wehub-resource-sync
118 lines
3.7 KiB
C++
118 lines
3.7 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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#include "test_precomp.hpp"
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#include <vector>
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namespace opencv_test { namespace {
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Mat CropMid(InputArray src, int w, int h)
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{
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Mat mat = src.getMat();
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return mat(Rect(mat.cols / 2 - w / 2, mat.rows / 2 - h / 2, w, h));
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}
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Mat GenerateTestImage(Size size)
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{
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Mat image = Mat::zeros(size.height * 2, size.width * 2, CV_32F);
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rectangle(image,
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Point(static_cast<int>(size.width * 0.1), static_cast<int>(size.height * 0.1)),
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Point(static_cast<int>(size.width * 0.9), static_cast<int>(size.height * 0.9)),
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Scalar(1),
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-1);
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return image;
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}
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void TestPhaseCorrelationIterative(const Size& size, const double maxShift)
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{
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const auto iters = std::max(201., maxShift * 10 + 1);
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const Point2d shiftOffset(-maxShift * 0.5, -maxShift * 0.5);
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Mat image1 = GenerateTestImage(size);
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Mat crop1 = CropMid(image1, size.width, size.height);
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Mat image2 = image1.clone();
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std::vector<double> pcErrors;
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std::vector<double> ipcErrors;
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for (int i = 0; i < iters; ++i)
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{
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const auto shift =
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Point2d(maxShift * i / (iters - 1), maxShift * i / (iters - 1)) + shiftOffset;
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const Mat Tmat = (Mat_<double>(2, 3) << 1., 0., shift.x, 0., 1., shift.y);
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warpAffine(image1, image2, Tmat, image2.size());
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Mat crop2 = CropMid(image2, size.width, size.height);
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const auto ipcshift = phaseCorrelateIterative(crop1, crop2);
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const auto pcshift = phaseCorrelate(crop1, crop2);
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pcErrors.push_back(
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0.5 * std::abs(pcshift.x - shift.y) + 0.5 * std::abs(pcshift.y - shift.x));
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ipcErrors.push_back(
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0.5 * std::abs(ipcshift.x - shift.y) + 0.5 * std::abs(ipcshift.y - shift.x));
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// error should be low
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EXPECT_NEAR(ipcshift.x - shift.x, 0.0, 0.1);
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EXPECT_NEAR(ipcshift.y - shift.y, 0.0, 0.1);
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}
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cv::Scalar pcMean, pcStddev, ipcMean, ipcStddev;
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meanStdDev(ipcErrors, ipcMean, ipcStddev);
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meanStdDev(pcErrors, pcMean, pcStddev);
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// average error should be low
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ASSERT_LT(ipcMean[0], 0.03);
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// average error should be less than non-iterative average error
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ASSERT_LT(ipcMean[0], pcMean[0]);
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// error stddev should be less than non-iterative error stddev
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ASSERT_LT(ipcStddev[0], pcStddev[0]);
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}
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TEST(Imgproc_PhaseCorrelationIterative, 256x128_accuracy)
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{
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TestPhaseCorrelationIterative(Size(256, 128), 1);
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}
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TEST(Imgproc_PhaseCorrelationIterative, 64x64_accuracy_shift_1)
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{
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TestPhaseCorrelationIterative(Size(64, 64), 1);
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}
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TEST(Imgproc_PhaseCorrelationIterative, 64x64_accuracy_shift_16)
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{
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TestPhaseCorrelationIterative(Size(64, 64), 16);
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}
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TEST(Imgproc_PhaseCorrelationIterative, 0x0_image)
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{
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ASSERT_ANY_THROW(TestPhaseCorrelationIterative(Size(0, 0), 1));
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}
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TEST(Imgproc_PhaseCorrelationIterative, 1x1_image)
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{
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ASSERT_ANY_THROW(TestPhaseCorrelationIterative(Size(1, 1), 1));
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}
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TEST(Imgproc_PhaseCorrelationIterative, accuracy_real_img)
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{
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Mat img = imread(cvtest::TS::ptr()->get_data_path() + "shared/airplane.png", IMREAD_GRAYSCALE);
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if (img.empty())
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return;
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img.convertTo(img, CV_64FC1);
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const int xLen = 256;
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const int yLen = 256;
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const int xShift = 40;
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const int yShift = 14;
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Mat roi1 = img(Rect(xShift, yShift, xLen, yLen));
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Mat roi2 = img(Rect(0, 0, xLen, yLen));
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const Point2d ipcShift = phaseCorrelateIterative(roi1, roi2);
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ASSERT_NEAR(ipcShift.x, (double)xShift, 1.);
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ASSERT_NEAR(ipcShift.y, (double)yShift, 1.);
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}
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}} // namespace opencv_test
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