mirror of
https://github.com/opencv/opencv.git
synced 2024-12-05 09:49:12 +08:00
d6c699c014
stereo module in opencv_contrib is renamed to xstereo
232 lines
8.5 KiB
C++
232 lines
8.5 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
|
|
//
|
|
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
|
|
//
|
|
// By downloading, copying, installing or using the software you agree to this license.
|
|
// If you do not agree to this license, do not download, install,
|
|
// copy or use the software.
|
|
//
|
|
//
|
|
// Intel License Agreement
|
|
// For Open Source Computer Vision Library
|
|
//
|
|
// Copyright (C) 2000, Intel Corporation, all rights reserved.
|
|
// Third party copyrights are property of their respective owners.
|
|
//
|
|
// Redistribution and use in source and binary forms, with or without modification,
|
|
// are permitted provided that the following conditions are met:
|
|
//
|
|
// * Redistribution's of source code must retain the above copyright notice,
|
|
// this list of conditions and the following disclaimer.
|
|
//
|
|
// * Redistribution's in binary form must reproduce the above copyright notice,
|
|
// this list of conditions and the following disclaimer in the documentation
|
|
// and/or other materials provided with the distribution.
|
|
//
|
|
// * The name of Intel Corporation may not be used to endorse or promote products
|
|
// derived from this software without specific prior written permission.
|
|
//
|
|
// This software is provided by the copyright holders and contributors "as is" and
|
|
// any express or implied warranties, including, but not limited to, the implied
|
|
// warranties of merchantability and fitness for a particular purpose are disclaimed.
|
|
// In no event shall the Intel Corporation or contributors be liable for any direct,
|
|
// indirect, incidental, special, exemplary, or consequential damages
|
|
// (including, but not limited to, procurement of substitute goods or services;
|
|
// loss of use, data, or profits; or business interruption) however caused
|
|
// and on any theory of liability, whether in contract, strict liability,
|
|
// or tort (including negligence or otherwise) arising in any way out of
|
|
// the use of this software, even if advised of the possibility of such damage.
|
|
//
|
|
//M*/
|
|
|
|
#include "test_precomp.hpp"
|
|
|
|
#if 0
|
|
#include "_modelest.h"
|
|
|
|
using namespace std;
|
|
using namespace cv;
|
|
|
|
class BareModelEstimator : public CvModelEstimator2
|
|
{
|
|
public:
|
|
BareModelEstimator(int modelPoints, CvSize modelSize, int maxBasicSolutions);
|
|
|
|
virtual int runKernel( const CvMat*, const CvMat*, CvMat* );
|
|
virtual void computeReprojError( const CvMat*, const CvMat*,
|
|
const CvMat*, CvMat* );
|
|
|
|
bool checkSubsetPublic( const CvMat* ms1, int count, bool checkPartialSubset );
|
|
};
|
|
|
|
BareModelEstimator::BareModelEstimator(int _modelPoints, CvSize _modelSize, int _maxBasicSolutions)
|
|
:CvModelEstimator2(_modelPoints, _modelSize, _maxBasicSolutions)
|
|
{
|
|
}
|
|
|
|
int BareModelEstimator::runKernel( const CvMat*, const CvMat*, CvMat* )
|
|
{
|
|
return 0;
|
|
}
|
|
|
|
void BareModelEstimator::computeReprojError( const CvMat*, const CvMat*,
|
|
const CvMat*, CvMat* )
|
|
{
|
|
}
|
|
|
|
bool BareModelEstimator::checkSubsetPublic( const CvMat* ms1, int count, bool checkPartialSubset )
|
|
{
|
|
checkPartialSubsets = checkPartialSubset;
|
|
return checkSubset(ms1, count);
|
|
}
|
|
|
|
class CV_ModelEstimator2_Test : public cvtest::ArrayTest
|
|
{
|
|
public:
|
|
CV_ModelEstimator2_Test();
|
|
|
|
protected:
|
|
void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
|
|
void fill_array( int test_case_idx, int i, int j, Mat& arr );
|
|
double get_success_error_level( int test_case_idx, int i, int j );
|
|
void run_func();
|
|
void prepare_to_validation( int test_case_idx );
|
|
|
|
bool checkPartialSubsets;
|
|
int usedPointsCount;
|
|
|
|
bool checkSubsetResult;
|
|
int generalPositionsCount;
|
|
int maxPointsCount;
|
|
};
|
|
|
|
CV_ModelEstimator2_Test::CV_ModelEstimator2_Test()
|
|
{
|
|
generalPositionsCount = get_test_case_count() / 2;
|
|
maxPointsCount = 100;
|
|
|
|
test_array[INPUT].push_back(NULL);
|
|
test_array[OUTPUT].push_back(NULL);
|
|
test_array[REF_OUTPUT].push_back(NULL);
|
|
}
|
|
|
|
void CV_ModelEstimator2_Test::get_test_array_types_and_sizes( int /*test_case_idx*/,
|
|
vector<vector<Size> > &sizes, vector<vector<int> > &types )
|
|
{
|
|
RNG &rng = ts->get_rng();
|
|
checkPartialSubsets = (cvtest::randInt(rng) % 2 == 0);
|
|
|
|
int pointsCount = cvtest::randInt(rng) % maxPointsCount;
|
|
usedPointsCount = pointsCount == 0 ? 0 : cvtest::randInt(rng) % pointsCount;
|
|
|
|
sizes[INPUT][0] = cvSize(1, pointsCount);
|
|
types[INPUT][0] = CV_64FC2;
|
|
|
|
sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(1, 1);
|
|
types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_8UC1;
|
|
}
|
|
|
|
void CV_ModelEstimator2_Test::fill_array( int test_case_idx, int i, int j, Mat& arr )
|
|
{
|
|
if( i != INPUT )
|
|
{
|
|
cvtest::ArrayTest::fill_array( test_case_idx, i, j, arr );
|
|
return;
|
|
}
|
|
|
|
if (test_case_idx < generalPositionsCount)
|
|
{
|
|
//generate points in a general position (i.e. no three points can lie on the same line.)
