Chiebot-Mirror
/
opencv
mirror of https://github.com/opencv/opencv.git
8
0
Fork 0
Code Issues Projects Releases Wiki Activity
Open Source Computer Vision Library https://opencv.org/
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
24079 Commits
7 Branches
126 Tags
3.0 GiB
 
 
 
 
 
 
Tag: Branch: Tree: 055f33ec46
Branches Tags
${ item.name }
Create tag ${ searchTerm }
Create branch ${ searchTerm }
from '055f33ec46'
${ noResults }
opencv/modules/imgproc/test/test_imgwarp_strict.cpp

1331 lines
42 KiB
Raw Blame History

/*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 "test_precomp.hpp"
namespace opencv_test { namespace {
void __wrap_printf_func(const char* fmt, ...)
{
va_list args;
va_start(args, fmt);
char buffer[256];
vsprintf (buffer, fmt, args);
cvtest::TS::ptr()->printf(cvtest::TS::SUMMARY, buffer);
va_end(args);
}
#define PRINT_TO_LOG __wrap_printf_func
#define SHOW_IMAGE
#undef SHOW_IMAGE
////////////////////////////////////////////////////////////////////////////////////////////////////////
// ImageWarpBaseTest
////////////////////////////////////////////////////////////////////////////////////////////////////////
class CV_ImageWarpBaseTest :
public cvtest::BaseTest
{
public:
enum { cell_size = 10 };
CV_ImageWarpBaseTest();
virtual ~CV_ImageWarpBaseTest();
virtual void run(int);
protected:
virtual void generate_test_data();
virtual void run_func() = 0;
virtual void run_reference_func() = 0;
virtual float get_success_error_level(int _interpolation, int _depth) const;
virtual void validate_results() const;
virtual void prepare_test_data_for_reference_func();
Size randSize(RNG& rng) const;
String interpolation_to_string(int inter_type) const;
int interpolation;
Mat src;
Mat dst;
Mat reference_dst;
};
CV_ImageWarpBaseTest::CV_ImageWarpBaseTest() :
BaseTest(), interpolation(-1),
src(), dst(), reference_dst()
{
test_case_count = 40;
ts->set_failed_test_info(cvtest::TS::OK);
}
CV_ImageWarpBaseTest::~CV_ImageWarpBaseTest()
{
}
String CV_ImageWarpBaseTest::interpolation_to_string(int inter) const
{
bool inverse = (inter & WARP_INVERSE_MAP) != 0;
inter &= ~WARP_INVERSE_MAP;
String str;
if (inter == INTER_NEAREST)
str = "INTER_NEAREST";
else if (inter == INTER_LINEAR)
str = "INTER_LINEAR";
else if (inter == INTER_LINEAR_EXACT)
str = "INTER_LINEAR_EXACT";
else if (inter == INTER_AREA)
str = "INTER_AREA";
else if (inter == INTER_CUBIC)
str = "INTER_CUBIC";
else if (inter == INTER_LANCZOS4)
str = "INTER_LANCZOS4";
else if (inter == INTER_LANCZOS4 + 1)
str = "INTER_AREA_FAST";
if (inverse)
str += " | WARP_INVERSE_MAP";
return str.empty() ? "Unsupported/Unknown interpolation type" : str;
}
Size CV_ImageWarpBaseTest::randSize(RNG& rng) const
{
Size size;
size.width = static_cast<int>(std::exp(rng.uniform(1.0f, 7.0f)));
size.height = static_cast<int>(std::exp(rng.uniform(1.0f, 7.0f)));
return size;
}
void CV_ImageWarpBaseTest::generate_test_data()
{
RNG& rng = ts->get_rng();
// generating the src matrix structure
Size ssize = randSize(rng), dsize;
int depth = rng.uniform(0, CV_64F);
while (depth == CV_8S || depth == CV_32S)
depth = rng.uniform(0, CV_64F);
int cn = rng.uniform(1, 4);
while (cn == 2)
cn = rng.uniform(1, 4);
src.create(ssize, CV_MAKE_TYPE(depth, cn));
// generating the src matrix
int x, y;
if (cvtest::randInt(rng) % 2)
{
for (y = 0; y < ssize.height; y += cell_size)
for (x = 0; x < ssize.width; x += cell_size)
rectangle(src, Point(x, y), Point(x + std::min<int>(cell_size, ssize.width - x), y +
std::min<int>(cell_size, ssize.height - y)), Scalar::all((x + y) % 2 ? 255: 0), CV_FILLED);
}
else
{
src = Scalar::all(255);
for (y = cell_size; y < src.rows; y += cell_size)
line(src, Point2i(0, y), Point2i(src.cols, y), Scalar::all(0), 1);
for (x = cell_size; x < src.cols; x += cell_size)
line(src, Point2i(x, 0), Point2i(x, src.rows), Scalar::all(0), 1);
}
// generating an interpolation type
interpolation = rng.uniform(0, CV_INTER_LANCZOS4 + 1);
// generating the dst matrix structure
double scale_x, scale_y;
if (interpolation == INTER_AREA)
{
bool area_fast = rng.uniform(0., 1.) > 0.5;
if (area_fast)
{
scale_x = rng.uniform(2, 5);
scale_y = rng.uniform(2, 5);
}
else
{
scale_x = rng.uniform(1.0, 3.0);
