236 lines
10 KiB
C++
236 lines
10 KiB
C++
|
/*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.
|
||
|
//
|
||
|
//
|
||
|
// Intel License Agreement
|
||
|
// For Open Source Computer Vision Library
|
||
|
//
|
||
|
// Copyright (C) 2000, Intel Corporation, 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 materials provided with the distribution.
|
||
|
//
|
||
|
// * The name of Intel Corporation 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 implied warranties, including, but not limited to, the implied
|
||
|
// 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 <iostream>
|
||
|
#include <limits>
|
||
|
#include "test_precomp.hpp"
|
||
|
|
||
|
#define CHECK(pred, err) if (!(pred)) { \
|
||
|
ts->printf(cvtest::TS::CONSOLE, "Fail: \"%s\" at line: %d\n", #pred, __LINE__); \
|
||
|
ts->set_failed_test_info(err); \
|
||
|
return; }
|
||
|
|
||
|
using namespace cv;
|
||
|
using namespace std;
|
||
|
|
||
|
struct CV_GpuBitwiseTest: public cvtest::BaseTest
|
||
|
{
|
||
|
CV_GpuBitwiseTest() {}
|
||
|
|
||
|
void run(int)
|
||
|
{
|
||
|
int rows, cols;
|
||
|
|
||
|
bool double_ok = gpu::TargetArchs::builtWith(gpu::NATIVE_DOUBLE) &&
|
||
|
gpu::DeviceInfo().supports(gpu::NATIVE_DOUBLE);
|
||
|
int depth_end = double_ok ? CV_64F : CV_32F;
|
||
|
|
||
|
for (int depth = CV_8U; depth <= depth_end; ++depth)
|
||
|
for (int cn = 1; cn <= 4; ++cn)
|
||
|
for (int attempt = 0; attempt < 3; ++attempt)
|
||
|
{
|
||
|
rows = 1 + rand() % 100;
|
||
|
cols = 1 + rand() % 100;
|
||
|
test_bitwise_not(rows, cols, CV_MAKETYPE(depth, cn));
|
||
|
test_bitwise_or(rows, cols, CV_MAKETYPE(depth, cn));
|
||
|
test_bitwise_and(rows, cols, CV_MAKETYPE(depth, cn));
|
||
|
test_bitwise_xor(rows, cols, CV_MAKETYPE(depth, cn));
|
||
|
}
|
||
|
}
|
||
|
|
||
|
void test_bitwise_not(int rows, int cols, int type)
|
||
|
{
|
||
|
Mat src(rows, cols, type);
|
||
|
|
||
|
RNG rng;
|
||
|
for (int i = 0; i < src.rows; ++i)
|
||
|
{
|
||
|
Mat row(1, src.cols * src.elemSize(), CV_8U, src.ptr(i));
|
||
|
rng.fill(row, RNG::UNIFORM, Scalar(0), Scalar(255));
|
||
|
}
|
||
|
|
||
|
Mat dst_gold = ~src;
|
||
|
|
||
|
gpu::GpuMat mask(src.size(), CV_8U);
|
||
|
mask.setTo(Scalar(1));
|
||
|
|
||
|
gpu::GpuMat dst;
|
||
|
gpu::bitwise_not(gpu::GpuMat(src), dst);
|
||
|
|
||
|
CHECK(dst_gold.size() == dst.size(), cvtest::TS::FAIL_INVALID_OUTPUT);
|
||
|
CHECK(dst_gold.type() == dst.type(), cvtest::TS::FAIL_INVALID_OUTPUT);
|
||
|
|
||
|
Mat dsth(dst);
|
||
|
for (int i = 0; i < dst_gold.rows; ++i)
|
||
|
CHECK(memcmp(dst_gold.ptr(i), dsth.ptr(i), dst_gold.cols * dst_gold.elemSize()) == 0, cvtest::TS::FAIL_INVALID_OUTPUT);
|
||
|
|
||
|
dst.setTo(Scalar::all(0));
|
||
|
gpu::bitwise_not(gpu::GpuMat(src), dst, mask);
|
||
|
|
||
|
CHECK(dst_gold.size() == dst.size(), cvtest::TS::FAIL_INVALID_OUTPUT);
