Open Source Computer Vision Library https://opencv.org/
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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.
//
// Copyright (C) 2018 Intel Corporation
#include "../test_precomp.hpp"
#include <opencv2/gapi/own/mat.hpp>
#include <opencv2/gapi/util/compiler_hints.hpp> //suppress_unused_warning
namespace opencv_test
{
using Mat = cv::gapi::own::Mat;
using Dims = std::vector<int>;
TEST(OwnMat, DefaultConstruction)
{
Mat m;
ASSERT_EQ(m.data, nullptr);
ASSERT_EQ(m.cols, 0);
ASSERT_EQ(m.rows, 0);
ASSERT_EQ(m.cols, 0);
ASSERT_EQ(m.type(), 0);
ASSERT_EQ(m.depth(), 0);
ASSERT_TRUE(m.dims.empty());
}
TEST(OwnMat, Create)
{
auto size = cv::gapi::own::Size{32,16};
Mat m;
m.create(size, CV_8UC1);
ASSERT_NE(m.data, nullptr);
ASSERT_EQ((cv::gapi::own::Size{m.cols, m.rows}), size);
ASSERT_EQ(m.total(), static_cast<size_t>(size.height*size.width));
ASSERT_EQ(m.type(), CV_8UC1);
ASSERT_EQ(m.depth(), CV_8U);
ASSERT_EQ(m.channels(), 1);
ASSERT_EQ(m.elemSize(), sizeof(uint8_t));
ASSERT_EQ(m.step, sizeof(uint8_t) * m.cols);
ASSERT_TRUE(m.dims.empty());
}
TEST(OwnMat, CreateND)
{
Dims dims = {1,1,32,32};
Mat m;
m.create(dims, CV_32F);
ASSERT_NE(nullptr , m.data );
ASSERT_EQ((cv::gapi::own::Size{0,0}), (cv::gapi::own::Size{m.cols, m.rows}));
ASSERT_EQ(static_cast<size_t>(dims[0]*dims[1]*dims[2]*dims[3]), m.total());
ASSERT_EQ(CV_32F , m.type() );
ASSERT_EQ(CV_32F , m.depth() );
ASSERT_EQ(-1 , m.channels());
ASSERT_EQ(sizeof(float) , m.elemSize());
ASSERT_EQ(0u , m.step );
ASSERT_EQ(dims , m.dims );
}
TEST(OwnMat, CreateOverload)
{
auto size = cv::gapi::own::Size{32,16};
Mat m;
m.create(size.height,size.width, CV_8UC1);
ASSERT_NE(m.data, nullptr);
ASSERT_EQ((cv::Size{m.cols, m.rows}), size);
ASSERT_EQ(m.total(), static_cast<size_t>(size.height*size.width));
ASSERT_EQ(m.type(), CV_8UC1);
ASSERT_EQ(m.depth(), CV_8U);
ASSERT_EQ(m.channels(), 1);
ASSERT_EQ(m.elemSize(), sizeof(uint8_t));
ASSERT_EQ(m.step, sizeof(uint8_t) * m.cols);
ASSERT_TRUE(m.dims.empty());
}
TEST(OwnMat, Create3chan)
{
auto size = cv::Size{32,16};
Mat m;
m.create(size, CV_8UC3);
ASSERT_NE(m.data, nullptr);
ASSERT_EQ((cv::Size{m.cols, m.rows}), size);
ASSERT_EQ(m.type(), CV_8UC3);
ASSERT_EQ(m.depth(), CV_8U);
ASSERT_EQ(m.channels(), 3);
ASSERT_EQ(m.elemSize(), 3 * sizeof(uint8_t));
ASSERT_EQ(m.step, 3* sizeof(uint8_t) * m.cols);
ASSERT_TRUE(m.dims.empty());
}
struct NonEmptyMat {
cv::gapi::own::Size size{32,16};
Mat m;
NonEmptyMat() {
m.create(size, CV_8UC1);
}
};
struct OwnMatSharedSemantics : NonEmptyMat, ::testing::Test {};
namespace {
auto state_of = [](Mat const& mat) {
return std::make_tuple(
mat.data,
cv::Size{mat.cols, mat.rows},
mat.type(),
mat.depth(),
mat.channels(),
mat.dims
);
};
void ensure_mats_are_same(Mat const& copy, Mat const& m){
EXPECT_NE(copy.data, nullptr);
EXPECT_EQ(state_of(copy), state_of(m));
}
}
TEST_F(OwnMatSharedSemantics, CopyConstruction)
{
Mat copy(m);
ensure_mats_are_same(copy, m);
}
TEST_F(OwnMatSharedSemantics, CopyAssignment)
{
Mat copy;
copy = m;