scale_y = rng.uniform(1.0, 3.0);
}
}
else
{
scale_x = rng.uniform(0.4, 4.0);
scale_y = rng.uniform(0.4, 4.0);
}
CV_Assert(scale_x > 0.0f && scale_y > 0.0f);
dsize.width = saturate_cast<int>((ssize.width + scale_x - 1) / scale_x);
dsize.height = saturate_cast<int>((ssize.height + scale_y - 1) / scale_y);
dst = Mat::zeros(dsize, src.type());
reference_dst = Mat::zeros(dst.size(), CV_MAKE_TYPE(CV_32F, dst.channels()));
scale_x = src.cols / static_cast<double>(dst.cols);
scale_y = src.rows / static_cast<double>(dst.rows);
if (interpolation == INTER_AREA && (scale_x < 1.0 || scale_y < 1.0))
interpolation = INTER_LINEAR;
}
void CV_ImageWarpBaseTest::run(int)
{
for (int i = 0; i < test_case_count; ++i)
{
generate_test_data();
run_func();
run_reference_func();
if (ts->get_err_code() < 0)
break;
validate_results();
if (ts->get_err_code() < 0)
break;
ts->update_context(this, i, true);
}
ts->set_gtest_status();
}
float CV_ImageWarpBaseTest::get_success_error_level(int _interpolation, int) const
{
if (_interpolation == INTER_CUBIC)
return 1.0f;
else if (_interpolation == INTER_LANCZOS4)
return 1.0f;
else if (_interpolation == INTER_NEAREST)
return 1.0f;
else if (_interpolation == INTER_AREA)
return 2.0f;
else
return 1.0f;
}
void CV_ImageWarpBaseTest::validate_results() const
{
Mat _dst;
dst.convertTo(_dst, reference_dst.depth());
Size dsize = dst.size(), ssize = src.size();
int cn = _dst.channels();
dsize.width *= cn;
float t = get_success_error_level(interpolation & INTER_MAX, dst.depth());
for (int dy = 0; dy < dsize.height; ++dy)
{
const float* rD = reference_dst.ptr<float>(dy);
const float* D = _dst.ptr<float>(dy);
for (int dx = 0; dx < dsize.width; ++dx)
if (fabs(rD[dx] - D[dx]) > t &&
// fabs(rD[dx] - D[dx]) < 250.0f &&
rD[dx] <= 255.0f && D[dx] <= 255.0f && rD[dx] >= 0.0f && D[dx] >= 0.0f)
{
PRINT_TO_LOG("\nNorm of the difference: %lf\n", cvtest::norm(reference_dst, _dst, NORM_INF));
PRINT_TO_LOG("Error in (dx, dy): (%d, %d)\n", dx / cn + 1, dy + 1);
PRINT_TO_LOG("Tuple (rD, D): (%f, %f)\n", rD[dx], D[dx]);
PRINT_TO_LOG("Dsize: (%d, %d)\n", dsize.width / cn, dsize.height);
PRINT_TO_LOG("Ssize: (%d, %d)\n", src.cols, src.rows);
double scale_x = static_cast<double>(ssize.width) / dsize.width;
double scale_y = static_cast<double>(ssize.height) / dsize.height;
bool area_fast = interpolation == INTER_AREA &&
fabs(scale_x - cvRound(scale_x)) < FLT_EPSILON &&
fabs(scale_y - cvRound(scale_y)) < FLT_EPSILON;
if (area_fast)
{
scale_y = cvRound(scale_y);
scale_x = cvRound(scale_x);
}
PRINT_TO_LOG("Interpolation: %s\n", interpolation_to_string(area_fast ? INTER_LANCZOS4 + 1 : interpolation).c_str());
PRINT_TO_LOG("Scale (x, y): (%lf, %lf)\n", scale_x, scale_y);
PRINT_TO_LOG("Elemsize: %d\n", src.elemSize1());
PRINT_TO_LOG("Channels: %d\n", cn);
#ifdef SHOW_IMAGE
const std::string w1("OpenCV impl (run func)"), w2("Reference func"), w3("Src image"), w4("Diff");
namedWindow(w1, CV_WINDOW_KEEPRATIO);
namedWindow(w2, CV_WINDOW_KEEPRATIO);
namedWindow(w3, CV_WINDOW_KEEPRATIO);
namedWindow(w4, CV_WINDOW_KEEPRATIO);
Mat diff;
absdiff(reference_dst, _dst, diff);
imshow(w1, dst);
imshow(w2, reference_dst);
imshow(w3, src);
imshow(w4, diff);
waitKey();
#endif
const int radius = 3;
int rmin = MAX(dy - radius, 0), rmax = MIN(dy + radius, dsize.height);
int cmin = MAX(dx / cn - radius, 0), cmax = MIN(dx / cn + radius, dsize.width);
std::cout << "opencv result:\n" << dst(Range(rmin, rmax), Range(cmin, cmax)) << std::endl;
std::cout << "reference result:\n" << reference_dst(Range(rmin, rmax), Range(cmin, cmax)) << std::endl;
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
return;
}
}
}
void CV_ImageWarpBaseTest::prepare_test_data_for_reference_func()
{
if (src.depth() != CV_32F)
{
Mat tmp;
src.convertTo(tmp, CV_32F);
src = tmp;
}
}
////////////////////////////////////////////////////////////////////////////////////////////////////////
// Resize
////////////////////////////////////////////////////////////////////////////////////////////////////////
class CV_Resize_Test :
public CV_ImageWarpBaseTest
{
public:
CV_Resize_Test();
virtual ~CV_Resize_Test();
protected:
virtual void generate_test_data();
virtual void run_func();
virtual void run_reference_func();