|
||
|
CHECK(dst_gold.type() == dst.type(), cvtest::TS::FAIL_INVALID_OUTPUT);
|
||
|
|
||
|
dsth = dst;
|
||
|
for (int i = 0; i < dst_gold.rows; ++i)
|
||
|
CHECK(memcmp(dst_gold.ptr(i), dsth.ptr(i), dst_gold.cols * dst_gold.elemSize()) == 0, cvtest::TS::FAIL_INVALID_OUTPUT)
|
||
|
}
|
||
|
|
||
|
void test_bitwise_or(int rows, int cols, int type)
|
||
|
{
|
||
|
Mat src1(rows, cols, type);
|
||
|
Mat src2(rows, cols, type);
|
||
|
|
||
|
RNG rng;
|
||
|
for (int i = 0; i < src1.rows; ++i)
|
||
|
{
|
||
|
Mat row1(1, src1.cols * src1.elemSize(), CV_8U, src1.ptr(i));
|
||
|
rng.fill(row1, RNG::UNIFORM, Scalar(0), Scalar(255));
|
||
|
Mat row2(1, src2.cols * src2.elemSize(), CV_8U, src2.ptr(i));
|
||
|
rng.fill(row2, RNG::UNIFORM, Scalar(0), Scalar(255));
|
||
|
}
|
||
|
|
||
|
Mat dst_gold = src1 | src2;
|
||
|
gpu::GpuMat dst = gpu::GpuMat(src1) | gpu::GpuMat(src2);
|
||
|
|
||
|
CHECK(dst_gold.size() == dst.size(), cvtest::TS::FAIL_INVALID_OUTPUT);
|
||
|
CHECK(dst_gold.type() == dst.type(), cvtest::TS::FAIL_INVALID_OUTPUT);
|
||
|
Mat dsth(dst);
|
||
|
for (int i = 0; i < dst_gold.rows; ++i)
|
||
|
CHECK(memcmp(dst_gold.ptr(i), dsth.ptr(i), dst_gold.cols * dst_gold.elemSize()) == 0, cvtest::TS::FAIL_INVALID_OUTPUT)
|
||
|
|
||
|
Mat mask(src1.size(), CV_8U);
|
||
|
randu(mask, Scalar(0), Scalar(255));
|
||
|
|
||
|
Mat dst_gold2(dst_gold.size(), dst_gold.type()); dst_gold2.setTo(Scalar::all(0));
|
||
|
gpu::GpuMat dst2(dst.size(), dst.type()); dst2.setTo(Scalar::all(0));
|
||
|
bitwise_or(src1, src2, dst_gold2, mask);
|
||
|
gpu::bitwise_or(gpu::GpuMat(src1), gpu::GpuMat(src2), dst2, gpu::GpuMat(mask));
|
||
|
|
||
|
CHECK(dst_gold2.size() == dst2.size(), cvtest::TS::FAIL_INVALID_OUTPUT);
|
||
|
CHECK(dst_gold2.type() == dst2.type(), cvtest::TS::FAIL_INVALID_OUTPUT);
|
||
|
dsth = dst2;
|
||
|
for (int i = 0; i < dst_gold.rows; ++i)
|
||
|
CHECK(memcmp(dst_gold2.ptr(i), dsth.ptr(i), dst_gold2.cols * dst_gold2.elemSize()) == 0, cvtest::TS::FAIL_INVALID_OUTPUT)
|
||
|
}
|
||
|
|
||
|
void test_bitwise_and(int rows, int cols, int type)
|
||
|
{
|
||
|
Mat src1(rows, cols, type);
|
||
|
Mat src2(rows, cols, type);
|
||
|
|
||
|
RNG rng;
|
||
|
for (int i = 0; i < src1.rows; ++i)
|
||
|
{
|
||
|
Mat row1(1, src1.cols * src1.elemSize(), CV_8U, src1.ptr(i));
|
||
|
rng.fill(row1, RNG::UNIFORM, Scalar(0), Scalar(255));
|
||
|
Mat row2(1, src2.cols * src2.elemSize(), CV_8U, src2.ptr(i));
|
||
|
rng.fill(row2, RNG::UNIFORM, Scalar(0), Scalar(255));
|
||
|
}
|
||
|
|
||
|
Mat dst_gold = src1 & src2;
|
||
|
|
||
|
gpu::GpuMat dst = gpu::GpuMat(src1) & gpu::GpuMat(src2);
|
||
|
|
||
|
CHECK(dst_gold.size() == dst.size(), cvtest::TS::FAIL_INVALID_OUTPUT);
|
||
|
CHECK(dst_gold.type() == dst.type(), cvtest::TS::FAIL_INVALID_OUTPUT);
