dst, const Mat& mask) |
|
{ |
|
int ndims=src[0].dims; |
|
vector<int> minidx(ndims), maxidx(ndims); |
|
double minval=0, maxval=0; |
|
cvtest::minMaxLoc(src[0], &minval, &maxval, &minidx, &maxidx, mask); |
|
saveOutput(minidx, maxidx, minval, maxval, dst); |
|
} |
|
double getMaxErr(int) |
|
{ |
|
return 0; |
|
} |
|
}; |
|
|
|
|
|
} |
|
|
|
typedef Ptr<cvtest::BaseElemWiseOp> ElemWiseOpPtr; |
|
class ElemWiseTest : public ::testing::TestWithParam<ElemWiseOpPtr> {}; |
|
|
|
TEST_P(ElemWiseTest, accuracy) |
|
{ |
|
ElemWiseOpPtr op = GetParam(); |
|
|
|
int testIdx = 0; |
|
RNG rng((uint64)cvtest::ARITHM_RNG_SEED); |
|
for( testIdx = 0; testIdx < cvtest::ARITHM_NTESTS; testIdx++ ) |
|
{ |
|
vector<int> size; |
|
op->getRandomSize(rng, size); |
|
int type = op->getRandomType(rng); |
|
int depth = CV_MAT_DEPTH(type); |
|
bool haveMask = (op->flags & cvtest::BaseElemWiseOp::SUPPORT_MASK) != 0 && rng.uniform(0, 4) == 0; |
|
|
|
double minval=0, maxval=0; |
|
op->getValueRange(depth, minval, maxval); |
|
int i, ninputs = op->ninputs; |
|
vector<Mat> src(ninputs); |
|
for( i = 0; i < ninputs; i++ ) |
|
src[i] = cvtest::randomMat(rng, size, type, minval, maxval, true); |
|
Mat dst0, dst, mask; |
|
if( haveMask ) |
|
mask = cvtest::randomMat(rng, size, CV_8U, 0, 2, true); |
|
|
|
if( (haveMask || ninputs == 0) && !(op->flags & cvtest::BaseElemWiseOp::SCALAR_OUTPUT)) |
|
{ |
|
dst0 = cvtest::randomMat(rng, size, type, minval, maxval, false); |
|
dst = cvtest::randomMat(rng, size, type, minval, maxval, true); |
|
cvtest::copy(dst, dst0); |
|
} |
|
op->generateScalars(depth, rng); |
|
|
|
op->refop(src, dst0, mask); |
|
op->op(src, dst, mask); |
|
|
|
double maxErr = op->getMaxErr(depth); |
|
vector<int> pos; |
|
ASSERT_PRED_FORMAT2(cvtest::MatComparator(maxErr, op->context), dst0, dst) << "\nsrc[0] ~ " << cvtest::MatInfo(!src.empty() ? src[0] : Mat()) << "\ntestCase #" << testIdx << "\n"; |
|
} |
|
} |
|
|
|
|
|
INSTANTIATE_TEST_CASE_P(Core_Copy, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::CopyOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_Set, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::SetOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_SetZero, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::SetZeroOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_ConvertScale, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::ConvertScaleOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_ConvertScaleAbs, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::ConvertScaleAbsOp))); |
|
|
|
INSTANTIATE_TEST_CASE_P(Core_Add, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::AddOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_Sub, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::SubOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_AddS, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::AddSOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_SubRS, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::SubRSOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_ScaleAdd, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::ScaleAddOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_AddWeighted, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::AddWeightedOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_AbsDiff, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::AbsDiffOp))); |
|
|
|
|
|
INSTANTIATE_TEST_CASE_P(Core_AbsDiffS, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::AbsDiffSOp))); |
|
|
|
INSTANTIATE_TEST_CASE_P(Core_And, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::LogicOp('&')))); |
|
INSTANTIATE_TEST_CASE_P(Core_AndS, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::LogicSOp('&')))); |
|
INSTANTIATE_TEST_CASE_P(Core_Or, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::LogicOp('|')))); |
|
INSTANTIATE_TEST_CASE_P(Core_OrS, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::LogicSOp('|')))); |
|
INSTANTIATE_TEST_CASE_P(Core_Xor, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::LogicOp('^')))); |
|
INSTANTIATE_TEST_CASE_P(Core_XorS, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::LogicSOp('^')))); |
|
INSTANTIATE_TEST_CASE_P(Core_Not, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::LogicSOp('~')))); |
|
|
|
INSTANTIATE_TEST_CASE_P(Core_Max, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::MaxOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_MaxS, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::MaxSOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_Min, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::MinOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_MinS, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::MinSOp))); |
