255 lines
6.8 KiB
C++
255 lines
6.8 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000, Intel Corporation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of Intel Corporation may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "test_precomp.hpp"
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#define VARNAME(A) #A
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using namespace std;
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using namespace cv;
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using namespace cv::gpu;
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using namespace cvtest;
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//std::string generateVarList(int first,...)
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//{
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// vector<std::string> varname;
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//
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// va_list argp;
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// string s;
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// stringstream ss;
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// va_start(argp,first);
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// int i=first;
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// while(i!=-1)
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// {
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// ss<<i<<",";
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// i=va_arg(argp,int);
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// };
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// s=ss.str();
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// va_end(argp);
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// return s;
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//};
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//std::string generateVarList(int& p1,int& p2)
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//{
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// stringstream ss;
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// ss<<VARNAME(p1)<<":"<<src1x<<","<<VARNAME(p2)<<":"<<src1y;
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// return ss.str();
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//};
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int randomInt(int minVal, int maxVal)
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{
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RNG &rng = TS::ptr()->get_rng();
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return rng.uniform(minVal, maxVal);
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}
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double randomDouble(double minVal, double maxVal)
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{
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RNG &rng = TS::ptr()->get_rng();
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return rng.uniform(minVal, maxVal);
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}
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Size randomSize(int minVal, int maxVal)
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{
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return cv::Size(randomInt(minVal, maxVal), randomInt(minVal, maxVal));
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}
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Scalar randomScalar(double minVal, double maxVal)
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{
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return Scalar(randomDouble(minVal, maxVal), randomDouble(minVal, maxVal), randomDouble(minVal, maxVal), randomDouble(minVal, maxVal));
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}
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Mat randomMat(Size size, int type, double minVal, double maxVal)
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{
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return randomMat(TS::ptr()->get_rng(), size, type, minVal, maxVal, false);
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}
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/*
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void showDiff(InputArray gold_, InputArray actual_, double eps)
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{
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Mat gold;
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if (gold_.kind() == _InputArray::MAT)
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gold = gold_.getMat();
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else
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gold_.getGpuMat().download(gold);
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Mat actual;
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if (actual_.kind() == _InputArray::MAT)
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actual = actual_.getMat();
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else
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actual_.getGpuMat().download(actual);
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Mat diff;
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absdiff(gold, actual, diff);
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threshold(diff, diff, eps, 255.0, cv::THRESH_BINARY);
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namedWindow("gold", WINDOW_NORMAL);
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namedWindow("actual", WINDOW_NORMAL);
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namedWindow("diff", WINDOW_NORMAL);
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imshow("gold", gold);
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imshow("actual", actual);
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imshow("diff", diff);
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waitKey();
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}
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*/
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vector<MatType> types(int depth_start, int depth_end, int cn_start, int cn_end)
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{
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vector<MatType> v;
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v.reserve((depth_end - depth_start + 1) * (cn_end - cn_start + 1));
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for (int depth = depth_start; depth <= depth_end; ++depth)
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{
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for (int cn = cn_start; cn <= cn_end; ++cn)
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{
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v.push_back(CV_MAKETYPE(depth, cn));
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}
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}
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return v;
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}
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const vector<MatType> &all_types()
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{
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static vector<MatType> v = types(CV_8U, CV_64F, 1, 4);
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return v;
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}
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Mat readImage(const string &fileName, int flags)
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{
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return imread(string(cvtest::TS::ptr()->get_data_path()) + fileName, flags);
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}
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Mat readImageType(const string &fname, int type)
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{
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Mat src = readImage(fname, CV_MAT_CN(type) == 1 ? IMREAD_GRAYSCALE : IMREAD_COLOR);
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if (CV_MAT_CN(type) == 4)
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{
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Mat temp;
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cvtColor(src, temp, cv::COLOR_BGR2BGRA);
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swap(src, temp);
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}
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src.convertTo(src, CV_MAT_DEPTH(type));
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return src;
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}
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double checkNorm(const Mat &m)
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{
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return norm(m, NORM_INF);
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}
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double checkNorm(const Mat &m1, const Mat &m2)
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{
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return norm(m1, m2, NORM_INF);
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}
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double checkSimilarity(const Mat &m1, const Mat &m2)
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{
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Mat diff;
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matchTemplate(m1, m2, diff, CV_TM_CCORR_NORMED);
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return std::abs(diff.at<float>(0, 0) - 1.f);
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}
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/*
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void cv::ocl::PrintTo(const DeviceInfo& info, ostream* os)
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{
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(*os) << info.name();
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}
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*/
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void PrintTo(const Inverse &inverse, std::ostream *os)
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{
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if (inverse)
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(*os) << "inverse";
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else
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(*os) << "direct";
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}
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double checkRectSimilarity(Size sz, std::vector<Rect>& ob1, std::vector<Rect>& ob2)
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{
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double final_test_result = 0.0;
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size_t sz1 = ob1.size();
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size_t sz2 = ob2.size();
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if(sz1 != sz2)
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{
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return sz1 > sz2 ? (double)(sz1 - sz2) : (double)(sz2 - sz1);
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}
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else
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{
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if(sz1==0 && sz2==0)
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return 0;
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cv::Mat cpu_result(sz, CV_8UC1);
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cpu_result.setTo(0);
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for(vector<Rect>::const_iterator r = ob1.begin(); r != ob1.end(); r++)
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{
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cv::Mat cpu_result_roi(cpu_result, *r);
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cpu_result_roi.setTo(1);
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cpu_result.copyTo(cpu_result);
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}
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int cpu_area = cv::countNonZero(cpu_result > 0);
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cv::Mat gpu_result(sz, CV_8UC1);
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gpu_result.setTo(0);
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for(vector<Rect>::const_iterator r2 = ob2.begin(); r2 != ob2.end(); r2++)
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{
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cv::Mat gpu_result_roi(gpu_result, *r2);
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gpu_result_roi.setTo(1);
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gpu_result.copyTo(gpu_result);
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}
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cv::Mat result_;
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multiply(cpu_result, gpu_result, result_);
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int result = cv::countNonZero(result_ > 0);
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if(cpu_area!=0 && result!=0)
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final_test_result = 1.0 - (double)result/(double)cpu_area;
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else if(cpu_area==0 && result!=0)
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final_test_result = -1;
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}
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return final_test_result;
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}
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