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opencv/modules/video/test/test_ecc.cpp
Danny 1b844f8413
Merge pull request #19993 from danielenricocahall:fix-compute-ecc-issue 
Fix unsigned int bug in computeECC

* address issue with unsigned ints in computeEcc

* remove additional logic checking firstOctave

* use swap instead of same src/dst

* simplify the unsigned check logic
2021-04-30 17:20:52 +00:00

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
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// For Open Source Computer Vision Library
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#include "test_precomp.hpp"
namespace opencv_test { namespace {
class CV_ECC_BaseTest : public cvtest::BaseTest
{
public:
CV_ECC_BaseTest();
protected:
double computeRMS(const Mat& mat1, const Mat& mat2);
bool isMapCorrect(const Mat& mat);
double MAX_RMS_ECC;//upper bound for RMS error
int ntests;//number of tests per motion type
int ECC_iterations;//number of iterations for ECC
double ECC_epsilon; //we choose a negative value, so that
// ECC_iterations are always executed
};
CV_ECC_BaseTest::CV_ECC_BaseTest()
{
MAX_RMS_ECC=0.1;
ntests = 3;
ECC_iterations = 50;
ECC_epsilon = -1; //-> negative value means that ECC_Iterations will be executed
}
bool CV_ECC_BaseTest::isMapCorrect(const Mat& map)
{
bool tr = true;
float mapVal;
for(int i =0; i<map.rows; i++)
for(int j=0; j<map.cols; j++){
mapVal = map.at<float>(i, j);
tr = tr & (!cvIsNaN(mapVal) && (fabs(mapVal) < 1e9));
}
return tr;
}
double CV_ECC_BaseTest::computeRMS(const Mat& mat1, const Mat& mat2){
CV_Assert(mat1.rows == mat2.rows);
CV_Assert(mat1.cols == mat2.cols);
Mat errorMat;
subtract(mat1, mat2, errorMat);
return sqrt(errorMat.dot(errorMat)/(mat1.rows*mat1.cols));
}
class CV_ECC_Test_Translation : public CV_ECC_BaseTest
{
public:
CV_ECC_Test_Translation();
protected:
void run(int);
bool testTranslation(int);
};
CV_ECC_Test_Translation::CV_ECC_Test_Translation(){}
bool CV_ECC_Test_Translation::testTranslation(int from)
{
Mat img = imread( string(ts->get_data_path()) + "shared/fruits.png", 0);
if (img.empty())
{
ts->printf( ts->LOG, "test image can not be read");
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
return false;
}
Mat testImg;
resize(img, testImg, Size(216, 216), 0, 0, INTER_LINEAR_EXACT);
cv::RNG rng = ts->get_rng();
int progress=0;
for (int k=from; k<ntests; k++){
ts->update_context( this, k, true );
progress = update_progress(progress, k, ntests, 0);
Mat translationGround = (Mat_<float>(2,3) << 1, 0, (rng.uniform(10.f, 20.f)),
0, 1, (rng.uniform(10.f, 20.f)));
Mat warpedImage;
warpAffine(testImg, warpedImage, translationGround,
Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);
Mat mapTranslation = (Mat_<float>(2,3) << 1, 0, 0, 0, 1, 0);
findTransformECC(warpedImage, testImg, mapTranslation, 0,
TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, ECC_iterations, ECC_epsilon));
if (!isMapCorrect(mapTranslation)){
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
return false;
}
if (computeRMS(mapTranslation, translationGround)>MAX_RMS_ECC){
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
ts->printf( ts->LOG, "RMS = %f",
computeRMS(mapTranslation, translationGround));
return false;
}
}
return true;
}
void CV_ECC_Test_Translation::run(int from)
{
if (!testTranslation(from))
return;
ts->set_failed_test_info(cvtest::TS::OK);
}
class CV_ECC_Test_Euclidean : public CV_ECC_BaseTest
{
public:
CV_ECC_Test_Euclidean();
protected:
void run(int);
bool testEuclidean(int);
};
CV_ECC_Test_Euclidean::CV_ECC_Test_Euclidean() { }
bool CV_ECC_Test_Euclidean::testEuclidean(int from)
{
Mat img = imread( string(ts->get_data_path()) + "shared/fruits.png", 0);
if (img.empty())
{
ts->printf( ts->LOG, "test image can not be read");
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
return false;
}
Mat testImg;
resize(img, testImg, Size(216, 216), 0, 0, INTER_LINEAR_EXACT);
cv::RNG rng = ts->get_rng();
int progress = 0;
for (int k=from; k<ntests; k++){
ts->update_context( this, k, true );