ensure_mats_are_same(copy, m);
}
struct OwnMatMoveSemantics : NonEmptyMat, ::testing::Test {
Mat& moved_from = m;
decltype(state_of(moved_from)) initial_state = state_of(moved_from);
void ensure_state_moved_to(Mat const& moved_to)
{
EXPECT_EQ(state_of(moved_to), initial_state);
EXPECT_EQ(state_of(moved_from), state_of(Mat{}));
}
};
TEST_F(OwnMatMoveSemantics, MoveConstruction)
{
Mat moved_to(std::move(moved_from));
ensure_state_moved_to(moved_to);
}
TEST_F(OwnMatMoveSemantics, MoveAssignment)
{
Mat moved_to(std::move(moved_from));
ensure_state_moved_to(moved_to);
}
struct OwnMatNonOwningView : NonEmptyMat, ::testing::Test {
decltype(state_of(m)) initial_state = state_of(m);
void TearDown() override {
EXPECT_EQ(state_of(m), initial_state)<<"State of the source matrix changed?";
//ASAN should complain here if memory is freed here (e.g. by bug in non owning logic of own::Mat)
volatile uchar dummy = m.data[0];
cv::util::suppress_unused_warning(dummy);
}
};
TEST_F(OwnMatNonOwningView, Construction)
{
Mat non_owning_view(m.rows, m.cols, m.type(), static_cast<void*>(m.data));
ensure_mats_are_same(non_owning_view, m);
}
TEST_F(OwnMatNonOwningView, CopyConstruction)
{
Mat non_owning_view{m.rows, m.cols, m.type(), static_cast<void*>(m.data)};
Mat non_owning_view_copy = non_owning_view;
ensure_mats_are_same(non_owning_view_copy, m);
}
TEST_F(OwnMatNonOwningView, Assignment)
{
Mat non_owning_view{m.rows, m.cols, m.type(), static_cast<void*>(m.data)};
Mat non_owning_view_copy;
non_owning_view_copy = non_owning_view;
ensure_mats_are_same(non_owning_view_copy, m);
}
TEST(OwnMatConversion, WithStep)
{
constexpr int width = 8;
constexpr int height = 8;
constexpr int stepInPixels = 16;
std::array<int, height * stepInPixels> data;
for (size_t i = 0; i < data.size(); i++)
{
data[i] = static_cast<int>(i);
}
cv::Mat cvMat(cv::Size{width, height}, CV_32S, data.data(), stepInPixels * sizeof(int));
auto ownMat = to_own(cvMat);
auto cvMatFromOwn = cv::gapi::own::to_ocv(ownMat);
EXPECT_EQ(0, cv::countNonZero(cvMat != cvMatFromOwn))
<< cvMat << std::endl
<< (cvMat != cvMatFromOwn);
}
TEST(OwnMatConversion, WithND)
{
const Dims dims = {1,3,8,8};
std::vector<uint8_t> data(dims[0]*dims[1]*dims[2]*dims[3]);
for (size_t i = 0u; i < data.size(); i++)
{
data[i] = static_cast<uint8_t>(i);
}
cv::Mat cvMat(dims, CV_32S, data.data());
auto ownMat = to_own(cvMat);
auto cvMatFromOwn = cv::gapi::own::to_ocv(ownMat);
EXPECT_EQ(0, cv::countNonZero(cvMat != cvMatFromOwn))
<< cvMat << std::endl
<< (cvMat != cvMatFromOwn);
}
TEST(OwnMat, PtrWithStep)
{
constexpr int width = 8;
constexpr int height = 8;
constexpr int stepInPixels = 16;
std::array<int, height * stepInPixels> data;
for (size_t i = 0; i < data.size(); i++)
{
data[i] = static_cast<int>(i);
}
Mat mat(height, width, CV_32S, data.data(), stepInPixels * sizeof(int));
EXPECT_EQ(& data[0], reinterpret_cast<int*>(mat.ptr(0)));
EXPECT_EQ(& data[1], reinterpret_cast<int*>(mat.ptr(0, 1)));
EXPECT_EQ(& data[stepInPixels], reinterpret_cast<int*>(mat.ptr(1)));
