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opencv_contrib/modules/ximgproc/test/test_fast_hough_transform.cpp
Alexander Alekhin edfdf12c31 tests: refactor test files
2018-02-02 19:15:28 +03:00

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
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//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2015, Smart Engines Ltd, all rights reserved.
// Copyright (C) 2015, Institute for Information Transmission Problems of the Russian Academy of Sciences (Kharkevich Institute), all rights reserved.
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#include "test_precomp.hpp"
namespace opencv_test { namespace {
//----------------------utils---------------------------------------------------
template <typename T> struct Eps
{
static T get() { return 1; }
};
template <> struct Eps<float> { static float get() { return float(1e-3); } };
template <> struct Eps<double> { static double get() { return 1e-6; } };
template <typename T> struct MinPos
{
static T get() { return Eps<T>::get(); }
};
template <typename T> struct Max { static T get()
{
return saturate_cast<T>(numeric_limits<T>::max()); }
};
template <typename T> struct Rand
{
static T get(T _min = MinPos<T>::get(), T _max = Max<T>::get())
{
RNG& rng = TS::ptr()->get_rng();
return saturate_cast<T>(rng.uniform(int(std::max(MinPos<T>::get(),
_min)),
int(std::min(Max<T>::get(),
_max))));
}
};
template <> struct Rand <float>
{
static float get(float _min = MinPos<float>::get(),
float _max = Max<float>::get())
{
RNG& rng = TS::ptr()->get_rng();
return rng.uniform(std::max(MinPos<float>::get(), _min),
std::min(Max<float>::get(), _max));
}
};
template <> struct Rand <double>
{
static double get(double _min = MinPos<double>::get(),
double _max = Max<double>::get())
{
RNG& rng = TS::ptr()->get_rng();
return rng.uniform(std::max(MinPos<double>::get(), _min),
std::min(Max<double>::get(), _max));
}
};
template <typename T> struct Eq
{
static bool get(T a, T b)
{
return a < b ? b - a < Eps<T>::get() : a - b < Eps<T>::get();
}
};
//----------------------TestFHT-------------------------------------------------
class TestFHT
{
public:
TestFHT() : ts(TS::ptr()) {}
void run_n_tests(int depth,
int channels,
int pts_count,
int n_per_test);
private:
template <typename T>
int run_n_tests_t(int depth,
int channels,
int pts_count,
int n_per_test);
template <typename T>
int run_test(int depth,
int channels,
int pts_count);
template <typename T>
int put_random_points(Mat &img,
int count,
vector<Point> &pts);
int run_func(Mat const&src,
Mat& fht);
template <typename T>
int validate_test_results(Mat const &fht,
Mat const &src,
vector<Point> const& pts);
template <typename T> int validate_sum(Mat const& src, Mat const& fht);
int validate_point(Mat const& fht, vector<Point> const &pts);
int validate_line(Mat const& fht, Mat const& src, vector<Point> const& pts);
private:
TS *ts;
};
template <typename T>
int TestFHT::put_random_points(Mat &img, int count, vector<Point> &pts)
{
int code = TS::OK;
pts.resize(count, Point(-1, -1));
for (int i = 0; i < count; ++i)
{
RNG rng = ts->get_rng();
Point const pt(rng.uniform(0, img.cols),
rng.uniform(0, img.rows));
pts[i] = pt;
for (int c = 0; c < img.channels(); ++c)