progress = update_progress(progress, k, ntests, 0);
double angle = CV_PI/30 + CV_PI*rng.uniform((double)-2.f, (double)2.f)/180;
Mat euclideanGround = (Mat_<float>(2,3) << cos(angle), -sin(angle), (rng.uniform(10.f, 20.f)),
sin(angle), cos(angle), (rng.uniform(10.f, 20.f)));
Mat warpedImage;
warpAffine(testImg, warpedImage, euclideanGround,
Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);
Mat mapEuclidean = (Mat_<float>(2,3) << 1, 0, 0, 0, 1, 0);
findTransformECC(warpedImage, testImg, mapEuclidean, 1,
TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, ECC_iterations, ECC_epsilon));
if (!isMapCorrect(mapEuclidean)){
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
return false;
}
if (computeRMS(mapEuclidean, euclideanGround)>MAX_RMS_ECC){
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
ts->printf( ts->LOG, "RMS = %f",
computeRMS(mapEuclidean, euclideanGround));
return false;
}
}
return true;
}
void CV_ECC_Test_Euclidean::run(int from)
{
if (!testEuclidean(from))
return;
ts->set_failed_test_info(cvtest::TS::OK);
}
class CV_ECC_Test_Affine : public CV_ECC_BaseTest
{
public:
CV_ECC_Test_Affine();
protected:
void run(int);
bool testAffine(int);
};
CV_ECC_Test_Affine::CV_ECC_Test_Affine(){}
bool CV_ECC_Test_Affine::testAffine(int from)
{
Mat img = imread( string(ts->get_data_path()) + "shared/fruits.png", 0);
if (img.empty())
{
ts->printf( ts->LOG, "test image can not be read");
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
return false;
}
Mat testImg;
resize(img, testImg, Size(216, 216), 0, 0, INTER_LINEAR_EXACT);
cv::RNG rng = ts->get_rng();
int progress = 0;
for (int k=from; k<ntests; k++){
ts->update_context( this, k, true );
progress = update_progress(progress, k, ntests, 0);
Mat affineGround = (Mat_<float>(2,3) << (1-rng.uniform(-0.05f, 0.05f)),
(rng.uniform(-0.03f, 0.03f)), (rng.uniform(10.f, 20.f)),
(rng.uniform(-0.03f, 0.03f)), (1-rng.uniform(-0.05f, 0.05f)),
(rng.uniform(10.f, 20.f)));
Mat warpedImage;
warpAffine(testImg, warpedImage, affineGround,
Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);
Mat mapAffine = (Mat_<float>(2,3) << 1, 0, 0, 0, 1, 0);
findTransformECC(warpedImage, testImg, mapAffine, 2,
TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, ECC_iterations, ECC_epsilon));
if (!isMapCorrect(mapAffine)){
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
return false;
}
if (computeRMS(mapAffine, affineGround)>MAX_RMS_ECC){
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
ts->printf( ts->LOG, "RMS = %f",
computeRMS(mapAffine, affineGround));
return false;
}
}
return true;
}
void CV_ECC_Test_Affine::run(int from)
{
if (!testAffine(from))
return;
ts->set_failed_test_info(cvtest::TS::OK);
}
class CV_ECC_Test_Homography : public CV_ECC_BaseTest
{
public:
CV_ECC_Test_Homography();
protected:
void run(int);
bool testHomography(int);
};
CV_ECC_Test_Homography::CV_ECC_Test_Homography(){}
bool CV_ECC_Test_Homography::testHomography(int from)
{
Mat img = imread( string(ts->get_data_path()) + "shared/fruits.png", 0);
if (img.empty())
{
ts->printf( ts->LOG, "test image can not be read");
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
return false;
}
Mat testImg;
resize(img, testImg, Size(216, 216), 0, 0, INTER_LINEAR_EXACT);
cv::RNG rng = ts->get_rng();
int progress = 0;
for (int k=from; k<ntests; k++){
ts->update_context( this, k, true );
progress = update_progress(progress, k, ntests, 0);
Mat homoGround = (Mat_<float>(3,3) << (1-rng.uniform(-0.05f, 0.05f)),
(rng.uniform(-0.03f, 0.03f)), (rng.uniform(10.f, 20.f)),
(rng.uniform(-0.03f, 0.03f)), (1-rng.uniform(-0.05f, 0.05f)),(rng.uniform(10.f, 20.f)),
(rng.uniform(0.0001f, 0.0003f)), (rng.uniform(0.0001f, 0.0003f)), 1.f);
Mat warpedImage;
warpPerspective(testImg, warpedImage, homoGround,
Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);
Mat mapHomography = Mat::eye(3, 3, CV_32F);
findTransformECC(warpedImage, testImg, mapHomography, 3,
TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, ECC_iterations, ECC_epsilon));
if (!isMapCorrect(mapHomography)){