private:
double scale_x;
double scale_y;
bool area_fast;
void resize_generic();
void resize_area();
double getWeight(double a, double b, int x);
typedef std::vector<std::pair<int, double> > dim;
void generate_buffer(double scale, dim& _dim);
void resize_1d(const Mat& _src, Mat& _dst, int dy, const dim& _dim);
};
CV_Resize_Test::CV_Resize_Test() :
CV_ImageWarpBaseTest(), scale_x(),
scale_y(), area_fast(false)
{
}
CV_Resize_Test::~CV_Resize_Test()
{
}
namespace
{
void interpolateLinear(float x, float* coeffs)
{
coeffs[0] = 1.f - x;
coeffs[1] = x;
}
void interpolateCubic(float x, float* coeffs)
{
const float A = -0.75f;
coeffs[0] = ((A*(x + 1) - 5*A)*(x + 1) + 8*A)*(x + 1) - 4*A;
coeffs[1] = ((A + 2)*x - (A + 3))*x*x + 1;
coeffs[2] = ((A + 2)*(1 - x) - (A + 3))*(1 - x)*(1 - x) + 1;
coeffs[3] = 1.f - coeffs[0] - coeffs[1] - coeffs[2];
}
void interpolateLanczos4(float x, float* coeffs)
{
static const double s45 = 0.70710678118654752440084436210485;
static const double cs[][2]=
{{1, 0}, {-s45, -s45}, {0, 1}, {s45, -s45}, {-1, 0}, {s45, s45}, {0, -1}, {-s45, s45}};
if( x < FLT_EPSILON )
{
for( int i = 0; i < 8; i++ )
coeffs[i] = 0;
coeffs[3] = 1;
return;
}
float sum = 0;
double y0=-(x+3)*CV_PI*0.25, s0 = sin(y0), c0=cos(y0);
for(int i = 0; i < 8; i++ )
{
double y = -(x+3-i)*CV_PI*0.25;
coeffs[i] = (float)((cs[i][0]*s0 + cs[i][1]*c0)/(y*y));
sum += coeffs[i];
}
sum = 1.f/sum;
for(int i = 0; i < 8; i++ )
coeffs[i] *= sum;
}
typedef void (*interpolate_method)(float x, float* coeffs);
interpolate_method inter_array[] = { &interpolateLinear, &interpolateCubic, &interpolateLanczos4 };
}
void CV_Resize_Test::generate_test_data()
{
RNG& rng = ts->get_rng();
// generating the src matrix structure
Size ssize = randSize(rng), dsize;
int depth = rng.uniform(0, CV_64F);
while (depth == CV_8S || depth == CV_32S)
depth = rng.uniform(0, CV_64F);
int cn = rng.uniform(1, 4);
while (cn == 2)
cn = rng.uniform(1, 4);
src.create(ssize, CV_MAKE_TYPE(depth, cn));
// generating the src matrix
int x, y;
if (cvtest::randInt(rng) % 2)
{
for (y = 0; y < ssize.height; y += cell_size)
for (x = 0; x < ssize.width; x += cell_size)
rectangle(src, Point(x, y), Point(x + std::min<int>(cell_size, ssize.width - x), y +
std::min<int>(cell_size, ssize.height - y)), Scalar::all((x + y) % 2 ? 255: 0), CV_FILLED);
}
else
{
src = Scalar::all(255);
for (y = cell_size; y < src.rows; y += cell_size)
line(src, Point2i(0, y), Point2i(src.cols, y), Scalar::all(0), 1);
for (x = cell_size; x < src.cols; x += cell_size)
line(src, Point2i(x, 0), Point2i(x, src.rows), Scalar::all(0), 1);
}
// generating an interpolation type
interpolation = rng.uniform(0, cv::INTER_MAX - 1);
// generating the dst matrix structure
if (interpolation == INTER_AREA)
{
area_fast = rng.uniform(0., 1.) > 0.5;
if (area_fast)
{
scale_x = rng.uniform(2, 5);
scale_y = rng.uniform(2, 5);
}
else
{
scale_x = rng.uniform(1.0, 3.0);
scale_y = rng.uniform(1.0, 3.0);
}
}
else
{
scale_x = rng.uniform(0.4, 4.0);
scale_y = rng.uniform(0.4, 4.0);
}
CV_Assert(scale_x > 0.0f && scale_y > 0.0f);
dsize.width = saturate_cast<int>((ssize.width + scale_x - 1) / scale_x);
dsize.height = saturate_cast<int>((ssize.height + scale_y - 1) / scale_y);
dst = Mat::zeros(dsize, src.type());
reference_dst = Mat::zeros(dst.size(), CV_MAKE_TYPE(CV_32F, dst.channels()));
scale_x = src.cols / static_cast<double>(dst.cols);
scale_y = src.rows / static_cast<double>(dst.rows);
if (interpolation == INTER_AREA && (scale_x < 1.0 || scale_y < 1.0))
interpolation = INTER_LINEAR_EXACT;
if (interpolation == INTER_LINEAR_EXACT && (depth == CV_32F || depth == CV_64F))
interpolation = INTER_LINEAR;
area_fast = interpolation == INTER_AREA &&
fabs(scale_x - cvRound(scale_x)) < FLT_EPSILON &&
fabs(scale_y - cvRound(scale_y)) < FLT_EPSILON;
if (area_fast)
{
scale_x = cvRound(scale_x);
scale_y = cvRound(scale_y);
}
}
void CV_Resize_Test::run_func()
{
cv::resize(src, dst, dst.size(), 0, 0, interpolation);
}
void CV_Resize_Test::run_reference_func()
{
CV_ImageWarpBaseTest::prepare_test_data_for_reference_func();
if (interpolation == INTER_AREA)
resize_area();
else
resize_generic();
}
double CV_Resize_Test::getWeight(double a, double b, int x)
{
