mirror of
https://github.com/opencv/opencv.git
synced 2024-12-15 18:09:11 +08:00
260 lines
9.4 KiB
C++
260 lines
9.4 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"
|
|
#include "opencv2/imgproc/imgproc_c.h"
|
|
#include "test_chessboardgenerator.hpp"
|
|
|
|
namespace opencv_test { namespace {
|
|
|
|
class CV_ChessboardSubpixelTest : public cvtest::BaseTest
|
|
{
|
|
public:
|
|
CV_ChessboardSubpixelTest();
|
|
|
|
protected:
|
|
Mat intrinsic_matrix_;
|
|
Mat distortion_coeffs_;
|
|
Size image_size_;
|
|
|
|
void run(int);
|
|
void generateIntrinsicParams();
|
|
};
|
|
|
|
|
|
int calcDistance(const vector<Point2f>& set1, const vector<Point2f>& set2, double& mean_dist)
|
|
{
|
|
if(set1.size() != set2.size())
|
|
{
|
|
return 0;
|
|
}
|
|
|
|
std::vector<int> indices;
|
|
double sum_dist = 0.0;
|
|
for(size_t i = 0; i < set1.size(); i++)
|
|
{
|
|
double min_dist = std::numeric_limits<double>::max();
|
|
int min_idx = -1;
|
|
|
|
for(int j = 0; j < (int)set2.size(); j++)
|
|
{
|
|
double dist = cv::norm(set1[i] - set2[j]); // TODO cvtest
|
|
if(dist < min_dist)
|
|
{
|
|
min_idx = j;
|
|
min_dist = dist;
|
|
}
|
|
}
|
|
|
|
// check validity of min_idx
|
|
if(min_idx == -1)
|
|
{
|
|
return 0;
|
|
}
|
|
std::vector<int>::iterator it = std::find(indices.begin(), indices.end(), min_idx);
|
|
if(it != indices.end())
|
|
{
|
|
// there are two points in set1 corresponding to the same point in set2
|
|
return 0;
|
|
}
|
|
indices.push_back(min_idx);
|
|
|
|
// printf("dist %d = %f\n", (int)i, min_dist);
|
|
|
|
sum_dist += min_dist*min_dist;
|
|
}
|
|
|
|
mean_dist = sqrt(sum_dist/set1.size());
|
|
// printf("sum_dist = %f, set1.size() = %d, mean_dist = %f\n", sum_dist, (int)set1.size(), mean_dist);
|
|
|
|
return 1;
|
|
}
|
|
|
|
CV_ChessboardSubpixelTest::CV_ChessboardSubpixelTest() :
|
|
intrinsic_matrix_(Size(3, 3), CV_64FC1), distortion_coeffs_(Size(1, 4), CV_64FC1),
|
|
image_size_(640, 480)
|
|
{
|
|
}
|
|
|
|
/* ///////////////////// chess_corner_test ///////////////////////// */
|
|
void CV_ChessboardSubpixelTest::run( int )
|
|
{
|
|
int code = cvtest::TS::OK;
|
|
int progress = 0;
|
|
|
|
RNG& rng = ts->get_rng();
|
|
|
|
const int runs_count = 20;
|
|
const int max_pattern_size = 8;
|
|
const int min_pattern_size = 5;
|
|
Mat bg(image_size_, CV_8UC1);
|
|
bg = Scalar(0);
|
|
|
|
double sum_dist = 0.0;
|
|
int count = 0;
|
|
for(int i = 0; i < runs_count; i++)
|
|
{
|
|
const int pattern_width = min_pattern_size + cvtest::randInt(rng) % (max_pattern_size - min_pattern_size);
|
|
const int pattern_height = min_pattern_size + cvtest::randInt(rng) % (max_pattern_size - min_pattern_size);
|
|
Size pattern_size;
|
|
if(pattern_width > pattern_height)
|
|
{
|
|
pattern_size = Size(pattern_height, pattern_width);
|
|
}
|
|
else
|
|
{
|
|
pattern_size = Size(pattern_width, pattern_height);
|
|
}
|
|
ChessBoardGenerator gen_chessboard(Size(pattern_size.width + 1, pattern_size.height + 1));
|
|
|
|
// generates intrinsic camera and distortion matrices
|
|
generateIntrinsicParams();
|
|
|
|
vector<Point2f> corners;
|
|
Mat chessboard_image = gen_chessboard(bg, intrinsic_matrix_, distortion_coeffs_, corners);
|
|
|
|
vector<Point2f> test_corners;
|
|
bool result = findChessboardCorners(chessboard_image, pattern_size, test_corners, 15);
|
|
if (!result && cvtest::debugLevel > 0)
|
|
{
|
|
ts->printf(cvtest::TS::LOG, "Warning: chessboard was not detected! Writing image to test.png\n");
|
|
ts->printf(cvtest::TS::LOG, "Size = %d, %d\n", pattern_size.width, pattern_size.height);
|
|
ts->printf(cvtest::TS::LOG, "Intrinsic params: fx = %f, fy = %f, cx = %f, cy = %f\n",