{
T color = Rand<T>::get(MinPos<T>::get(),
T(Max<T>::get() / count));
T *img_line = (T*)(img.data + img.step * pt.y);
img_line[pt.x * img.channels() + c] = color;
}
}
return code;
}
template <typename T>
int TestFHT::validate_sum(Mat const& src, Mat const& fht)
{
int const channels = src.channels();
if (fht.channels() != channels)
return TS::FAIL_BAD_ARG_CHECK;
vector<Mat> src_channels(channels);
split(src, src_channels);
vector<Mat> fht_channels(channels);
split(fht, fht_channels);
for (int c = 0; c < channels; ++c)
{
T const src_sum = saturate_cast<T>(sum(src_channels[c]).val[0]);
for (int y = 0; y < fht.rows; ++y)
{
T const fht_sum = saturate_cast<T>(sum(fht_channels[c].row(y)).val[0]);
if (!Eq<T>::get(src_sum, fht_sum))
{
ts->printf(TS::LOG,
"The sum of column #%d of channel #%d of the fast "
"hough transform result and the sum of source image"
" mismatch (=%g, should be =%g)\n",
y, c, (float)fht_sum, (float)src_sum);
return TS::FAIL_BAD_ACCURACY;
}
}
}
return TS::OK;
}
int TestFHT::validate_point(Mat const& fht,
vector<Point> const &pts)
{
if (pts.empty())
return TS::OK;
for (size_t i = 1; i < pts.size(); ++i)
{
if (pts[0] != pts[i])
return TS::OK;
}
int const channels = fht.channels();
vector<Mat> fht_channels(channels);
split(fht, fht_channels);
for (int c = 0; c < channels; ++c)
{
for (int y = 0; y < fht.rows; ++y)
{
int cnt = countNonZero(fht_channels[c].row(y));
if (cnt != 1)
{
ts->printf(TS::LOG,
"The incorrect count of non-zero values in column "
"#%d, channel #%d of FastHoughTransform result "
"image (=%d, should be %d)\n",
y, c, cnt, 1);
return TS::FAIL_BAD_ACCURACY;
}
}
}
return TS::OK;
}
static const double MAX_LDIST = 2.0;
int TestFHT::validate_line(Mat const& fht,
Mat const& src,
vector<Point> const& pts)
{
size_t const size = (int)pts.size();
if (size < 2)
return TS::OK;
size_t first_pt_i = 0, second_pt_i = 1;
for (size_t i = first_pt_i + 1; i < size; ++i)
{
if (pts[i] != pts[first_pt_i])
{
second_pt_i = first_pt_i;
break;
}
}
if (pts[second_pt_i] == pts[first_pt_i])
return TS::OK;
for (size_t i = second_pt_i + 1; i < size; ++i)
{
if (pts[i] != pts[second_pt_i])
return TS::OK;
}
const Point &f = pts[first_pt_i];
const Point &s = pts[second_pt_i];
int const channels = fht.channels();
vector<Mat> fht_channels(channels);
split(fht, fht_channels);
for (int ch = 0; ch < channels; ++ch)
{
Point fht_max(-1, -1);
minMaxLoc(fht_channels[ch], 0, 0, 0, &fht_max);
Vec4i src_line = HoughPoint2Line(fht_max, src,
ARO_315_135, HDO_DESKEW, RO_STRICT);
double const a = src_line[1] - src_line[3];
double const b = src_line[2] - src_line[0];
double const c = - (a * src_line[0] + b * src_line[1]);
double const fd = abs(f.x * a + f.y * b + c) / sqrt(a * a + b * b);
double const sd = abs(s.x * a + s.y * b + c) / sqrt(a * a + b * b);
double const dist = std::max(fd, sd);
if (dist > MAX_LDIST)
{
ts->printf(TS::LOG,
"Failed to detect max line in channels %d (distance "
"between point and line correspoinding of maximum in "
"FastHoughTransform space is #%g)\n", ch, dist);
return TS::FAIL_BAD_ACCURACY;
}
}
return TS::OK;
}
template <typename T>
int TestFHT::validate_test_results(Mat const &fht,
Mat const &src,
vector<Point> const& pts)
{
int code = validate_sum<T>(src, fht);
if (code == TS::OK)