double w = std::min(static_cast<double>(x + 1), b) - std::max(static_cast<double>(x), a);
CV_Assert(w >= 0);
return w;
}
void CV_Resize_Test::resize_area()
{
Size ssize = src.size(), dsize = reference_dst.size();
CV_Assert(ssize.area() > 0 && dsize.area() > 0);
int cn = src.channels();
CV_Assert(scale_x >= 1.0 && scale_y >= 1.0);
double fsy0 = 0, fsy1 = scale_y;
for (int dy = 0; dy < dsize.height; ++dy)
{
float* yD = reference_dst.ptr<float>(dy);
int isy0 = cvFloor(fsy0), isy1 = std::min(cvFloor(fsy1), ssize.height - 1);
CV_Assert(isy1 <= ssize.height && isy0 < ssize.height);
double fsx0 = 0, fsx1 = scale_x;
for (int dx = 0; dx < dsize.width; ++dx)
{
float* xyD = yD + cn * dx;
int isx0 = cvFloor(fsx0), isx1 = std::min(ssize.width - 1, cvFloor(fsx1));
CV_Assert(isx1 <= ssize.width);
CV_Assert(isx0 < ssize.width);
// for each pixel of dst
for (int r = 0; r < cn; ++r)
{
xyD[r] = 0.0f;
double area = 0.0;
for (int sy = isy0; sy <= isy1; ++sy)
{
const float* yS = src.ptr<float>(sy);
for (int sx = isx0; sx <= isx1; ++sx)
{
double wy = getWeight(fsy0, fsy1, sy);
double wx = getWeight(fsx0, fsx1, sx);
double w = wx * wy;
xyD[r] += static_cast<float>(yS[sx * cn + r] * w);
area += w;
}
}
CV_Assert(area != 0);
// norming pixel
xyD[r] = static_cast<float>(xyD[r] / area);
}
fsx1 = std::min((fsx0 = fsx1) + scale_x, static_cast<double>(ssize.width));
}
fsy1 = std::min((fsy0 = fsy1) + scale_y, static_cast<double>(ssize.height));
}
}
// for interpolation type : INTER_LINEAR, INTER_LINEAR_EXACT, INTER_CUBIC, INTER_LANCZOS4
void CV_Resize_Test::resize_1d(const Mat& _src, Mat& _dst, int dy, const dim& _dim)
{
Size dsize = _dst.size();
int cn = _dst.channels();
float* yD = _dst.ptr<float>(dy);
if (interpolation == INTER_NEAREST)
{
const float* yS = _src.ptr<float>(dy);
for (int dx = 0; dx < dsize.width; ++dx)
{
int isx = _dim[dx].first;
const float* xyS = yS + isx * cn;
float* xyD = yD + dx * cn;
for (int r = 0; r < cn; ++r)
xyD[r] = xyS[r];
}
}
else if (interpolation == INTER_LINEAR || interpolation == INTER_LINEAR_EXACT || interpolation == INTER_CUBIC || interpolation == INTER_LANCZOS4)
{
interpolate_method inter_func = inter_array[interpolation - (interpolation == INTER_LANCZOS4 ? 2 : interpolation == INTER_LINEAR_EXACT ? 5 : 1)];
size_t elemsize = _src.elemSize();
int ofs = 0, ksize = 2;
if (interpolation == INTER_CUBIC)
ofs = 1, ksize = 4;
else if (interpolation == INTER_LANCZOS4)
ofs = 3, ksize = 8;
Mat _extended_src_row(1, _src.cols + ksize * 2, _src.type());
const uchar* srow = _src.ptr(dy);
memcpy(_extended_src_row.ptr() + elemsize * ksize, srow, _src.step);
for (int k = 0; k < ksize; ++k)
{
memcpy(_extended_src_row.ptr() + k * elemsize, srow, elemsize);
memcpy(_extended_src_row.ptr() + (ksize + k) * elemsize + _src.step, srow + _src.step - elemsize, elemsize);
}
for (int dx = 0; dx < dsize.width; ++dx)
{
int isx = _dim[dx].first;
double fsx = _dim[dx].second;
float *xyD = yD + dx * cn;
const float* xyS = _extended_src_row.ptr<float>(0) + (isx + ksize - ofs) * cn;
float w[8];
inter_func(static_cast<float>(fsx), w);
for (int r = 0; r < cn; ++r)
{
xyD[r] = 0;
for (int k = 0; k < ksize; ++k)
xyD[r] += w[k] * xyS[k * cn + r];
}
}
}
else
CV_Assert(0);
}
void CV_Resize_Test::generate_buffer(double scale, dim& _dim)
{
size_t length = _dim.size();
for (size_t dx = 0; dx < length; ++dx)
{
double fsx = scale * (dx + 0.5) - 0.5;
int isx = cvFloor(fsx);
_dim[dx] = std::make_pair(isx, fsx - isx);
}
}
void CV_Resize_Test::resize_generic()
{
Size dsize = reference_dst.size(), ssize = src.size();
CV_Assert(dsize.area() > 0 && ssize.area() > 0);
dim dims[] = { dim(dsize.width), dim(dsize.height) };
if (interpolation == INTER_NEAREST)
{
for (int dx = 0; dx < dsize.width; ++dx)
dims[0][dx].first = std::min(cvFloor(dx * scale_x), ssize.width - 1);
for (int dy = 0; dy < dsize.height; ++dy)
dims[1][dy].first = std::min(cvFloor(dy * scale_y), ssize.height - 1);
}
else
{
generate_buffer(scale_x, dims[0]);
generate_buffer(scale_y, dims[1]);
}
Mat tmp(ssize.height, dsize.width, reference_dst.type());
for (int dy = 0; dy < tmp.rows; ++dy)
resize_1d(src, tmp, dy, dims[0]);
cv::Mat tmp_t(tmp.cols, tmp.rows, tmp.type());
cvtest::transpose(tmp, tmp_t);