|
||
|
Mat dsth(dst);
|
||
|
for (int i = 0; i < dst_gold.rows; ++i)
|
||
|
CHECK(memcmp(dst_gold.ptr(i), dsth.ptr(i), dst_gold.cols * dst_gold.elemSize()) == 0, cvtest::TS::FAIL_INVALID_OUTPUT)
|
||
|
|
||
|
|
||
|
Mat mask(src1.size(), CV_8U);
|
||
|
randu(mask, Scalar(0), Scalar(255));
|
||
|
|
||
|
Mat dst_gold2(dst_gold.size(), dst_gold.type()); dst_gold2.setTo(Scalar::all(0));
|
||
|
gpu::GpuMat dst2(dst.size(), dst.type()); dst2.setTo(Scalar::all(0));
|
||
|
bitwise_and(src1, src2, dst_gold2, mask);
|
||
|
gpu::bitwise_and(gpu::GpuMat(src1), gpu::GpuMat(src2), dst2, gpu::GpuMat(mask));
|
||
|
|
||
|
CHECK(dst_gold2.size() == dst2.size(), cvtest::TS::FAIL_INVALID_OUTPUT);
|
||
|
CHECK(dst_gold2.type() == dst2.type(), cvtest::TS::FAIL_INVALID_OUTPUT);
|
||
|
dsth = dst2;
|
||
|
for (int i = 0; i < dst_gold.rows; ++i)
|
||
|
CHECK(memcmp(dst_gold2.ptr(i), dsth.ptr(i), dst_gold2.cols * dst_gold2.elemSize()) == 0, cvtest::TS::FAIL_INVALID_OUTPUT)
|
||
|
}
|
||
|
|
||
|
void test_bitwise_xor(int rows, int cols, int type)
|
||
|
{
|
||
|
Mat src1(rows, cols, type);
|
||
|
Mat src2(rows, cols, type);
|
||
|
|
||
|
RNG rng;
|
||
|
for (int i = 0; i < src1.rows; ++i)
|
||
|
{
|
||
|
Mat row1(1, src1.cols * src1.elemSize(), CV_8U, src1.ptr(i));
|
||
|
rng.fill(row1, RNG::UNIFORM, Scalar(0), Scalar(255));
|
||
|
Mat row2(1, src2.cols * src2.elemSize(), CV_8U, src2.ptr(i));
|
||
|
rng.fill(row2, RNG::UNIFORM, Scalar(0), Scalar(255));
|
||
|
}
|
||
|
|
||
|
Mat dst_gold = src1 ^ src2;
|
||
|
|
||
|
gpu::GpuMat dst = gpu::GpuMat(src1) ^ gpu::GpuMat(src2);
|
||
|
|
||
|
CHECK(dst_gold.size() == dst.size(), cvtest::TS::FAIL_INVALID_OUTPUT);
|
||
|
CHECK(dst_gold.type() == dst.type(), cvtest::TS::FAIL_INVALID_OUTPUT);
|
||
|
Mat dsth(dst);
|
||
|
for (int i = 0; i < dst_gold.rows; ++i)
|
||
|
CHECK(memcmp(dst_gold.ptr(i), dsth.ptr(i), dst_gold.cols * dst_gold.elemSize()) == 0, cvtest::TS::FAIL_INVALID_OUTPUT)
|
||
|
|
||
|
|
||
|
Mat mask(src1.size(), CV_8U);
|
||
|
randu(mask, Scalar(0), Scalar(255));
|
||
|
|
||
|
Mat dst_gold2(dst_gold.size(), dst_gold.type()); dst_gold2.setTo(Scalar::all(0));
|
||
|
gpu::GpuMat dst2(dst.size(), dst.type()); dst2.setTo(Scalar::all(0));
|
||
|
bitwise_xor(src1, src2, dst_gold2, mask);
|
||
|
gpu::bitwise_xor(gpu::GpuMat(src1), gpu::GpuMat(src2), dst2, gpu::GpuMat(mask));
|
||
|
|
||
|
CHECK(dst_gold2.size() == dst2.size(), cvtest::TS::FAIL_INVALID_OUTPUT);
|
||
|
CHECK(dst_gold2.type() == dst2.type(), cvtest::TS::FAIL_INVALID_OUTPUT);
|
||
|
dsth = dst2;
|
||
|
for (int i = 0; i < dst_gold.rows; ++i)
|
||
|
CHECK(memcmp(dst_gold2.ptr(i), dsth.ptr(i), dst_gold2.cols * dst_gold2.elemSize()) == 0, cvtest::TS::FAIL_INVALID_OUTPUT)
|
||
|
}
|
||
|
};
|
||
|
|
||
|
TEST(BitwiseOperations, accuracy) { CV_GpuBitwiseTest test; test; }
|