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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other GpuMaterials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or bpied warranties, including, but not limited to, the bpied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "test_precomp.hpp"
using namespace std;
using namespace cv;
////////////////////////////////////////////////////////////////////////////////
// Merge
struct CV_MergeTest : public cvtest::BaseTest
{
void can_merge(size_t rows, size_t cols);
void can_merge_submatrixes(size_t rows, size_t cols);
void run(int);
};
void CV_MergeTest::can_merge(size_t rows, size_t cols)
{
bool double_ok = gpu::TargetArchs::builtWith(gpu::NATIVE_DOUBLE) &&
gpu::DeviceInfo().supports(gpu::NATIVE_DOUBLE);
size_t depth_end = double_ok ? CV_64F : CV_32F;
for (size_t num_channels = 1; num_channels <= 4; ++num_channels)
for (size_t depth = CV_8U; depth <= depth_end; ++depth)
{
vector<Mat> src;
for (size_t i = 0; i < num_channels; ++i)
src.push_back(Mat(rows, cols, depth, Scalar::all(static_cast<double>(i))));
Mat dst(rows, cols, CV_MAKETYPE(depth, num_channels));
cv::merge(src, dst);
vector<gpu::GpuMat> dev_src;
for (size_t i = 0; i < num_channels; ++i)
dev_src.push_back(gpu::GpuMat(src[i]));
gpu::GpuMat dev_dst(rows, cols, CV_MAKETYPE(depth, num_channels));
cv::gpu::merge(dev_src, dev_dst);
Mat host_dst = dev_dst;
double err = norm(dst, host_dst, NORM_INF);
if (err > 1e-3)
{
//ts->printf(cvtest::TS::CONSOLE, "\nNorm: %f\n", err);
//ts->printf(cvtest::TS::CONSOLE, "Depth: %d\n", depth);
//ts->printf(cvtest::TS::CONSOLE, "Rows: %d\n", rows);
//ts->printf(cvtest::TS::CONSOLE, "Cols: %d\n", cols);
//ts->printf(cvtest::TS::CONSOLE, "NumChannels: %d\n", num_channels);
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
return;
}
}
}
void CV_MergeTest::can_merge_submatrixes(size_t rows, size_t cols)
{
bool double_ok = gpu::TargetArchs::builtWith(gpu::NATIVE_DOUBLE) &&
gpu::DeviceInfo().supports(gpu::NATIVE_DOUBLE);
size_t depth_end = double_ok ? CV_64F : CV_32F;
for (size_t num_channels = 1; num_channels <= 4; ++num_channels)
for (size_t depth = CV_8U; depth <= depth_end; ++depth)
{
vector<Mat> src;
for (size_t i = 0; i < num_channels; ++i)
{
Mat m(rows * 2, cols * 2, depth, Scalar::all(static_cast<double>(i)));
src.push_back(m(Range(rows / 2, rows / 2 + rows), Range(cols / 2, cols / 2 + cols)));
}
Mat dst(rows, cols, CV_MAKETYPE(depth, num_channels));
cv::merge(src, dst);
vector<gpu::GpuMat> dev_src;
for (size_t i = 0; i < num_channels; ++i)
dev_src.push_back(gpu::GpuMat(src[i]));
gpu::GpuMat dev_dst(rows, cols, CV_MAKETYPE(depth, num_channels));
cv::gpu::merge(dev_src, dev_dst);
Mat host_dst = dev_dst;
double err = norm(dst, host_dst, NORM_INF);
if (err > 1e-3)
{
//ts->printf(cvtest::TS::CONSOLE, "\nNorm: %f\n", err);
//ts->printf(cvtest::TS::CONSOLE, "Depth: %d\n", depth);
//ts->printf(cvtest::TS::CONSOLE, "Rows: %d\n", rows);
//ts->printf(cvtest::TS::CONSOLE, "Cols: %d\n", cols);
//ts->printf(cvtest::TS::CONSOLE, "NumChannels: %d\n", num_channels);
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
return;
}
}
}
void CV_MergeTest::run(int)
{
can_merge(1, 1);
can_merge(1, 7);
can_merge(53, 7);
can_merge_submatrixes(1, 1);
can_merge_submatrixes(1, 7);
can_merge_submatrixes(53, 7);
}
////////////////////////////////////////////////////////////////////////////////
// Split
struct CV_SplitTest : public cvtest::BaseTest
{
void can_split(size_t rows, size_t cols);
void can_split_submatrix(size_t rows, size_t cols);
void run(int);
};
void CV_SplitTest::can_split(size_t rows, size_t cols)
{
bool double_ok = gpu::TargetArchs::builtWith(gpu::NATIVE_DOUBLE) &&
gpu::DeviceInfo().supports(gpu::NATIVE_DOUBLE);
size_t depth_end = double_ok ? CV_64F : CV_32F;
for (size_t num_channels = 1; num_channels <= 4; ++num_channels)
for (size_t depth = CV_8U; depth <= depth_end; ++depth)
{