cv::Mat reference_dst_t(reference_dst.cols, reference_dst.rows, reference_dst.type());
cvtest::transpose(reference_dst, reference_dst_t);
for (int dy = 0; dy < tmp_t.rows; ++dy)
resize_1d(tmp_t, reference_dst_t, dy, dims[1]);
cvtest::transpose(reference_dst_t, reference_dst);
}
////////////////////////////////////////////////////////////////////////////////////////////////////////
// remap
////////////////////////////////////////////////////////////////////////////////////////////////////////
class CV_Remap_Test :
public CV_ImageWarpBaseTest
{
public:
CV_Remap_Test();
virtual ~CV_Remap_Test();
private:
typedef void (CV_Remap_Test::*remap_func)(const Mat&, Mat&);
protected:
virtual void generate_test_data();
virtual void prepare_test_data_for_reference_func();
virtual void run_func();
virtual void run_reference_func();
Mat mapx, mapy;
int borderType;
Scalar borderValue;
remap_func funcs[2];
private:
void remap_nearest(const Mat&, Mat&);
void remap_generic(const Mat&, Mat&);
void convert_maps();
const char* borderType_to_string() const;
virtual void validate_results() const;
};
CV_Remap_Test::CV_Remap_Test() :
CV_ImageWarpBaseTest(), borderType(-1)
{
funcs[0] = &CV_Remap_Test::remap_nearest;
funcs[1] = &CV_Remap_Test::remap_generic;
}
CV_Remap_Test::~CV_Remap_Test()
{
}
void CV_Remap_Test::generate_test_data()
{
CV_ImageWarpBaseTest::generate_test_data();
RNG& rng = ts->get_rng();
borderType = rng.uniform(1, BORDER_WRAP);
borderValue = Scalar::all(rng.uniform(0, 255));
// generating the mapx, mapy matrices
static const int mapx_types[] = { CV_16SC2, CV_32FC1, CV_32FC2 };
mapx.create(dst.size(), mapx_types[rng.uniform(0, sizeof(mapx_types) / sizeof(int))]);
mapy.release();
const int n = std::min(std::min(src.cols, src.rows) / 10 + 1, 2);
float _n = 0; //static_cast<float>(-n);
switch (mapx.type())
{
case CV_16SC2:
{
MatIterator_<Vec2s> begin_x = mapx.begin<Vec2s>(), end_x = mapx.end<Vec2s>();
for ( ; begin_x != end_x; ++begin_x)
{
(*begin_x)[0] = static_cast<short>(rng.uniform(static_cast<int>(_n), std::max(src.cols + n - 1, 0)));
(*begin_x)[1] = static_cast<short>(rng.uniform(static_cast<int>(_n), std::max(src.rows + n - 1, 0)));
}
if (interpolation != INTER_NEAREST)
{
static const int mapy_types[] = { CV_16UC1, CV_16SC1 };
mapy.create(dst.size(), mapy_types[rng.uniform(0, sizeof(mapy_types) / sizeof(int))]);
switch (mapy.type())
{
case CV_16UC1:
{
MatIterator_<ushort> begin_y = mapy.begin<ushort>(), end_y = mapy.end<ushort>();
for ( ; begin_y != end_y; ++begin_y)
*begin_y = static_cast<ushort>(rng.uniform(0, 1024));
}
break;
case CV_16SC1:
{
MatIterator_<short> begin_y = mapy.begin<short>(), end_y = mapy.end<short>();
for ( ; begin_y != end_y; ++begin_y)
*begin_y = static_cast<short>(rng.uniform(0, 1024));
}
break;
}
}
}
break;
case CV_32FC1:
{
mapy.create(dst.size(), CV_32FC1);
float fscols = static_cast<float>(std::max(src.cols - 1 + n, 0)),
fsrows = static_cast<float>(std::max(src.rows - 1 + n, 0));
MatIterator_<float> begin_x = mapx.begin<float>(), end_x = mapx.end<float>();
MatIterator_<float> begin_y = mapy.begin<float>();
for ( ; begin_x != end_x; ++begin_x, ++begin_y)
{
*begin_x = rng.uniform(_n, fscols);
*begin_y = rng.uniform(_n, fsrows);
}
}
break;
case CV_32FC2:
{
float fscols = static_cast<float>(std::max(src.cols - 1 + n, 0)),
fsrows = static_cast<float>(std::max(src.rows - 1 + n, 0));
int width = mapx.cols << 1;
for (int y = 0; y < mapx.rows; ++y)
{
float * ptr = mapx.ptr<float>(y);
for (int x = 0; x < width; x += 2)
{
ptr[x] = rng.uniform(_n, fscols);
ptr[x + 1] = rng.uniform(_n, fsrows);
}
}
}
break;
default:
CV_Assert(0);
break;
}
}
void CV_Remap_Test::run_func()
{
remap(src, dst, mapx, mapy, interpolation, borderType, borderValue);
}
void CV_Remap_Test::convert_maps()
{
if (mapx.type() != CV_16SC2)
convertMaps(mapx.clone(), mapy.clone(), mapx, mapy, CV_16SC2, interpolation == INTER_NEAREST);
else if (interpolation != INTER_NEAREST)
if (mapy.type() != CV_16UC1)
mapy.clone().convertTo(mapy, CV_16UC1);
if (interpolation == INTER_NEAREST)
mapy = Mat();
CV_Assert(((interpolation == INTER_NEAREST && mapy.empty()) || mapy.type() == CV_16UC1 ||
mapy.type() == CV_16SC1) && mapx.type() == CV_16SC2);
}
