mirror of
https://github.com/opencv/opencv.git
synced 2024-12-05 09:49:12 +08:00
8a62b03761
C-API cleanup for OpenCV 5.x (imgproc, highgui) * imgproc: C-API cleanup * imgproc: increase cvtColor test diff threshold * imgproc: C-API cleanup pt.2 * imgproc: C-API cleanup pt.3 * imgproc: C-API cleanup pt.4 * imgproc: C-API cleanup pt.5 * imgproc: C-API cleanup pt.5 * imgproc: C-API cleanup pt.6 * highgui: C-API cleanup * highgui: C-API cleanup pt.2 * highgui: C-API cleanup pt.3 * highgui: C-API cleanup pt.3 * imgproc: C-API cleanup pt.7 * fixup! highgui: C-API cleanup pt.3 * fixup! imgproc: C-API cleanup pt.6 * imgproc: C-API cleanup pt.8 * imgproc: C-API cleanup pt.9 * fixup! imgproc: C-API cleanup pt.9 * fixup! imgproc: C-API cleanup pt.9 * fixup! imgproc: C-API cleanup pt.9 * fixup! imgproc: C-API cleanup pt.9 * fixup! imgproc: C-API cleanup pt.9 * fixup! imgproc: C-API cleanup pt.9
279 lines
9.5 KiB
C++
279 lines
9.5 KiB
C++
// 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.
|
|
|
|
#include "test_precomp.hpp"
|
|
|
|
namespace opencv_test { namespace {
|
|
|
|
CV_ENUM(MatchTemplType, cv::TM_CCORR, cv::TM_CCORR_NORMED,
|
|
cv::TM_SQDIFF, cv::TM_SQDIFF_NORMED,
|
|
cv::TM_CCOEFF, cv::TM_CCOEFF_NORMED)
|
|
|
|
class Imgproc_MatchTemplateWithMask : public TestWithParam<std::tuple<MatType,MatType>>
|
|
{
|
|
protected:
|
|
// Member functions inherited from ::testing::Test
|
|
void SetUp() override;
|
|
|
|
// Matrices for test calculations (always CV_32)
|
|
Mat img_;
|
|
Mat templ_;
|
|
Mat mask_;
|
|
Mat templ_masked_;
|
|
Mat img_roi_masked_;
|
|
// Matrices for call to matchTemplate (have test type)
|
|
Mat img_testtype_;
|
|
Mat templ_testtype_;
|
|
Mat mask_testtype_;
|
|
Mat result_;
|
|
|
|
// Constants
|
|
static const Size IMG_SIZE;
|
|
static const Size TEMPL_SIZE;
|
|
static const Point TEST_POINT;
|
|
};
|
|
|
|
// Arbitraryly chosen test constants
|
|
const Size Imgproc_MatchTemplateWithMask::IMG_SIZE(160, 100);
|
|
const Size Imgproc_MatchTemplateWithMask::TEMPL_SIZE(21, 13);
|
|
const Point Imgproc_MatchTemplateWithMask::TEST_POINT(8, 9);
|
|
|
|
void Imgproc_MatchTemplateWithMask::SetUp()
|
|
{
|
|
int type = std::get<0>(GetParam());
|
|
int type_mask = std::get<1>(GetParam());
|
|
|
|
// Matrices are created with the depth to test (for the call to matchTemplate()), but are also
|
|
// converted to CV_32 for the test calculations, because matchTemplate() also only operates on
|
|
// and returns CV_32.
