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"
namespace opencv_test
{
TEST(GAPI, Mat_Create_NoLink)
{
cv::Mat m1;
cv::Mat m2 = m1;
m2.create(32, 32, CV_8U);
EXPECT_NE(m1.rows, m2.rows);
EXPECT_NE(m1.cols, m2.cols);
EXPECT_NE(m1.data, m2.data);
}
TEST(GAPI, Mat_Recreate)
{
cv::Mat m1 = cv::Mat::zeros(480, 640, CV_8U);
m1.at<uchar>(0, 0) = 128;
cv::Mat m2 = m1;
EXPECT_EQ(m1.rows, m2.rows);
EXPECT_EQ(m1.cols, m2.cols);
EXPECT_EQ(m1.data, m2.data);
EXPECT_EQ(m1.at<uchar>(0, 0), m2.at<uchar>(0, 0));
// Calling "create" with the same meta is NOOP - both m1 and m2 are the same
m1.create(480, 640, CV_8U);
EXPECT_EQ(m1.rows, m2.rows);
EXPECT_EQ(m1.cols, m2.cols);
EXPECT_EQ(m1.data, m2.data);
EXPECT_EQ(m1.at<uchar>(0, 0), m2.at<uchar>(0, 0));
// Calling "create" on m2 with different meta doesn't update original m1
// Now m1 and m2 are distinct
m2.create(720, 1280, CV_8U);
m2.at<uchar>(0, 0) = 64; // Initialize 0,0 element since m2 is a new buffer
EXPECT_NE(m1.rows, m2.rows);
EXPECT_NE(m1.cols, m2.cols);
EXPECT_NE(m1.data, m2.data);
EXPECT_NE(m1.at<uchar>(0, 0), m2.at<uchar>(0, 0));
// What if a Mat is created from handle?
uchar data[] = {
32, 0, 0,
0, 0, 0,
0, 0, 0
};
cv::Mat m3(3, 3, CV_8U, data);
cv::Mat m4 = m3;
EXPECT_EQ(m3.rows, m4.rows);
EXPECT_EQ(m3.cols, m4.cols);
EXPECT_EQ(m3.data, m4.data);
EXPECT_EQ(data, m3.data);
EXPECT_EQ(data, m4.data);
EXPECT_EQ(m3.at<uchar>(0, 0), m4.at<uchar>(0, 0));
// cv::Mat::create must be NOOP if we don't change the meta,
// even if the original mat is created from handle.
m4.create(3, 3, CV_8U);
EXPECT_EQ(m3.rows, m4.rows);
EXPECT_EQ(m3.cols, m4.cols);
EXPECT_EQ(m3.data, m4.data);
EXPECT_EQ(data, m3.data);
EXPECT_EQ(data, m4.data);
EXPECT_EQ(m3.at<uchar>(0, 0), m4.at<uchar>(0, 0));
}
TEST(GAPI, EmptyOutMat)
{
cv::Mat in_mat = cv::Mat(480, 640, CV_8U, cv::Scalar(64));
cv::GComputation cc([]()
{
cv::GMat in;
cv::GMat out = in + in;
return cv::GComputation(in, out);
});
cv::Mat out;
cc.apply(in_mat, out);
EXPECT_EQ(640, out.cols);
EXPECT_EQ(480, out.rows);
EXPECT_EQ(CV_8U, out.type());
EXPECT_EQ(0, cvtest::norm(out, (in_mat+in_mat), NORM_INF));
}
}