const char* CV_Remap_Test::borderType_to_string() const
{
if (borderType == BORDER_CONSTANT)
return "BORDER_CONSTANT";
if (borderType == BORDER_REPLICATE)
return "BORDER_REPLICATE";
if (borderType == BORDER_REFLECT)
return "BORDER_REFLECT";
if (borderType == BORDER_WRAP)
return "BORDER_WRAP";
if (borderType == BORDER_REFLECT_101)
return "BORDER_REFLECT_101";
return "Unsupported/Unknown border type";
}
void CV_Remap_Test::prepare_test_data_for_reference_func()
{
CV_ImageWarpBaseTest::prepare_test_data_for_reference_func();
convert_maps();
}
void CV_Remap_Test::run_reference_func()
{
prepare_test_data_for_reference_func();
if (interpolation == INTER_AREA)
interpolation = INTER_LINEAR;
int index = interpolation == INTER_NEAREST ? 0 : 1;
(this->*funcs[index])(src, reference_dst);
}
void CV_Remap_Test::remap_nearest(const Mat& _src, Mat& _dst)
{
CV_Assert(_src.depth() == CV_32F && _dst.type() == _src.type());
CV_Assert(mapx.type() == CV_16SC2 && mapy.empty());
Size ssize = _src.size(), dsize = _dst.size();
CV_Assert(ssize.area() > 0 && dsize.area() > 0);
int cn = _src.channels();
for (int dy = 0; dy < dsize.height; ++dy)
{
const short* yM = mapx.ptr<short>(dy);
float* yD = _dst.ptr<float>(dy);
for (int dx = 0; dx < dsize.width; ++dx)
{
float* xyD = yD + cn * dx;
int sx = yM[dx * 2], sy = yM[dx * 2 + 1];
if (sx >= 0 && sx < ssize.width && sy >= 0 && sy < ssize.height)
{
const float *xyS = _src.ptr<float>(sy) + sx * cn;
for (int r = 0; r < cn; ++r)
xyD[r] = xyS[r];
}
else if (borderType != BORDER_TRANSPARENT)
{
if (borderType == BORDER_CONSTANT)
for (int r = 0; r < cn; ++r)
xyD[r] = saturate_cast<float>(borderValue[r]);
else
{
sx = borderInterpolate(sx, ssize.width, borderType);
sy = borderInterpolate(sy, ssize.height, borderType);
CV_Assert(sx >= 0 && sy >= 0 && sx < ssize.width && sy < ssize.height);
const float *xyS = _src.ptr<float>(sy) + sx * cn;
for (int r = 0; r < cn; ++r)
xyD[r] = xyS[r];
}
}
}
}
}
void CV_Remap_Test::remap_generic(const Mat& _src, Mat& _dst)
{
CV_Assert(mapx.type() == CV_16SC2 && mapy.type() == CV_16UC1);
int ksize = 2;
if (interpolation == INTER_CUBIC)
ksize = 4;
else if (interpolation == INTER_LANCZOS4)
ksize = 8;
else if (interpolation != INTER_LINEAR)
assert(0);
int ofs = (ksize / 2) - 1;
CV_Assert(_src.depth() == CV_32F && _dst.type() == _src.type());
Size ssize = _src.size(), dsize = _dst.size();
int cn = _src.channels(), width1 = std::max(ssize.width - ksize + 1, 0),
height1 = std::max(ssize.height - ksize + 1, 0);
float ix[8], w[16];
interpolate_method inter_func = inter_array[interpolation - (interpolation == INTER_LANCZOS4 ? 2 : 1)];
for (int dy = 0; dy < dsize.height; ++dy)
{
const short* yMx = mapx.ptr<short>(dy);
const ushort* yMy = mapy.ptr<ushort>(dy);
float* yD = _dst.ptr<float>(dy);
for (int dx = 0; dx < dsize.width; ++dx)
{
float* xyD = yD + dx * cn;
float sx = yMx[dx * 2], sy = yMx[dx * 2 + 1];
int isx = cvFloor(sx), isy = cvFloor(sy);
inter_func((yMy[dx] & (INTER_TAB_SIZE - 1)) / static_cast<float>(INTER_TAB_SIZE), w);
inter_func(((yMy[dx] >> INTER_BITS) & (INTER_TAB_SIZE - 1)) / static_cast<float>(INTER_TAB_SIZE), w + ksize);
isx -= ofs;
isy -= ofs;
if (isx >= 0 && isx < width1 && isy >= 0 && isy < height1)
{
for (int r = 0; r < cn; ++r)
{
for (int y = 0; y < ksize; ++y)
{
const float* xyS = _src.ptr<float>(isy + y) + isx * cn;
ix[y] = 0;
for (int i = 0; i < ksize; ++i)
ix[y] += w[i] * xyS[i * cn + r];
}
xyD[r] = 0;
for (int i = 0; i < ksize; ++i)
xyD[r] += w[ksize + i] * ix[i];
}
}
else if (borderType != BORDER_TRANSPARENT)
{
int ar_x[8], ar_y[8];
for (int k = 0; k < ksize; k++)
{
ar_x[k] = borderInterpolate(isx + k, ssize.width, borderType) * cn;
ar_y[k] = borderInterpolate(isy + k, ssize.height, borderType);
}
for (int r = 0; r < cn; r++)
{
xyD[r] = 0;
for (int i = 0; i < ksize; ++i)
{
ix[i] = 0;
if (ar_y[i] >= 0)
{
const float* yS = _src.ptr<float>(ar_y[i]);
for (int j = 0; j < ksize; ++j)
ix[i] += saturate_cast<float>((ar_x[j] >= 0 ? yS[ar_x[j] + r] : borderValue[r]) * w[j]);
}
else
for (int j = 0; j < ksize; ++j)
ix[i] += saturate_cast<float>(borderValue[r] * w[j]);
}
for (int i = 0; i < ksize; ++i)
xyD[r] += saturate_cast<float>(w[ksize + i] * ix[i]);
}
}
}
}
}