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
return false;
}
if (computeRMS(mapHomography, homoGround)>MAX_RMS_ECC){
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
ts->printf( ts->LOG, "RMS = %f",
computeRMS(mapHomography, homoGround));
return false;
}
}
return true;
}
void CV_ECC_Test_Homography::run(int from)
{
if (!testHomography(from))
return;
ts->set_failed_test_info(cvtest::TS::OK);
}
class CV_ECC_Test_Mask : public CV_ECC_BaseTest
{
public:
CV_ECC_Test_Mask();
protected:
void run(int);
bool testMask(int);
};
CV_ECC_Test_Mask::CV_ECC_Test_Mask(){}
bool CV_ECC_Test_Mask::testMask(int from)
{
Mat img = imread( string(ts->get_data_path()) + "shared/fruits.png", 0);
if (img.empty())
{
ts->printf( ts->LOG, "test image can not be read");
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
return false;
}
Mat scaledImage;
resize(img, scaledImage, Size(216, 216), 0, 0, INTER_LINEAR_EXACT );
Mat_<float> testImg;
scaledImage.convertTo(testImg, testImg.type());
cv::RNG rng = ts->get_rng();
int progress=0;
for (int k=from; k<ntests; k++){
ts->update_context( this, k, true );
progress = update_progress(progress, k, ntests, 0);
Mat translationGround = (Mat_<float>(2,3) << 1, 0, (rng.uniform(10.f, 20.f)),
0, 1, (rng.uniform(10.f, 20.f)));
Mat warpedImage;
warpAffine(testImg, warpedImage, translationGround,
Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);
Mat mapTranslation = (Mat_<float>(2,3) << 1, 0, 0, 0, 1, 0);
Mat_<unsigned char> mask = Mat_<unsigned char>::ones(testImg.rows, testImg.cols);
for (int i=testImg.rows*2/3; i<testImg.rows; i++) {
for (int j=testImg.cols*2/3; j<testImg.cols; j++) {
testImg(i, j) = 0;
mask(i, j) = 0;
}
}
findTransformECC(warpedImage, testImg, mapTranslation, 0,
TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, ECC_iterations, ECC_epsilon), mask);
if (!isMapCorrect(mapTranslation)){
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
return false;
}
if (computeRMS(mapTranslation, translationGround)>MAX_RMS_ECC){
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
ts->printf( ts->LOG, "RMS = %f",
computeRMS(mapTranslation, translationGround));
return false;
}
// Test with non-default gaussian blur.
findTransformECC(warpedImage, testImg, mapTranslation, 0,
TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, ECC_iterations, ECC_epsilon), mask, 1);
if (!isMapCorrect(mapTranslation)){
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
return false;
}
if (computeRMS(mapTranslation, translationGround)>MAX_RMS_ECC){
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
ts->printf( ts->LOG, "RMS = %f",
computeRMS(mapTranslation, translationGround));
return false;
}
}
return true;
}
void CV_ECC_Test_Mask::run(int from)
{
if (!testMask(from))
return;
ts->set_failed_test_info(cvtest::TS::OK);
}
TEST(Video_ECC_Test_Compute, accuracy)
{
Mat testImg = (Mat_<float>(3, 3) << 1, 0, 0, 1, 0, 0, 1, 0, 0);
Mat warpedImage = (Mat_<float>(3, 3) << 0, 1, 0, 0, 1, 0, 0, 1, 0);
Mat_<unsigned char> mask = Mat_<unsigned char>::ones(testImg.rows, testImg.cols);
double ecc = computeECC(warpedImage, testImg, mask);
EXPECT_NEAR(ecc, -0.5f, 1e-5f);
}
TEST(Video_ECC_Test_Compute, bug_14657)
{
/*
* Simple test case - a 2 x 2 matrix with 10, 10, 10, 6. When the mean (36 / 4 = 9) is subtracted,
* it results in 1, 1, 1, 0 for the unsigned int case - compare to 1, 1, 1, -3 in the signed case.
* For this reason, when the same matrix was provided as the input and the template, we didn't get 1 as expected.
*/
Mat img = (Mat_<uint8_t>(2, 2) << 10, 10, 10, 6);
EXPECT_NEAR(computeECC(img, img), 1.0f, 1e-5f);
}
TEST(Video_ECC_Translation, accuracy) { CV_ECC_Test_Translation test; test.safe_run();}
TEST(Video_ECC_Euclidean, accuracy) { CV_ECC_Test_Euclidean test; test.safe_run(); }
TEST(Video_ECC_Affine, accuracy) { CV_ECC_Test_Affine test; test.safe_run(); }
TEST(Video_ECC_Homography, accuracy) { CV_ECC_Test_Homography test; test.safe_run(); }
TEST(Video_ECC_Mask, accuracy) { CV_ECC_Test_Mask test; test.safe_run(); }
}} // namespace
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