Mat src(rows, cols, CV_MAKETYPE(depth, num_channels), Scalar(1.0, 2.0, 3.0, 4.0));
vector<Mat> dst;
cv::split(src, dst);
gpu::GpuMat dev_src(src);
vector<gpu::GpuMat> dev_dst;
cv::gpu::split(dev_src, dev_dst);
if (dev_dst.size() != dst.size())
{
ts->printf(cvtest::TS::CONSOLE, "Bad output sizes");
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
}
for (size_t i = 0; i < num_channels; ++i)
{
Mat host_dst = dev_dst[i];
double err = norm(dst[i], host_dst, NORM_INF);
if (err > 1e-3)
{
//ts->printf(cvtest::TS::CONSOLE, "\nNorm: %f\n", err);
//ts->printf(cvtest::TS::CONSOLE, "Depth: %d\n", depth);
//ts->printf(cvtest::TS::CONSOLE, "Rows: %d\n", rows);
//ts->printf(cvtest::TS::CONSOLE, "Cols: %d\n", cols);
//ts->printf(cvtest::TS::CONSOLE, "NumChannels: %d\n", num_channels);
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
return;
}
}
}
}
void CV_SplitTest::can_split_submatrix(size_t rows, size_t cols)
{
bool double_ok = gpu::TargetArchs::builtWith(gpu::NATIVE_DOUBLE) &&
gpu::DeviceInfo().supports(gpu::NATIVE_DOUBLE);
size_t depth_end = double_ok ? CV_64F : CV_32F;
for (size_t num_channels = 1; num_channels <= 4; ++num_channels)
for (size_t depth = CV_8U; depth <= depth_end; ++depth)
{
Mat src_data(rows * 2, cols * 2, CV_MAKETYPE(depth, num_channels), Scalar(1.0, 2.0, 3.0, 4.0));
Mat src(src_data(Range(rows / 2, rows / 2 + rows), Range(cols / 2, cols / 2 + cols)));
vector<Mat> dst;
cv::split(src, dst);
gpu::GpuMat dev_src(src);
vector<gpu::GpuMat> dev_dst;
cv::gpu::split(dev_src, dev_dst);
if (dev_dst.size() != dst.size())
{
ts->printf(cvtest::TS::CONSOLE, "Bad output sizes");
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
}
for (size_t i = 0; i < num_channels; ++i)
{
Mat host_dst = dev_dst[i];
double err = norm(dst[i], host_dst, NORM_INF);
if (err > 1e-3)
{
//ts->printf(cvtest::TS::CONSOLE, "\nNorm: %f\n", err);
//ts->printf(cvtest::TS::CONSOLE, "Depth: %d\n", depth);
//ts->printf(cvtest::TS::CONSOLE, "Rows: %d\n", rows);
//ts->printf(cvtest::TS::CONSOLE, "Cols: %d\n", cols);
//ts->printf(cvtest::TS::CONSOLE, "NumChannels: %d\n", num_channels);
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
return;
}
}
}
}
void CV_SplitTest::run(int)
{
can_split(1, 1);
can_split(1, 7);
can_split(7, 53);
can_split_submatrix(1, 1);
can_split_submatrix(1, 7);
can_split_submatrix(7, 53);
}
////////////////////////////////////////////////////////////////////////////////
// Split and merge
struct CV_SplitMergeTest : public cvtest::BaseTest
{
void can_split_merge(size_t rows, size_t cols);
void run(int);
};
void CV_SplitMergeTest::can_split_merge(size_t rows, size_t cols) {
bool double_ok = gpu::TargetArchs::builtWith(gpu::NATIVE_DOUBLE) &&
gpu::DeviceInfo().supports(gpu::NATIVE_DOUBLE);
size_t depth_end = double_ok ? CV_64F : CV_32F;
for (size_t num_channels = 1; num_channels <= 4; ++num_channels)
for (size_t depth = CV_8U; depth <= depth_end; ++depth)
{
Mat orig(rows, cols, CV_MAKETYPE(depth, num_channels), Scalar(1.0, 2.0, 3.0, 4.0));
gpu::GpuMat dev_orig(orig);
vector<gpu::GpuMat> dev_vec;
cv::gpu::split(dev_orig, dev_vec);
gpu::GpuMat dev_final(rows, cols, CV_MAKETYPE(depth, num_channels));
cv::gpu::merge(dev_vec, dev_final);
double err = cv::norm((Mat)dev_orig, (Mat)dev_final, NORM_INF);
if (err > 1e-3)
{
//ts->printf(cvtest::TS::CONSOLE, "\nNorm: %f\n", err);
//ts->printf(cvtest::TS::CONSOLE, "Depth: %d\n", depth);
//ts->printf(cvtest::TS::CONSOLE, "Rows: %d\n", rows);
//ts->printf(cvtest::TS::CONSOLE, "Cols: %d\n", cols);
//ts->printf(cvtest::TS::CONSOLE, "NumChannels: %d\n", num_channels);
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
return;
}
}
}
void CV_SplitMergeTest::run(int)
{
can_split_merge(1, 1);
can_split_merge(1, 7);
can_split_merge(7, 53);
}
TEST(merge, accuracy) { CV_MergeTest test; test.safe_run(); }
TEST(split, accuracy) { CV_SplitTest test; test.safe_run(); }
TEST(split, merge_consistency) { CV_SplitMergeTest test; test.safe_run(); }