void CV_Remap_Test::validate_results() const
{
CV_ImageWarpBaseTest::validate_results();
if (cvtest::TS::ptr()->get_err_code() == cvtest::TS::FAIL_BAD_ACCURACY)
{
PRINT_TO_LOG("BorderType: %s\n", borderType_to_string());
PRINT_TO_LOG("BorderValue: (%f, %f, %f, %f)\n",
borderValue[0], borderValue[1], borderValue[2], borderValue[3]);
}
}
////////////////////////////////////////////////////////////////////////////////////////////////////////
// warpAffine
////////////////////////////////////////////////////////////////////////////////////////////////////////
class CV_WarpAffine_Test :
public CV_Remap_Test
{
public:
CV_WarpAffine_Test();
virtual ~CV_WarpAffine_Test();
protected:
virtual void generate_test_data();
virtual float get_success_error_level(int _interpolation, int _depth) const;
virtual void run_func();
virtual void run_reference_func();
Mat M;
private:
void warpAffine(const Mat&, Mat&);
};
CV_WarpAffine_Test::CV_WarpAffine_Test() :
CV_Remap_Test()
{
}
CV_WarpAffine_Test::~CV_WarpAffine_Test()
{
}
void CV_WarpAffine_Test::generate_test_data()
{
CV_Remap_Test::generate_test_data();
RNG& rng = ts->get_rng();
// generating the M 2x3 matrix
static const int depths[] = { CV_32FC1, CV_64FC1 };
// generating 2d matrix
M = getRotationMatrix2D(Point2f(src.cols / 2.f, src.rows / 2.f),
rng.uniform(-180.f, 180.f), rng.uniform(0.4f, 2.0f));
int depth = depths[rng.uniform(0, sizeof(depths) / sizeof(depths[0]))];
if (M.depth() != depth)
{
Mat tmp;
M.convertTo(tmp, depth);
M = tmp;
}
// warp_matrix is inverse
if (rng.uniform(0., 1.) > 0)
interpolation |= CV_WARP_INVERSE_MAP;
}
void CV_WarpAffine_Test::run_func()
{
cv::warpAffine(src, dst, M, dst.size(), interpolation, borderType, borderValue);
}
float CV_WarpAffine_Test::get_success_error_level(int _interpolation, int _depth) const
{
return _depth == CV_8U ? 0 : CV_ImageWarpBaseTest::get_success_error_level(_interpolation, _depth);
}
void CV_WarpAffine_Test::run_reference_func()
{
Mat tmp = Mat::zeros(dst.size(), dst.type());
warpAffine(src, tmp);
tmp.convertTo(reference_dst, reference_dst.depth());
}
void CV_WarpAffine_Test::warpAffine(const Mat& _src, Mat& _dst)
{
Size dsize = _dst.size();
CV_Assert(_src.size().area() > 0);
CV_Assert(dsize.area() > 0);
CV_Assert(_src.type() == _dst.type());
Mat tM;
M.convertTo(tM, CV_64F);
int inter = interpolation & INTER_MAX;
if (inter == INTER_AREA)
inter = INTER_LINEAR;
mapx.create(dsize, CV_16SC2);
if (inter != INTER_NEAREST)
mapy.create(dsize, CV_16SC1);
else
mapy = Mat();
if (!(interpolation & CV_WARP_INVERSE_MAP))
invertAffineTransform(tM.clone(), tM);
const int AB_BITS = MAX(10, (int)INTER_BITS);
const int AB_SCALE = 1 << AB_BITS;
int round_delta = (inter == INTER_NEAREST) ? AB_SCALE / 2 : (AB_SCALE / INTER_TAB_SIZE / 2);
const softdouble* data_tM = tM.ptr<softdouble>(0);
for (int dy = 0; dy < dsize.height; ++dy)
{
short* yM = mapx.ptr<short>(dy);
for (int dx = 0; dx < dsize.width; ++dx, yM += 2)
{
int v1 = saturate_cast<int>(saturate_cast<int>(data_tM[0] * dx * AB_SCALE) +
saturate_cast<int>((data_tM[1] * dy + data_tM[2]) * AB_SCALE) + round_delta),
v2 = saturate_cast<int>(saturate_cast<int>(data_tM[3] * dx * AB_SCALE) +
saturate_cast<int>((data_tM[4] * dy + data_tM[5]) * AB_SCALE) + round_delta);
v1 >>= AB_BITS - INTER_BITS;
v2 >>= AB_BITS - INTER_BITS;
yM[0] = saturate_cast<short>(v1 >> INTER_BITS);
yM[1] = saturate_cast<short>(v2 >> INTER_BITS);
if (inter != INTER_NEAREST)
mapy.ptr<short>(dy)[dx] = ((v2 & (INTER_TAB_SIZE - 1)) * INTER_TAB_SIZE + (v1 & (INTER_TAB_SIZE - 1)));
}
}
CV_Assert(mapx.type() == CV_16SC2 && ((inter == INTER_NEAREST && mapy.empty()) || mapy.type() == CV_16SC1));
cv::remap(_src, _dst, mapx, mapy, inter, borderType, borderValue);
}
////////////////////////////////////////////////////////////////////////////////////////////////////////
// warpPerspective
////////////////////////////////////////////////////////////////////////////////////////////////////////
class CV_WarpPerspective_Test :
public CV_WarpAffine_Test
{
public:
CV_WarpPerspective_Test();
virtual ~CV_WarpPerspective_Test();
protected:
virtual void generate_test_data();
virtual float get_success_error_level(int _interpolation, int _depth) const;
virtual void run_func();