|
|
intrinsic_matrix_.at<double>(0, 0), intrinsic_matrix_.at<double>(1, 1),
|
|
intrinsic_matrix_.at<double>(0, 2), intrinsic_matrix_.at<double>(1, 2));
|
|
ts->printf(cvtest::TS::LOG, "Distortion matrix: %f, %f, %f, %f, %f\n",
|
|
distortion_coeffs_.at<double>(0, 0), distortion_coeffs_.at<double>(0, 1),
|
|
distortion_coeffs_.at<double>(0, 2), distortion_coeffs_.at<double>(0, 3),
|
|
distortion_coeffs_.at<double>(0, 4));
|
|
|
|
imwrite("test.png", chessboard_image);
|
|
}
|
|
if (!result)
|
|
{
|
|
continue;
|
|
}
|
|
|
|
double dist1 = 0.0;
|
|
int ret = calcDistance(corners, test_corners, dist1);
|
|
if(ret == 0)
|
|
{
|
|
ts->printf(cvtest::TS::LOG, "findChessboardCorners returns invalid corner coordinates!\n");
|
|
code = cvtest::TS::FAIL_INVALID_OUTPUT;
|
|
break;
|
|
}
|
|
|
|
IplImage chessboard_image_header = cvIplImage(chessboard_image);
|
|
cvFindCornerSubPix(&chessboard_image_header, (CvPoint2D32f*)&test_corners[0],
|
|
(int)test_corners.size(), cvSize(3, 3), cvSize(1, 1), cvTermCriteria(CV_TERMCRIT_EPS|CV_TERMCRIT_ITER,300,0.1));
|
|
find4QuadCornerSubpix(chessboard_image, test_corners, Size(5, 5));
|
|
|
|
double dist2 = 0.0;
|
|
ret = calcDistance(corners, test_corners, dist2);
|
|
if(ret == 0)
|
|
{
|
|
ts->printf(cvtest::TS::LOG, "findCornerSubpix returns invalid corner coordinates!\n");
|
|
code = cvtest::TS::FAIL_INVALID_OUTPUT;
|
|
break;
|
|
}
|
|
|
|
ts->printf(cvtest::TS::LOG, "Error after findChessboardCorners: %f, after findCornerSubPix: %f\n",
|
|
dist1, dist2);
|
|
sum_dist += dist2;
|
|
count++;
|
|
|
|
const double max_reduce_factor = 0.8;
|
|
if(dist1 < dist2*max_reduce_factor)
|
|
{
|
|
ts->printf(cvtest::TS::LOG, "findCornerSubPix increases average error!\n");
|
|
code = cvtest::TS::FAIL_INVALID_OUTPUT;
|
|
break;
|
|
}
|
|
|
|
progress = update_progress( progress, i-1, runs_count, 0 );
|
|
}
|
|
ASSERT_NE(0, count);
|
|
sum_dist /= count;
|
|
ts->printf(cvtest::TS::LOG, "Average error after findCornerSubpix: %f\n", sum_dist);
|
|
|
|
if( code < 0 )
|
|
ts->set_failed_test_info( code );
|
|
}
|
|
|
|
void CV_ChessboardSubpixelTest::generateIntrinsicParams()
|
|
{
|
|
RNG& rng = ts->get_rng();
|
|
const double max_focus_length = 1000.0;
|
|
const double max_focus_diff = 5.0;
|
|
|
|
double fx = cvtest::randReal(rng)*max_focus_length;
|
|
double fy = fx + cvtest::randReal(rng)*max_focus_diff;
|
|
double cx = image_size_.width/2;
|
|
double cy = image_size_.height/2;
|
|
|
|
double k1 = 0.5*cvtest::randReal(rng);
|
|
double k2 = 0.05*cvtest::randReal(rng);
|
|
double p1 = 0.05*cvtest::randReal(rng);
|
|
double p2 = 0.05*cvtest::randReal(rng);
|
|
double k3 = 0.0;
|
|
|
|
intrinsic_matrix_ = (Mat_<double>(3, 3) << fx, 0.0, cx, 0.0, fy, cy, 0.0, 0.0, 1.0);
|
|
distortion_coeffs_ = (Mat_<double>(1, 5) << k1, k2, p1, p2, k3);
|
|
}
|
|
|
|
TEST(Calib3d_ChessboardSubPixDetector, accuracy) { CV_ChessboardSubpixelTest test; test.safe_run(); }
|
|
|
|
TEST(Calib3d_CornerSubPix, regression_7204)
|
|
{
|
|
cv::Mat image(cv::Size(70, 38), CV_8UC1, cv::Scalar::all(0));
|
|
image(cv::Rect(65, 26, 5, 5)).setTo(cv::Scalar::all(255));
|
|
image(cv::Rect(55, 31, 8, 1)).setTo(cv::Scalar::all(255));
|
|
image(cv::Rect(56, 35, 14, 2)).setTo(cv::Scalar::all(255));
|
|
image(cv::Rect(66, 24, 4, 2)).setTo(cv::Scalar::all(255));
|
|
image.at<uchar>(24, 69) = 0;
|
|
std::vector<cv::Point2f> corners;
|
|
corners.push_back(cv::Point2f(65, 30));
|
|
cv::cornerSubPix(image, corners, cv::Size(3, 3), cv::Size(-1, -1),
|
|
cv::TermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 30, 0.1));
|
|
}
|
|
|
|
}} // namespace
|
|
/* End of file. */
|