|
|
img_testtype_.create(IMG_SIZE, type);
|
|
templ_testtype_.create(TEMPL_SIZE, type);
|
|
mask_testtype_.create(TEMPL_SIZE, type_mask);
|
|
|
|
randu(img_testtype_, 0, 10);
|
|
randu(templ_testtype_, 0, 10);
|
|
randu(mask_testtype_, 0, 5);
|
|
|
|
img_testtype_.convertTo(img_, CV_32F);
|
|
templ_testtype_.convertTo(templ_, CV_32F);
|
|
mask_testtype_.convertTo(mask_, CV_32F);
|
|
if (CV_MAT_DEPTH(type_mask) == CV_8U)
|
|
{
|
|
// CV_8U masks are interpreted as binary masks
|
|
mask_.setTo(Scalar::all(1), mask_ != 0);
|
|
}
|
|
if (mask_.channels() != templ_.channels())
|
|
{
|
|
std::vector<Mat> mask_channels(templ_.channels(), mask_);
|
|
merge(mask_channels.data(), templ_.channels(), mask_);
|
|
}
|
|
|
|
Rect roi(TEST_POINT, TEMPL_SIZE);
|
|
img_roi_masked_ = img_(roi).mul(mask_);
|
|
templ_masked_ = templ_.mul(mask_);
|
|
}
|
|
|
|
TEST_P(Imgproc_MatchTemplateWithMask, CompareNaiveImplSQDIFF)
|
|
{
|
|
matchTemplate(img_testtype_, templ_testtype_, result_, cv::TM_SQDIFF, mask_testtype_);
|
|
// Naive implementation for one point
|
|
Mat temp = img_roi_masked_ - templ_masked_;
|
|
Scalar temp_s = sum(temp.mul(temp));
|
|
double val = temp_s[0] + temp_s[1] + temp_s[2] + temp_s[3];
|
|
|
|
EXPECT_NEAR(val, result_.at<float>(TEST_POINT), TEMPL_SIZE.area()*abs(val)*FLT_EPSILON);
|
|
}
|
|
|
|
TEST_P(Imgproc_MatchTemplateWithMask, CompareNaiveImplSQDIFF_NORMED)
|
|
{
|
|
matchTemplate(img_testtype_, templ_testtype_, result_, cv::TM_SQDIFF_NORMED, mask_testtype_);
|
|
// Naive implementation for one point
|
|
Mat temp = img_roi_masked_ - templ_masked_;
|
|
Scalar temp_s = sum(temp.mul(temp));
|
|
double val = temp_s[0] + temp_s[1] + temp_s[2] + temp_s[3];
|
|
|
|
// Normalization
|
|
temp_s = sum(templ_masked_.mul(templ_masked_));
|
|
double norm = temp_s[0] + temp_s[1] + temp_s[2] + temp_s[3];
|
|
temp_s = sum(img_roi_masked_.mul(img_roi_masked_));
|
|
norm *= temp_s[0] + temp_s[1] + temp_s[2] + temp_s[3];
|
|
norm = sqrt(norm);
|
|
val /= norm;
|
|
|
|
EXPECT_NEAR(val, result_.at<float>(TEST_POINT), TEMPL_SIZE.area()*abs(val)*FLT_EPSILON);
|
|
}
|
|
|
|
TEST_P(Imgproc_MatchTemplateWithMask, CompareNaiveImplCCORR)
|
|
{
|
|
matchTemplate(img_testtype_, templ_testtype_, result_, cv::TM_CCORR, mask_testtype_);
|
|
// Naive implementation for one point
|
|
Scalar temp_s = sum(templ_masked_.mul(img_roi_masked_));
|
|
double val = temp_s[0] + temp_s[1] + temp_s[2] + temp_s[3];
|
|
|
|
EXPECT_NEAR(val, result_.at<float>(TEST_POINT), TEMPL_SIZE.area()*abs(val)*FLT_EPSILON);
|
|
}
|
|
|
|
TEST_P(Imgproc_MatchTemplateWithMask, CompareNaiveImplCCORR_NORMED)
|
|
{
|
|
matchTemplate(img_testtype_, templ_testtype_, result_, cv::TM_CCORR_NORMED, mask_testtype_);
|
|
// Naive implementation for one point