EXPECT_EQ(& data[stepInPixels +1], reinterpret_cast<int*>(mat.ptr(1,1)));
auto const& cmat = mat;
EXPECT_EQ(& data[0], reinterpret_cast<const int*>(cmat.ptr(0)));
EXPECT_EQ(& data[1], reinterpret_cast<const int*>(cmat.ptr(0, 1)));
EXPECT_EQ(& data[stepInPixels], reinterpret_cast<const int*>(cmat.ptr(1)));
EXPECT_EQ(& data[stepInPixels +1], reinterpret_cast<const int*>(cmat.ptr(1,1)));
}
TEST(OwnMat, CopyToWithStep)
{
constexpr int width = 8;
constexpr int height = 8;
constexpr int stepInPixels = 16;
std::array<int, height * stepInPixels> data;
for (size_t i = 0; i < data.size(); i++)
{
data[i] = static_cast<int>(i);
}
Mat mat(height, width, CV_32S, data.data(), stepInPixels * sizeof(int));
Mat dst;
mat.copyTo(dst);
EXPECT_NE(mat.data, dst.data);
EXPECT_EQ(0, cv::countNonZero(to_ocv(mat) != to_ocv(dst)))
<< to_ocv(mat) << std::endl
<< (to_ocv(mat) != to_ocv(dst));
}
TEST(OwnMat, AssignNDtoRegular)
{
const auto sz = cv::gapi::own::Size{32,32};
const auto dims = Dims{1,3,224,224};
Mat a;
a.create(sz, CV_8U);
const auto *old_ptr = a.data;
ASSERT_NE(nullptr , a.data);
ASSERT_EQ(sz , (cv::gapi::own::Size{a.cols, a.rows}));
ASSERT_EQ(static_cast<size_t>(sz.width*sz.height), a.total());
ASSERT_EQ(CV_8U , a.type());
ASSERT_EQ(CV_8U , a.depth());
ASSERT_EQ(1 , a.channels());
ASSERT_EQ(sizeof(uint8_t), a.elemSize());
ASSERT_EQ(static_cast<size_t>(sz.width), a.step);
ASSERT_TRUE(a.dims.empty());
Mat b;
b.create(dims, CV_32F);
a = b;
ASSERT_NE(nullptr , a.data);
ASSERT_NE(old_ptr , a.data);
ASSERT_EQ((cv::gapi::own::Size{0,0}), (cv::gapi::own::Size{a.cols, a.rows}));
ASSERT_EQ(static_cast<size_t>(dims[0]*dims[1]*dims[2]*dims[3]), a.total());
ASSERT_EQ(CV_32F , a.type());
ASSERT_EQ(CV_32F , a.depth());
ASSERT_EQ(-1 , a.channels());
ASSERT_EQ(sizeof(float), a.elemSize());
ASSERT_EQ(0u , a.step);
ASSERT_EQ(dims , a.dims);
}
TEST(OwnMat, AssignRegularToND)
{
const auto sz = cv::gapi::own::Size{32,32};
const auto dims = Dims{1,3,224,224};
Mat a;
a.create(dims, CV_32F);
const auto *old_ptr = a.data;
ASSERT_NE(nullptr , a.data);
ASSERT_EQ((cv::gapi::own::Size{0,0}), (cv::gapi::own::Size{a.cols, a.rows}));
ASSERT_EQ(static_cast<size_t>(dims[0]*dims[1]*dims[2]*dims[3]), a.total());
ASSERT_EQ(CV_32F , a.type());
ASSERT_EQ(CV_32F , a.depth());
ASSERT_EQ(-1 , a.channels());
ASSERT_EQ(sizeof(float), a.elemSize());
ASSERT_EQ(0u , a.step);
ASSERT_EQ(dims , a.dims);
Mat b;
b.create(sz, CV_8U);
a = b;
ASSERT_NE(nullptr , a.data);
ASSERT_NE(old_ptr , a.data);
ASSERT_EQ(sz , (cv::gapi::own::Size{a.cols, a.rows}));
ASSERT_EQ(static_cast<size_t>(sz.width*sz.height), a.total());
ASSERT_EQ(CV_8U , a.type());
ASSERT_EQ(CV_8U , a.depth());
ASSERT_EQ(1 , a.channels());
ASSERT_EQ(sizeof(uint8_t), a.elemSize());
ASSERT_EQ(static_cast<size_t>(sz.width), a.step);
ASSERT_TRUE(a.dims.empty());
}
TEST(OwnMat, CopyNDtoRegular)
{
const auto sz = cv::gapi::own::Size{32,32};
const auto dims = Dims{1,3,224,224};
Mat a;
a.create(sz, CV_8U);
const auto *old_ptr = a.data;
ASSERT_NE(nullptr , a.data);
ASSERT_EQ(sz , (cv::gapi::own::Size{a.cols, a.rows}));
