Open Source Computer Vision Library https://opencv.org/
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#include "test_precomp.hpp"
#include "opencv2/video/tracking_c.h"
namespace opencv_test { namespace {
/* ///////////////////// pyrlk_test ///////////////////////// */
class CV_OptFlowPyrLKTest : public cvtest::BaseTest
{
public:
CV_OptFlowPyrLKTest();
protected:
void run(int);
};
CV_OptFlowPyrLKTest::CV_OptFlowPyrLKTest() {}
void CV_OptFlowPyrLKTest::run( int )
{
int code = cvtest::TS::OK;
const double success_error_level = 0.3;
const int bad_points_max = 8;
/* test parameters */
double max_err = 0., sum_err = 0;
int pt_cmpd = 0;
int pt_exceed = 0;
int merr_i = 0, merr_j = 0, merr_k = 0, merr_nan = 0;
char filename[1000];
CvPoint2D32f *v = 0, *v2 = 0;
cv::Mat _u, _v, _v2;
cv::Mat imgI, imgJ;
int n = 0, i = 0;
for(;;)
{
sprintf( filename, "%soptflow/%s", ts->get_data_path().c_str(), "lk_prev.dat" );
{
FileStorage fs(filename, FileStorage::READ);
fs["points"] >> _u;
if( _u.empty() )
{
ts->printf( cvtest::TS::LOG, "could not read %s\n", filename );
code = cvtest::TS::FAIL_MISSING_TEST_DATA;
break;
}
}
sprintf( filename, "%soptflow/%s", ts->get_data_path().c_str(), "lk_next.dat" );
{
FileStorage fs(filename, FileStorage::READ);
fs["points"] >> _v;
if( _v.empty() )
{
ts->printf( cvtest::TS::LOG, "could not read %s\n", filename );
code = cvtest::TS::FAIL_MISSING_TEST_DATA;
break;
}
}
if( _u.cols != 2 || _u.type() != CV_32F ||
_v.cols != 2 || _v.type() != CV_32F ||
_v.rows != _u.rows )
{
ts->printf( cvtest::TS::LOG, "the loaded matrices of points are not valid\n" );
code = cvtest::TS::FAIL_MISSING_TEST_DATA;
break;
}
/* read first image */
sprintf( filename, "%soptflow/%s", ts->get_data_path().c_str(), "rock_1.bmp" );
imgI = cv::imread( filename, cv::IMREAD_UNCHANGED );
if( imgI.empty() )
{
ts->printf( cvtest::TS::LOG, "could not read %s\n", filename );
code = cvtest::TS::FAIL_MISSING_TEST_DATA;
break;
}
/* read second image */
sprintf( filename, "%soptflow/%s", ts->get_data_path().c_str(), "rock_2.bmp" );
imgJ = cv::imread( filename, cv::IMREAD_UNCHANGED );
if( imgJ.empty() )
{
ts->printf( cvtest::TS::LOG, "could not read %s\n", filename );
code = cvtest::TS::FAIL_MISSING_TEST_DATA;
break;
}
n = _u.rows;
std::vector<uchar> status(n, (uchar)0);
/* calculate flow */
calcOpticalFlowPyrLK(imgI, imgJ, _u, _v2, status, cv::noArray(), Size( 41, 41 ), 4,
TermCriteria( TermCriteria::MAX_ITER + TermCriteria::EPS, 30, 0.01f ), 0 );
v = (CvPoint2D32f*)_v.ptr();
v2 = (CvPoint2D32f*)_v2.ptr();
/* compare results */
for( i = 0; i < n; i++ )
{
if( status[i] != 0 )
{
double err;
if( cvIsNaN(v[i].x) || cvIsNaN(v[i].y) )
{
merr_j++;
continue;
}
if( cvIsNaN(v2[i].x) || cvIsNaN(v2[i].y) )
{
merr_nan++;
continue;
}
err = fabs(v2[i].x - v[i].x) + fabs(v2[i].y - v[i].y);
if( err > max_err )
{
max_err = err;
merr_i = i;
}
pt_exceed += err > success_error_level;
sum_err += err;
pt_cmpd++;
}
else
{
if( !cvIsNaN( v[i].x ))
{
merr_i = i;
merr_k++;
ts->printf( cvtest::TS::LOG, "The algorithm lost the point #%d\n", i );
code = cvtest::TS::FAIL_BAD_ACCURACY;
break;
}
}
}
if( i < n )
break;
if( pt_exceed > bad_points_max )
{
ts->printf( cvtest::TS::LOG,
"The number of poorly tracked points is too big (>=%d)\n", pt_exceed );
code = cvtest::TS::FAIL_BAD_ACCURACY;
break;
}
if( max_err > 1 )
{
ts->printf( cvtest::TS::LOG, "Maximum tracking error is too big (=%g) at %d\n", max_err, merr_i );
code = cvtest::TS::FAIL_BAD_ACCURACY;
break;
}
if( merr_nan > 0 )
{
ts->printf( cvtest::TS::LOG, "NAN tracking result with status != 0 (%d times)\n", merr_nan );
code = cvtest::TS::FAIL_BAD_ACCURACY;
}
break;
}
if( code < 0 )
ts->set_failed_test_info( code );
}
TEST(Video_OpticalFlowPyrLK, accuracy) { CV_OptFlowPyrLKTest test; test.safe_run(); }
TEST(Video_OpticalFlowPyrLK, submat)
{
// see bug #2075
std::string path = cvtest::TS::ptr()->get_data_path() + "../cv/shared/lena.png";
cv::Mat lenaImg = cv::imread(path);
ASSERT_FALSE(lenaImg.empty());
cv::Mat wholeImage;
cv::resize(lenaImg, wholeImage, cv::Size(1024, 1024), 0, 0, cv::INTER_LINEAR_EXACT);
cv::Mat img1 = wholeImage(cv::Rect(0, 0, 640, 360)).clone();
cv::Mat img2 = wholeImage(cv::Rect(40, 60, 640, 360));
std::vector<uchar> status;
std::vector<float> error;
std::vector<cv::Point2f> prev;
std::vector<cv::Point2f> next;
cv::RNG rng(123123);
for(int i = 0; i < 50; ++i)
{
int x = rng.uniform(0, 640);
int y = rng.uniform(0, 360);
prev.push_back(cv::Point2f((float)x, (float)y));
}
ASSERT_NO_THROW(cv::calcOpticalFlowPyrLK(img1, img2, prev, next, status, error));
}
}} // namespace