|
|
Scalar temp_s = sum(templ_masked_.mul(img_roi_masked_));
|
|
double val = temp_s[0] + temp_s[1] + temp_s[2] + temp_s[3];
|
|
|
|
// Normalization
|
|
temp_s = sum(templ_masked_.mul(templ_masked_));
|
|
double norm = temp_s[0] + temp_s[1] + temp_s[2] + temp_s[3];
|
|
temp_s = sum(img_roi_masked_.mul(img_roi_masked_));
|
|
norm *= temp_s[0] + temp_s[1] + temp_s[2] + temp_s[3];
|
|
norm = sqrt(norm);
|
|
val /= norm;
|
|
|
|
EXPECT_NEAR(val, result_.at<float>(TEST_POINT), TEMPL_SIZE.area()*abs(val)*FLT_EPSILON);
|
|
}
|
|
|
|
TEST_P(Imgproc_MatchTemplateWithMask, CompareNaiveImplCCOEFF)
|
|
{
|
|
matchTemplate(img_testtype_, templ_testtype_, result_, cv::TM_CCOEFF, mask_testtype_);
|
|
// Naive implementation for one point
|
|
Scalar temp_s = sum(mask_);
|
|
for (int i = 0; i < 4; i++)
|
|
{
|
|
if (temp_s[i] != 0.0)
|
|
temp_s[i] = 1.0 / temp_s[i];
|
|
else
|
|
temp_s[i] = 1.0;
|
|
}
|
|
Mat temp = mask_.clone(); temp = temp_s; // Workaround to multiply Mat by Scalar
|
|
Mat temp2 = mask_.clone(); temp2 = sum(templ_masked_); // Workaround to multiply Mat by Scalar
|
|
Mat templx = templ_masked_ - mask_.mul(temp).mul(temp2);
|
|
temp2 = sum(img_roi_masked_); // Workaround to multiply Mat by Scalar
|
|
Mat imgx = img_roi_masked_ - mask_.mul(temp).mul(temp2);
|
|
temp_s = sum(templx.mul(imgx));
|
|
double val = temp_s[0] + temp_s[1] + temp_s[2] + temp_s[3];
|
|
|
|
EXPECT_NEAR(val, result_.at<float>(TEST_POINT), TEMPL_SIZE.area()*abs(val)*FLT_EPSILON);
|
|
}
|
|
|
|
TEST_P(Imgproc_MatchTemplateWithMask, CompareNaiveImplCCOEFF_NORMED)
|
|
{
|
|
matchTemplate(img_testtype_, templ_testtype_, result_, cv::TM_CCOEFF_NORMED, mask_testtype_);
|
|
// Naive implementation for one point
|
|
Scalar temp_s = sum(mask_);
|
|
for (int i = 0; i < 4; i++)
|
|
{
|
|
if (temp_s[i] != 0.0)
|
|
temp_s[i] = 1.0 / temp_s[i];
|
|
else
|
|
temp_s[i] = 1.0;
|
|
}
|
|
Mat temp = mask_.clone(); temp = temp_s; // Workaround to multiply Mat by Scalar
|
|
Mat temp2 = mask_.clone(); temp2 = sum(templ_masked_); // Workaround to multiply Mat by Scalar
|
|
Mat templx = templ_masked_ - mask_.mul(temp).mul(temp2);
|
|
temp2 = sum(img_roi_masked_); // Workaround to multiply Mat by Scalar
|
|
Mat imgx = img_roi_masked_ - mask_.mul(temp).mul(temp2);
|
|
temp_s = sum(templx.mul(imgx));
|
|
double val = temp_s[0] + temp_s[1] + temp_s[2] + temp_s[3];
|
|
|
|
// Normalization
|
|
temp_s = sum(templx.mul(templx));
|
|
double norm = temp_s[0] + temp_s[1] + temp_s[2] + temp_s[3];
|
|
temp_s = sum(imgx.mul(imgx));
|
|
norm *= temp_s[0] + temp_s[1] + temp_s[2] + temp_s[3];
|
|
norm = sqrt(norm);
|
|
val /= norm;
|
|
|
|
EXPECT_NEAR(val, result_.at<float>(TEST_POINT), TEMPL_SIZE.area()*abs(val)*FLT_EPSILON);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(SingleChannelMask, Imgproc_MatchTemplateWithMask,