code = validate_point(fht, pts);
if (code == TS::OK)
code = validate_line(fht, src, pts);
return code;
}
int TestFHT::run_func(Mat const&src,
Mat& fht)
{
int code = TS::OK;
FastHoughTransform(src, fht, src.depth());
return code;
}
static Size random_size(int const max_size_log,
int const elem_size)
{
RNG& rng = TS::ptr()->get_rng();
return randomSize(rng, std::max(1,
max_size_log - cvRound(log(double(elem_size)))));
}
static const int FHT_MAX_SIZE_LOG = 9;
template <typename T>
int TestFHT::run_test(int depth,
int channels,
int pts_count)
{
int code = TS::OK;
Size size = random_size(FHT_MAX_SIZE_LOG,
CV_ELEM_SIZE(CV_MAKE_TYPE(depth, channels)));
Mat src = Mat::zeros(size, CV_MAKETYPE(depth, channels));
vector<Point> pts;
code = put_random_points<T>(src, pts_count, pts);
if (code != TS::OK)
return code;
Mat fht;
code = run_func(src, fht);
if (code != TS::OK)
return code;
code = validate_test_results<T>(fht, src, pts);
return code;
}
void TestFHT::run_n_tests(int depth,
int channels,
int pts_count,
int n)
{
try
{
int code = TS::OK;
switch (depth)
{
case CV_8U:
code = run_n_tests_t<uchar>(depth, channels, pts_count, n);
break;
case CV_8S:
code = run_n_tests_t<schar>(depth, channels, pts_count, n);
break;
case CV_16U:
code = run_n_tests_t<ushort>(depth, channels, pts_count, n);
break;
case CV_16S:
code = run_n_tests_t<short>(depth, channels, pts_count, n);
break;
case CV_32S:
code = run_n_tests_t<int>(depth, channels, pts_count, n);
break;
case CV_32F:
code = run_n_tests_t<float>(depth, channels, pts_count, n);
break;
case CV_64F:
code = run_n_tests_t<double>(depth, channels, pts_count, n);
break;
default:
code = TS::FAIL_BAD_ARG_CHECK;
ts->printf(TS::LOG, "Unknown depth %d\n", depth);
break;
}
if (code != TS::OK)
throw TS::FailureCode(code);
}
catch (const TS::FailureCode& fc)
{
std::string errorStr = TS::str_from_code(fc);
ts->printf(TS::LOG,
"General failure:\n\t%s (%d)\n", errorStr.c_str(), fc);
ts->set_failed_test_info(fc);
}
catch(...)
{
ts->printf(TS::LOG, "Unknown failure\n");
ts->set_failed_test_info(TS::FAIL_EXCEPTION);
}
}
template <typename T>
int TestFHT::run_n_tests_t(int depth,
int channels,
int pts_count,
int n)
{
int code = TS::OK;
for (int iTest = 0; iTest < n; ++iTest)
{
code = run_test<T>(depth, channels, pts_count);
if (code != TS::OK)
{
ts->printf(TS::LOG, "Test %d failed with code %d\n", iTest, code);
break;
}
}
return code;
}
//----------------------TEST_P--------------------------------------------------
typedef tuple<int, int, int, int> Depth_Channels_PtsC_nPerTest;
typedef TestWithParam<Depth_Channels_PtsC_nPerTest> FastHoughTransformTest;
TEST_P(FastHoughTransformTest, accuracy)
{
int const depth = get<0>(GetParam());
int const channels = get<1>(GetParam());
int const pts_count = get<2>(GetParam());
int const n_per_test = get<3>(GetParam());
TestFHT testFht;
testFht.run_n_tests(depth, channels, pts_count, n_per_test);
}
#define FHT_ALL_DEPTHS CV_8U, CV_16U, CV_32S, CV_32F, CV_64F
#define FHT_ALL_CHANNELS 1, 3, 4
INSTANTIATE_TEST_CASE_P(FullSet, FastHoughTransformTest,
Combine(Values(FHT_ALL_DEPTHS),
Values(FHT_ALL_CHANNELS),
Values(1, 2),
Values(5)));
#undef FHT_ALL_DEPTHS
#undef FHT_ALL_CHANNELS
}} // namespace
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