ASSERT_EQ(static_cast<size_t>(sz.width*sz.height), a.total());
ASSERT_EQ(CV_8U , a.type());
ASSERT_EQ(CV_8U , a.depth());
ASSERT_EQ(1 , a.channels());
ASSERT_EQ(sizeof(uint8_t), a.elemSize());
ASSERT_EQ(static_cast<size_t>(sz.width), a.step);
ASSERT_TRUE(a.dims.empty());
Mat b;
b.create(dims, CV_32F);
b.copyTo(a);
ASSERT_NE(nullptr , a.data);
ASSERT_NE(old_ptr , a.data);
ASSERT_NE(b.data , a.data);
ASSERT_EQ((cv::gapi::own::Size{0,0}), (cv::gapi::own::Size{a.cols, a.rows}));
ASSERT_EQ(static_cast<size_t>(dims[0]*dims[1]*dims[2]*dims[3]), a.total());
ASSERT_EQ(CV_32F , a.type());
ASSERT_EQ(CV_32F , a.depth());
ASSERT_EQ(-1 , a.channels());
ASSERT_EQ(sizeof(float), a.elemSize());
ASSERT_EQ(0u , a.step);
ASSERT_EQ(dims , a.dims);
}
TEST(OwnMat, CopyRegularToND)
{
const auto sz = cv::gapi::own::Size{32,32};
const auto dims = Dims{1,3,224,224};
Mat a;
a.create(dims, CV_32F);
const auto *old_ptr = a.data;
ASSERT_NE(nullptr , a.data);
ASSERT_EQ((cv::gapi::own::Size{0,0}), (cv::gapi::own::Size{a.cols, a.rows}));
ASSERT_EQ(static_cast<size_t>(dims[0]*dims[1]*dims[2]*dims[3]), a.total());
ASSERT_EQ(CV_32F , a.type());
ASSERT_EQ(CV_32F , a.depth());
ASSERT_EQ(-1 , a.channels());
ASSERT_EQ(sizeof(float), a.elemSize());
ASSERT_EQ(0u , a.step);
ASSERT_EQ(dims , a.dims);
Mat b;
b.create(sz, CV_8U);
b.copyTo(a);
ASSERT_NE(nullptr , a.data);
ASSERT_NE(old_ptr , a.data);
ASSERT_NE(b.data , a.data);
ASSERT_EQ(sz , (cv::gapi::own::Size{a.cols, a.rows}));
ASSERT_EQ(static_cast<size_t>(sz.width*sz.height), a.total());
ASSERT_EQ(CV_8U , a.type());
ASSERT_EQ(CV_8U , a.depth());
ASSERT_EQ(1 , a.channels());
ASSERT_EQ(sizeof(uint8_t), a.elemSize());
ASSERT_EQ(static_cast<size_t>(sz.width), a.step);
ASSERT_TRUE(a.dims.empty());
}
TEST(OwnMat, ScalarAssign32SC1)
{
constexpr int width = 8;
constexpr int height = 8;
constexpr int stepInPixels = 16;
std::array<int, height * stepInPixels> data;
for (size_t i = 0; i < data.size(); i++)
{
data[i] = static_cast<int>(i);
}
Mat mat(height, width, CV_32S, data.data(), stepInPixels * sizeof(data[0]));
mat = cv::gapi::own::Scalar{-1};
std::array<int, height * stepInPixels> expected;
for (size_t row = 0; row < height; row++)
{
for (size_t col = 0; col < stepInPixels; col++)
{
auto index = row*stepInPixels + col;
expected[index] = col < width ? -1 : static_cast<int>(index);
}
}
auto cmp_result_mat = (cv::Mat{height, stepInPixels, CV_32S, data.data()} != cv::Mat{height, stepInPixels, CV_32S, expected.data()});
EXPECT_EQ(0, cv::countNonZero(cmp_result_mat))
<< cmp_result_mat << std::endl;
}
TEST(OwnMat, ScalarAssign8UC1)
{
constexpr int width = 8;
constexpr int height = 8;
constexpr int stepInPixels = 16;
std::array<uchar, height * stepInPixels> data;
for (size_t i = 0; i < data.size(); i++)
{
data[i] = static_cast<uchar>(i);
}
Mat mat(height, width, CV_8U, data.data(), stepInPixels * sizeof(data[0]));
mat = cv::gapi::own::Scalar{-1};
std::array<uchar, height * stepInPixels> expected;
for (size_t row = 0; row < height; row++)
{
