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// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html
#include "opencv2/imgproc.hpp"
#include "test_precomp.hpp"
using namespace cv;
using namespace std;
namespace opencv_test { namespace {
//==============================================================================
// Utility
template <typename T>
inline T sqr(T val)
{
return val * val;
}
inline static float calcEMD(Mat w1, Mat w2, Mat& flow, int dist, int dims)
{
float mass1 = 0.f, mass2 = 0.f, work = 0.f;
for (int i = 0; i < flow.rows; ++i)
{
mass1 += w1.at<float>(i, 0);
for (int j = 0; j < flow.cols; ++j)
{
if (i == 0)
mass2 += w2.at<float>(j, 0);
float dist_ = 0.f;
switch (dist)
{
case DIST_L1:
{
for (int k = 1; k <= dims; ++k)
{
dist_ += abs(w1.at<float>(i, k) - w2.at<float>(j, k));
}
break;
}
case DIST_L2:
{
for (int k = 1; k <= dims; ++k)
{
dist_ += sqr(w1.at<float>(i, k) - w2.at<float>(j, k));
}
dist_ = sqrt(dist_);
break;
}
case DIST_C:
{
for (int k = 1; k <= dims; ++k)
{
const float val = abs(w1.at<float>(i, k) - w2.at<float>(j, k));
if (val > dist_)
dist_ = val;
}
break;
}
}
const float weight = flow.at<float>(i, j);
work += dist_ * weight;
}
}
return work / max(mass1, mass2);
}
//==============================================================================
TEST(Imgproc_EMD, regression)
{
// input data
const float M = 10000;
Matx<float, 4, 1> w1 {50, 60, 50, 50};
Matx<float, 5, 1> w2 {30, 20, 70, 30, 60};
Matx<float, 4, 5> cost {16, 16, 13, 22, 17, 14, 14, 13, 19, 15,
19, 19, 20, 23, M, M, 0, M, 0, 0};
// expected results
const double emd0 = 2460. / 210;
Matx<float, 4, 5> flow0 {0, 0, 50, 0, 0, 0, 0, 20, 0, 40, 30, 20, 0, 0, 0, 0, 0, 0, 30, 20};
// basic call with cost
{
float emd = 0.f;
ASSERT_NO_THROW(emd = EMD(w1, w2, DIST_USER, cost));
EXPECT_NEAR(emd, emd0, 1e-6 * emd0);
}
// basic call with cost and flow output
{
Mat flow;
float emd = 0.f;
ASSERT_NO_THROW(emd = EMD(w1, w2, DIST_USER, cost, nullptr, flow));
EXPECT_NEAR(emd, emd0, 1e-6 * emd0);
EXPECT_MAT_NEAR(Mat(flow0), flow, 1e-6);
}
// no cost and DIST_USER - error
{
Mat flow;
EXPECT_THROW(EMD(w1, w2, DIST_USER, noArray(), nullptr, flow), cv::Exception);
EXPECT_THROW(EMD(w1, w2, DIST_USER), cv::Exception);
}
}
TEST(Imgproc_EMD, distance_types)
{
// 1D (sum = 210)
Matx<float, 4, 2> w1 {50, 1, 60, 2, 50, 3, 50, 4};
Matx<float, 5, 2> w2 {30, 1, 20, 2, 70, 3, 30, 4, 60, 5};
// 2D (sum = 210)
Matx<float, 4, 3> w3 {50, 0, 0, 60, 0, 1, 50, 1, 0, 50, 1, 1};
Matx<float, 5, 3> w4 {20, 0, 1, 70, 1, 0, 30, 1, 1, 60, 2, 2, 30, 3, 3};
// basic call with all distance types
{
const vector<DistanceTypes> good_types {DIST_L1, DIST_L2, DIST_C};
for (const auto& dt : good_types)
{
SCOPED_TRACE(cv::format("dt=%d", dt));
float emd = 0.f;
Mat flow;
// 1D
{
ASSERT_NO_THROW(emd = EMD(w1, w2, dt, noArray(), nullptr, flow));
const float emd0 = calcEMD(Mat(w1), Mat(w2), flow, dt, 1);
EXPECT_NEAR(emd0, emd, 1e-6);
}
// 2D
{
ASSERT_NO_THROW(emd = EMD(w3, w4, dt, noArray(), nullptr, flow));
const float emd0 = calcEMD(Mat(w3), Mat(w4), flow, dt, 2);
EXPECT_NEAR(emd0, emd, 1e-6);
}
}
}
}