virtual void run_reference_func();
private:
void warpPerspective(const Mat&, Mat&);
};
CV_WarpPerspective_Test::CV_WarpPerspective_Test() :
CV_WarpAffine_Test()
{
}
CV_WarpPerspective_Test::~CV_WarpPerspective_Test()
{
}
void CV_WarpPerspective_Test::generate_test_data()
{
CV_Remap_Test::generate_test_data();
// generating the M 3x3 matrix
RNG& rng = ts->get_rng();
float cols = static_cast<float>(src.cols), rows = static_cast<float>(src.rows);
Point2f sp[] = { Point2f(0.0f, 0.0f), Point2f(cols, 0.0f), Point2f(0.0f, rows), Point2f(cols, rows) };
Point2f dp[] = { Point2f(rng.uniform(0.0f, cols), rng.uniform(0.0f, rows)),
Point2f(rng.uniform(0.0f, cols), rng.uniform(0.0f, rows)),
Point2f(rng.uniform(0.0f, cols), rng.uniform(0.0f, rows)),
Point2f(rng.uniform(0.0f, cols), rng.uniform(0.0f, rows)) };
M = getPerspectiveTransform(sp, dp);
static const int depths[] = { CV_32F, CV_64F };
int depth = depths[rng.uniform(0, 2)];
M.clone().convertTo(M, depth);
}
void CV_WarpPerspective_Test::run_func()
{
cv::warpPerspective(src, dst, M, dst.size(), interpolation, borderType, borderValue);
}
float CV_WarpPerspective_Test::get_success_error_level(int _interpolation, int _depth) const
{
return CV_ImageWarpBaseTest::get_success_error_level(_interpolation, _depth);
}
void CV_WarpPerspective_Test::run_reference_func()
{
Mat tmp = Mat::zeros(dst.size(), dst.type());
warpPerspective(src, tmp);
tmp.convertTo(reference_dst, reference_dst.depth());
}
void CV_WarpPerspective_Test::warpPerspective(const Mat& _src, Mat& _dst)
{
Size ssize = _src.size(), dsize = _dst.size();
CV_Assert(ssize.area() > 0);
CV_Assert(dsize.area() > 0);
CV_Assert(_src.type() == _dst.type());
if (M.depth() != CV_64F)
{
Mat tmp;
M.convertTo(tmp, CV_64F);
M = tmp;
}
if (!(interpolation & CV_WARP_INVERSE_MAP))
{
Mat tmp;
invert(M, tmp);
M = tmp;
}
int inter = interpolation & INTER_MAX;
if (inter == INTER_AREA)
inter = INTER_LINEAR;
mapx.create(dsize, CV_16SC2);
if (inter != INTER_NEAREST)
mapy.create(dsize, CV_16SC1);
else
mapy = Mat();
double* tM = M.ptr<double>(0);
for (int dy = 0; dy < dsize.height; ++dy)
{
short* yMx = mapx.ptr<short>(dy);
for (int dx = 0; dx < dsize.width; ++dx, yMx += 2)
{
double den = tM[6] * dx + tM[7] * dy + tM[8];
den = den ? 1.0 / den : 0.0;
if (inter == INTER_NEAREST)
{
yMx[0] = saturate_cast<short>((tM[0] * dx + tM[1] * dy + tM[2]) * den);
yMx[1] = saturate_cast<short>((tM[3] * dx + tM[4] * dy + tM[5]) * den);
continue;
}
den *= INTER_TAB_SIZE;
int v0 = saturate_cast<int>((tM[0] * dx + tM[1] * dy + tM[2]) * den);
int v1 = saturate_cast<int>((tM[3] * dx + tM[4] * dy + tM[5]) * den);
yMx[0] = saturate_cast<short>(v0 >> INTER_BITS);
yMx[1] = saturate_cast<short>(v1 >> INTER_BITS);
mapy.ptr<short>(dy)[dx] = saturate_cast<short>((v1 & (INTER_TAB_SIZE - 1)) *
INTER_TAB_SIZE + (v0 & (INTER_TAB_SIZE - 1)));
}
}
CV_Assert(mapx.type() == CV_16SC2 && ((inter == INTER_NEAREST && mapy.empty()) || mapy.type() == CV_16SC1));
cv::remap(_src, _dst, mapx, mapy, inter, borderType, borderValue);
}
////////////////////////////////////////////////////////////////////////////////////////////////////////
// Tests
////////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(Imgproc_Resize_Test, accuracy) { CV_Resize_Test test; test.safe_run(); }
TEST(Imgproc_Remap_Test, accuracy) { CV_Remap_Test test; test.safe_run(); }
TEST(Imgproc_WarpAffine_Test, accuracy) { CV_WarpAffine_Test test; test.safe_run(); }
TEST(Imgproc_WarpPerspective_Test, accuracy) { CV_WarpPerspective_Test test; test.safe_run(); }
////////////////////////////////////////////////////////////////////////////////////////////////////////
#ifdef OPENCV_TEST_BIGDATA
CV_ENUM(Interpolation, INTER_NEAREST, INTER_LINEAR, INTER_LINEAR_EXACT, INTER_CUBIC, INTER_AREA)
class Imgproc_Resize :
public ::testing::TestWithParam<Interpolation>
{
public:
virtual void SetUp()
{
inter = GetParam();
}
protected:
int inter;
};
TEST_P(Imgproc_Resize, BigSize)
{
cv::Mat src(46342, 46342, CV_8UC3, cv::Scalar::all(10)), dst;
ASSERT_FALSE(src.empty());
ASSERT_NO_THROW(cv::resize(src, dst, cv::Size(), 0.5, 0.5, inter));
}
INSTANTIATE_TEST_CASE_P(Imgproc, Imgproc_Resize, Interpolation::all());
#endif
}} // namespace