for (size_t col = 0; col < stepInPixels; col++)
{
auto index = row*stepInPixels + col;
expected[index] = col < width ? cv::saturate_cast<uchar>(-1) : static_cast<uchar>(index);
}
}
auto cmp_result_mat = (cv::Mat{height, stepInPixels, CV_8U, data.data()} != cv::Mat{height, stepInPixels, CV_8U, expected.data()});
EXPECT_EQ(0, cv::countNonZero(cmp_result_mat))
<< cmp_result_mat << std::endl;
}
TEST(OwnMat, ScalarAssignND)
{
std::vector<int> dims = {1,1000};
Mat m;
m.create(dims, CV_32F);
m = cv::gapi::own::Scalar{-1};
const float *ptr = reinterpret_cast<float*>(m.data);
for (auto i = 0u; i < m.total(); i++) {
EXPECT_EQ(-1.f, ptr[i]);
}
}
TEST(OwnMat, ScalarAssign8UC3)
{
constexpr auto cv_type = CV_8SC3;
constexpr int channels = 3;
constexpr int width = 8;
constexpr int height = 8;
constexpr int stepInPixels = 16;
std::array<schar, height * stepInPixels * channels> data;
for (size_t i = 0; i < data.size(); i+= channels)
{
data[i + 0] = static_cast<schar>(10 * i + 0);
data[i + 1] = static_cast<schar>(10 * i + 1);
data[i + 2] = static_cast<schar>(10 * i + 2);
}
Mat mat(height, width, cv_type, data.data(), channels * stepInPixels * sizeof(data[0]));
mat = cv::gapi::own::Scalar{-10, -11, -12};
std::array<schar, data.size()> expected;
for (size_t row = 0; row < height; row++)
{
for (size_t col = 0; col < stepInPixels; col++)
{
int index = static_cast<int>(channels * (row*stepInPixels + col));
expected[index + 0] = static_cast<schar>(col < width ? -10 : 10 * index + 0);
expected[index + 1] = static_cast<schar>(col < width ? -11 : 10 * index + 1);
expected[index + 2] = static_cast<schar>(col < width ? -12 : 10 * index + 2);
}
}
auto cmp_result_mat = (cv::Mat{height, stepInPixels, cv_type, data.data()} != cv::Mat{height, stepInPixels, cv_type, expected.data()});
EXPECT_EQ(0, cv::countNonZero(cmp_result_mat))
<< cmp_result_mat << std::endl
<< "data : " << std::endl
<< cv::Mat{height, stepInPixels, cv_type, data.data()} << std::endl
<< "expected : " << std::endl
<< cv::Mat{height, stepInPixels, cv_type, expected.data()} << std::endl;
}
TEST(OwnMat, ROIView)
{
constexpr int width = 8;
constexpr int height = 8;
constexpr int stepInPixels = 16;
std::array<uchar, height * stepInPixels> data;
for (size_t i = 0; i < data.size(); i++)
{
data[i] = static_cast<uchar>(i);
}
// std::cout<<cv::Mat{height, stepInPixels, CV_8U, data.data()}<<std::endl;
std::array<uchar, 4 * 4> expected;
for (size_t row = 0; row < 4; row++)
{
for (size_t col = 0; col < 4; col++)
{
expected[row*4 +col] = static_cast<uchar>(stepInPixels * (2 + row) + 2 + col);
}
}
Mat mat(height, width, CV_8U, data.data(), stepInPixels * sizeof(data[0]));
Mat roi_view (mat, cv::gapi::own::Rect{2,2,4,4});
// std::cout<<cv::Mat{4, 4, CV_8U, expected.data()}<<std::endl;
//
auto expected_cv_mat = cv::Mat{4, 4, CV_8U, expected.data()};
auto cmp_result_mat = (to_ocv(roi_view) != expected_cv_mat);
EXPECT_EQ(0, cv::countNonZero(cmp_result_mat))
<< cmp_result_mat << std::endl
<< to_ocv(roi_view) << std::endl
<< expected_cv_mat << std::endl;
}
} // namespace opencv_test