|
|
Combine(
|
|
Values(CV_32FC1, CV_32FC3, CV_8UC1, CV_8UC3),
|
|
Values(CV_32FC1, CV_8UC1)));
|
|
|
|
INSTANTIATE_TEST_CASE_P(MultiChannelMask, Imgproc_MatchTemplateWithMask,
|
|
Combine(
|
|
Values(CV_32FC3, CV_8UC3),
|
|
Values(CV_32FC3, CV_8UC3)));
|
|
|
|
class Imgproc_MatchTemplateWithMask2 : public TestWithParam<std::tuple<MatType,MatType,
|
|
MatchTemplType>>
|
|
{
|
|
protected:
|
|
// Member functions inherited from ::testing::Test
|
|
void SetUp() override;
|
|
|
|
// Data members
|
|
Mat img_;
|
|
Mat templ_;
|
|
Mat mask_;
|
|
Mat result_withoutmask_;
|
|
Mat result_withmask_;
|
|
|
|
// Constants
|
|
static const Size IMG_SIZE;
|
|
static const Size TEMPL_SIZE;
|
|
};
|
|
|
|
// Arbitraryly chosen test constants
|
|
const Size Imgproc_MatchTemplateWithMask2::IMG_SIZE(160, 100);
|
|
const Size Imgproc_MatchTemplateWithMask2::TEMPL_SIZE(21, 13);
|
|
|
|
void Imgproc_MatchTemplateWithMask2::SetUp()
|
|
{
|
|
int type = std::get<0>(GetParam());
|
|
int type_mask = std::get<1>(GetParam());
|
|
|
|
img_.create(IMG_SIZE, type);
|
|
templ_.create(TEMPL_SIZE, type);
|
|
mask_.create(TEMPL_SIZE, type_mask);
|
|
|
|
randu(img_, 0, 100);
|
|
randu(templ_, 0, 100);
|
|
|
|
if (CV_MAT_DEPTH(type_mask) == CV_8U)
|
|
{
|
|
// CV_8U implies binary mask, so all nonzero values should work
|
|
randu(mask_, 1, 255);
|
|
}
|
|
else
|
|
{
|
|
mask_ = Scalar(1, 1, 1, 1);
|
|
}
|
|
}
|
|
|
|
TEST_P(Imgproc_MatchTemplateWithMask2, CompareWithAndWithoutMask)
|
|
{
|
|
int method = std::get<2>(GetParam());
|
|
|
|
matchTemplate(img_, templ_, result_withmask_, method, mask_);
|
|
matchTemplate(img_, templ_, result_withoutmask_, method);
|
|
|
|
// Get maximum result for relative error calculation
|
|
double min_val, max_val;
|
|
minMaxLoc(abs(result_withmask_), &min_val, &max_val);
|
|
|
|
// Get maximum of absolute diff for comparison
|
|
double mindiff, maxdiff;
|
|
minMaxLoc(abs(result_withmask_ - result_withoutmask_), &mindiff, &maxdiff);
|
|
|
|
EXPECT_LT(maxdiff, max_val*TEMPL_SIZE.area()*FLT_EPSILON);
|
|
}
|
|
|
|
|
|
INSTANTIATE_TEST_CASE_P(SingleChannelMask, Imgproc_MatchTemplateWithMask2,
|
|
Combine(
|
|
Values(CV_32FC1, CV_32FC3, CV_8UC1, CV_8UC3),
|
|
Values(CV_32FC1, CV_8UC1),
|
|
Values(cv::TM_SQDIFF, cv::TM_SQDIFF_NORMED, cv::TM_CCORR, cv::TM_CCORR_NORMED,
|
|
cv::TM_CCOEFF, cv::TM_CCOEFF_NORMED)));
|
|
|
|
INSTANTIATE_TEST_CASE_P(MultiChannelMask, Imgproc_MatchTemplateWithMask2,
|
|
Combine(
|
|
Values(CV_32FC3, CV_8UC3),
|
|
Values(CV_32FC3, CV_8UC3),
|
|
Values(cv::TM_SQDIFF, cv::TM_SQDIFF_NORMED, cv::TM_CCORR, cv::TM_CCORR_NORMED,
|
|
cv::TM_CCOEFF, cv::TM_CCOEFF_NORMED)));
|
|
|
|
}} // namespace
|