|
|
|
INSTANTIATE_TEST_CASE_P(Core_Mul, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::MulOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_Div, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::DivOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_Recip, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::RecipOp))); |
|
|
|
INSTANTIATE_TEST_CASE_P(Core_Cmp, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::CmpOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_CmpS, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::CmpSOp))); |
|
|
|
INSTANTIATE_TEST_CASE_P(Core_InRangeS, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::InRangeSOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_InRange, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::InRangeOp))); |
|
|
|
INSTANTIATE_TEST_CASE_P(Core_Flip, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::FlipOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_Transpose, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::TransposeOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_SetIdentity, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::SetIdentityOp))); |
|
|
|
INSTANTIATE_TEST_CASE_P(Core_Exp, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::ExpOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_Log, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::LogOp))); |
|
|
|
INSTANTIATE_TEST_CASE_P(Core_CountNonZero, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::CountNonZeroOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_Mean, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::MeanOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_MeanStdDev, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::MeanStdDevOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_Sum, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::SumOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_Norm, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::NormOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_MinMaxLoc, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::MinMaxLocOp))); |
|
INSTANTIATE_TEST_CASE_P(Core_CartToPolarToCart, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new cvtest::CartToPolarToCartOp))); |
|
|
|
|
|
class CV_ArithmMaskTest : public cvtest::BaseTest |
|
{ |
|
public: |
|
CV_ArithmMaskTest() {} |
|
~CV_ArithmMaskTest() {} |
|
protected: |
|
void run(int) |
|
{ |
|
try |
|
{ |
|
RNG& rng = theRNG(); |
|
const int MAX_DIM=3; |
|
int sizes[MAX_DIM]; |
|
for( int iter = 0; iter < 100; iter++ ) |
|
{ |
|
//ts->printf(cvtest::TS::LOG, "."); |
|
|
|
ts->update_context(this, iter, true); |
|
int k, dims = rng.uniform(1, MAX_DIM+1), p = 1; |
|
int depth = rng.uniform(CV_8U, CV_64F+1); |
|
int cn = rng.uniform(1, 6); |
|
int type = CV_MAKETYPE(depth, cn); |
|
int op = rng.uniform(0, 5); |
|
int depth1 = op <= 1 ? CV_64F : depth; |
|
for( k = 0; k < dims; k++ ) |
|
{ |
|
sizes[k] = rng.uniform(1, 30); |
|
p *= sizes[k]; |
|
} |
|
Mat a(dims, sizes, type), a1; |
|
Mat b(dims, sizes, type), b1; |
|
Mat mask(dims, sizes, CV_8U); |
|
Mat mask1; |
|
Mat c, d; |
|
|
|
rng.fill(a, RNG::UNIFORM, 0, 100); |
|
rng.fill(b, RNG::UNIFORM, 0, 100); |
|
|
|
// [-2,2) range means that the each generated random number |
|
// will be one of -2, -1, 0, 1. Saturated to [0,255], it will become |
|
// 0, 0, 0, 1 => the mask will be filled by ~25%. |
|
rng.fill(mask, RNG::UNIFORM, -2, 2); |
|
|
|
a.convertTo(a1, depth1); |
|
b.convertTo(b1, depth1); |
|
// invert the mask |
|
compare(mask, 0, mask1, CMP_EQ); |
|
a1.setTo(0, mask1); |
|
b1.setTo(0, mask1); |
|
|
|
if( op == 0 ) |
|
{ |
|
add(a, b, c, mask); |
|
add(a1, b1, d); |
|
} |
|
else if( op == 1 ) |
|
{ |
|
subtract(a, b, c, mask); |
|
subtract(a1, b1, d); |
|
} |
|
else if( op == 2 ) |
|
{ |
|
bitwise_and(a, b, c, mask); |
|
bitwise_and(a1, b1, d); |
|
} |
|
else if( op == 3 ) |
|
{ |
|
bitwise_or(a, b, c, mask); |
|
bitwise_or(a1, b1, d); |
|
} |
|
else if( op == 4 ) |
|
{ |
|
bitwise_xor(a, b, c, mask); |
|
bitwise_xor(a1, b1, d); |
|
} |
|
Mat d1; |
|
d.convertTo(d1, depth); |
|
CV_Assert( norm(c, d1, CV_C) <= DBL_EPSILON ); |
|
} |
|
|
|
Mat_<uchar> tmpSrc(100,100); |
|
tmpSrc = 124; |
|
Mat_<uchar> tmpMask(100,100); |
|
tmpMask = 255; |
|
Mat_<uchar> tmpDst(100,100); |
|
tmpDst = 2; |
|
tmpSrc.copyTo(tmpDst,tmpMask); |
|
} |
|
catch(...) |
|
{ |
|
ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH); |
|
} |
|
} |
|
}; |
|
|
|
TEST(Core_ArithmMask, uninitialized) { CV_ArithmMaskTest test; test.safe_run(); } |
|
|
|
|
|
|