typedef testing::TestWithParam<int> Imgproc_EMD_dist;
TEST_P(Imgproc_EMD_dist, random_flow_verify)
{
const int dist = GetParam();
for (size_t iter = 0; iter < 100; ++iter)
{
SCOPED_TRACE(cv::format("iter=%zu", iter));
RNG& rng = TS::ptr()->get_rng();
const int dims = rng.uniform(1, 10);
Mat w1(rng.uniform(1, 10), dims + 1, CV_32FC1);
Mat w2(rng.uniform(1, 10), dims + 1, CV_32FC1);
// weights > 0
{
Mat w1_weights = w1.col(0);
Mat w2_weights = w2.col(0);
cvtest::randUni(rng, w1_weights, 0, 100);
cvtest::randUni(rng, w2_weights, 0, 100);
}
// coord
{
Mat w1_coord = w1.colRange(1, dims + 1);
Mat w2_coord = w2.colRange(1, dims + 1);
cvtest::randUni(rng, w1_coord, -10, +10);
cvtest::randUni(rng, w2_coord, -10, +10);
}
float emd1 = 0.f, emd2 = 0.f;
const float eps = 1e-5f;
Mat flow;
{
ASSERT_NO_THROW(emd1 = EMD(w1, w2, dist, noArray(), nullptr, flow));
const float emd0 = calcEMD(w1, w2, flow, dist, dims);
EXPECT_NEAR(emd0, emd1, eps);
}
{
ASSERT_NO_THROW(emd2 = EMD(w2, w1, dist, noArray(), nullptr, flow));
const float emd0 = calcEMD(w2, w1, flow, dist, dims);
EXPECT_NEAR(emd0, emd2, eps);
}
EXPECT_NEAR(emd1, emd2, eps);
}
}
INSTANTIATE_TEST_CASE_P(, Imgproc_EMD_dist, testing::Values(DIST_L1, DIST_L2, DIST_C));
TEST(Imgproc_EMD, invalid)
{
Matx<float, 4, 2> w1 {50, 1, 60, 2, 50, 3, 50, 4};
Matx<float, 5, 2> w2 {30, 1, 20, 2, 70, 3, 30, 4, 60, 5};
// empty signature
{
Mat empty;
EXPECT_THROW(EMD(empty, w2, DIST_USER), cv::Exception);
EXPECT_THROW(EMD(w1, empty, DIST_USER), cv::Exception);
}
// zero total weight, negative weight
{
Matx<float, 3, 1> wz {0, 0, 0};
Matx<float, 3, 2> wz1 {0, 1, 0, 2, 0, 3};
Matx<float, 3, 1> wn {0, 3, -2};
Matx<float, 3, 2> wn1 {0, 1, 3, 2, -2, 3};
EXPECT_THROW(EMD(wz, w2, DIST_USER), cv::Exception);
EXPECT_THROW(EMD(wz1, w2, DIST_USER), cv::Exception);
EXPECT_THROW(EMD(wn, w2, DIST_USER), cv::Exception);
EXPECT_THROW(EMD(wn1, w2, DIST_USER), cv::Exception);
}
// user distance type, but no cost matrix provided or is wrong
{
Mat cost(3, 3, CV_32FC1, Scalar::all(0)), cost8u(4, 5, CV_8UC1, Scalar::all(0)), empty;
EXPECT_THROW(EMD(w1, w2, DIST_USER, noArray()), cv::Exception);
EXPECT_THROW(EMD(w1, w2, DIST_USER, empty), cv::Exception);
EXPECT_THROW(EMD(w1, w2, DIST_USER, cost8u), cv::Exception);
EXPECT_THROW(EMD(w1, w2, DIST_USER, cost), cv::Exception);
}
// lower_bound is set together with cost
{
Mat cost(4, 5, CV_32FC1, Scalar::all(0));
float bound = 0.f;
EXPECT_THROW(EMD(w1, w2, DIST_USER, cost, &bound), cv::Exception);
}
// zero dimensions with non-user distance type
const vector<DistanceTypes> good_types {DIST_L1, DIST_L2, DIST_C};
for (const auto& dt : good_types)
{
SCOPED_TRACE(cv::format("dt=%d", dt));
Matx<float, 4, 1> w01 {20, 30, 40, 50};
Matx<float, 5, 1> w02 {20, 30, 40, 50, 10};
EXPECT_THROW(EMD(w01, w02, dt), cv::Exception);
}
// wrong distance type
const vector<DistanceTypes> bad_types {DIST_L12, DIST_FAIR, DIST_WELSCH, DIST_HUBER};
for (const auto& dt : bad_types)
{
SCOPED_TRACE(cv::format("dt=%d", dt));
EXPECT_THROW(EMD(w1, w2, dt), cv::Exception);
}
}
}} // namespace opencv_test
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