|
|
|
|
bool isGeneralPosition;
|
|
do
|
|
{
|
|
ArrayTest::fill_array(test_case_idx, i, j, arr);
|
|
|
|
//a simple check that the position is general:
|
|
// for each line check that all other points don't belong to it
|
|
isGeneralPosition = true;
|
|
for (int startPointIndex = 0; startPointIndex < usedPointsCount && isGeneralPosition; startPointIndex++)
|
|
{
|
|
for (int endPointIndex = startPointIndex + 1; endPointIndex < usedPointsCount && isGeneralPosition; endPointIndex++)
|
|
{
|
|
|
|
for (int testPointIndex = 0; testPointIndex < usedPointsCount && isGeneralPosition; testPointIndex++)
|
|
{
|
|
if (testPointIndex == startPointIndex || testPointIndex == endPointIndex)
|
|
{
|
|
continue;
|
|
}
|
|
|
|
CV_Assert(arr.type() == CV_64FC2);
|
|
Point2d tangentVector_1 = arr.at<Point2d>(endPointIndex) - arr.at<Point2d>(startPointIndex);
|
|
Point2d tangentVector_2 = arr.at<Point2d>(testPointIndex) - arr.at<Point2d>(startPointIndex);
|
|
|
|
const float eps = 1e-4f;
|
|
//TODO: perhaps it is better to normalize the cross product by norms of the tangent vectors
|
|
if (fabs(tangentVector_1.cross(tangentVector_2)) < eps)
|
|
{
|
|
isGeneralPosition = false;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
while(!isGeneralPosition);
|
|
}
|
|
else
|
|
{
|
|
//create points in a degenerate position (there are at least 3 points belonging to the same line)
|
|
|
|
ArrayTest::fill_array(test_case_idx, i, j, arr);
|
|
if (usedPointsCount <= 2)
|
|
{
|
|
return;
|
|
}
|
|
|
|
RNG &rng = ts->get_rng();
|
|
int startPointIndex, endPointIndex, modifiedPointIndex;
|
|
do
|
|
{
|
|
startPointIndex = cvtest::randInt(rng) % usedPointsCount;
|
|
endPointIndex = cvtest::randInt(rng) % usedPointsCount;
|
|
modifiedPointIndex = checkPartialSubsets ? usedPointsCount - 1 : cvtest::randInt(rng) % usedPointsCount;
|
|
}
|
|
while (startPointIndex == endPointIndex || startPointIndex == modifiedPointIndex || endPointIndex == modifiedPointIndex);
|
|
|
|
double startWeight = cvtest::randReal(rng);
|
|
CV_Assert(arr.type() == CV_64FC2);
|
|
arr.at<Point2d>(modifiedPointIndex) = startWeight * arr.at<Point2d>(startPointIndex) + (1.0 - startWeight) * arr.at<Point2d>(endPointIndex);
|
|
}
|
|
}
|
|
|
|
|
|
double CV_ModelEstimator2_Test::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
|
|
{
|
|
return 0;
|
|
}
|
|
|
|
void CV_ModelEstimator2_Test::prepare_to_validation( int test_case_idx )
|
|
{
|
|
test_mat[OUTPUT][0].at<uchar>(0) = checkSubsetResult;
|
|
test_mat[REF_OUTPUT][0].at<uchar>(0) = test_case_idx < generalPositionsCount || usedPointsCount <= 2;
|
|
}
|
|
|
|
void CV_ModelEstimator2_Test::run_func()
|
|
{
|
|
//make the input continuous
|
|
Mat input = test_mat[INPUT][0].clone();
|
|
CvMat _input = input;
|
|
|
|
RNG &rng = ts->get_rng();
|
|
int modelPoints = cvtest::randInt(rng);
|
|
CvSize modelSize = cvSize(2, modelPoints);
|
|
int maxBasicSolutions = cvtest::randInt(rng);
|
|
BareModelEstimator modelEstimator(modelPoints, modelSize, maxBasicSolutions);
|
|
checkSubsetResult = modelEstimator.checkSubsetPublic(&_input, usedPointsCount, checkPartialSubsets);
|
|
}
|
|
|
|
TEST(Calib3d_ModelEstimator2, accuracy) { CV_ModelEstimator2_Test test; test.safe_run(); }
|
|
|
|
#endif
|