init - 初始化项目

modules/calib3d/test/test_affine_partial2d_estimator.cpp

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+// copy or use the software.
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+//                For Open Source Computer Vision Library
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+//     this list of conditions and the following disclaimer.
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+// and on any theory of liability, whether in contract, strict liability,
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+//M*/
+
+#include "test_precomp.hpp"
+
+namespace opencv_test { namespace {
+
+CV_ENUM(Method, RANSAC, LMEDS)
+typedef TestWithParam<Method> EstimateAffinePartial2D;
+
+static float rngIn(float from, float to) { return from + (to-from) * (float)theRNG(); }
+
+// get random matrix of affine transformation limited to combinations of translation,
+// rotation, and uniform scaling
+static Mat rngPartialAffMat() {
+    double theta = rngIn(0, (float)CV_PI*2.f);
+    double scale = rngIn(0, 3);
+    double tx = rngIn(-2, 2);
+    double ty = rngIn(-2, 2);
+    double aff[2*3] = { std::cos(theta) * scale, -std::sin(theta) * scale, tx,
+                        std::sin(theta) * scale,  std::cos(theta) * scale, ty };
+    return Mat(2, 3, CV_64F, aff).clone();
+}
+
+TEST_P(EstimateAffinePartial2D, test2Points)
+{
+    // try more transformations
+    for (size_t i = 0; i < 500; ++i)
+    {
+        Mat aff = rngPartialAffMat();
+
+        // setting points that are no in the same line
+        Mat fpts(1, 2, CV_32FC2);
+        Mat tpts(1, 2, CV_32FC2);
+
+        fpts.at<Point2f>(0) = Point2f( rngIn(1,2), rngIn(5,6) );
+        fpts.at<Point2f>(1) = Point2f( rngIn(3,4), rngIn(3,4) );
+
+        transform(fpts, tpts, aff);
+
+        vector<uchar> inliers;
+        Mat aff_est = estimateAffinePartial2D(fpts, tpts, inliers, GetParam() /* method */);
+
+        EXPECT_NEAR(0., cvtest::norm(aff_est, aff, NORM_INF), 1e-3);
+
+        // all must be inliers
+        EXPECT_EQ(countNonZero(inliers), 2);
+    }
+}
+
+TEST_P(EstimateAffinePartial2D, testNPoints)
+{
+    // try more transformations
+    for (size_t i = 0; i < 500; ++i)
+    {
+        Mat aff = rngPartialAffMat();
+
+        const int method = GetParam();
+        const int n = 100;
+        int m;
+        // LMEDS can't handle more than 50% outliers (by design)
+        if (method == LMEDS)
+            m = 3*n/5;
+        else
+            m = 2*n/5;
+        const float shift_outl = 15.f;
+        const float noise_level = 20.f;
+
+        Mat fpts(1, n, CV_32FC2);
+        Mat tpts(1, n, CV_32FC2);
+
+        randu(fpts, 0., 100.);
+        transform(fpts, tpts, aff);
+
+        /* adding noise to some points */
+        Mat outliers = tpts.colRange(m, n);
+        outliers.reshape(1) += shift_outl;
+
+        Mat noise (outliers.size(), outliers.type());
+        randu(noise, 0., noise_level);
+        outliers += noise;
+
+        vector<uchar> inliers;
+        Mat aff_est = estimateAffinePartial2D(fpts, tpts, inliers, method);
+
+        EXPECT_FALSE(aff_est.empty());
+
+        EXPECT_NEAR(0., cvtest::norm(aff_est, aff, NORM_INF), 1e-4);
+
+        bool inliers_good = count(inliers.begin(), inliers.end(), 1) == m &&
+            m == accumulate(inliers.begin(), inliers.begin() + m, 0);
+
+        EXPECT_TRUE(inliers_good);
+    }
+}
+
+// test conversion from other datatypes than float
+TEST_P(EstimateAffinePartial2D, testConversion)
+{
+    Mat aff = rngPartialAffMat();
+    aff.convertTo(aff, CV_32S); // convert to int to transform ints properly
+
+    std::vector<Point> fpts(3);
+    std::vector<Point> tpts(3);
+
+    fpts[0] = Point2f( rngIn(1,2), rngIn(5,6) );
+    fpts[1] = Point2f( rngIn(3,4), rngIn(3,4) );
+    fpts[2] = Point2f( rngIn(1,2), rngIn(3,4) );
+
+    transform(fpts, tpts, aff);
+
+    vector<uchar> inliers;
+    Mat aff_est = estimateAffinePartial2D(fpts, tpts, inliers, GetParam() /* method */);
+
+    ASSERT_FALSE(aff_est.empty());
+
+    aff.convertTo(aff, CV_64F); // need to convert back before compare
+    EXPECT_NEAR(0., cvtest::norm(aff_est, aff, NORM_INF), 1e-3);
+
+    // all must be inliers
+    EXPECT_EQ(countNonZero(inliers), 3);
+}
+
+INSTANTIATE_TEST_CASE_P(Calib3d, EstimateAffinePartial2D, Method::all());
+
+
+// https://github.com/opencv/opencv/issues/14259
+TEST(EstimateAffinePartial2D, issue_14259_dont_change_inputs)
+{
+    /*const static*/ float pts0_[10] = {
+            0.0f, 0.0f,
+            0.0f, 8.0f,
+            4.0f, 0.0f, // outlier
+            8.0f, 8.0f,
+            8.0f, 0.0f
+    };
+    /*const static*/ float pts1_[10] = {
+            0.1f, 0.1f,
+            0.1f, 8.1f,
+            0.0f, 4.0f, // outlier
+            8.1f, 8.1f,
+            8.1f, 0.1f
+    };
+
+    Mat pts0(Size(1, 5), CV_32FC2, (void*)pts0_);
+    Mat pts1(Size(1, 5), CV_32FC2, (void*)pts1_);
+
+    Mat pts0_copy = pts0.clone();
+    Mat pts1_copy = pts1.clone();
+
+    Mat inliers;
+
+    cv::Mat A = cv::estimateAffinePartial2D(pts0, pts1, inliers);
+
+    for(int i = 0; i < pts0.rows; ++i)
+    {
+        EXPECT_EQ(pts0_copy.at<Vec2f>(i), pts0.at<Vec2f>(i)) << "pts0: i=" << i;
+    }
+
+    for(int i = 0; i < pts1.rows; ++i)
+    {
+        EXPECT_EQ(pts1_copy.at<Vec2f>(i), pts1.at<Vec2f>(i)) << "pts1: i=" << i;
+    }
+
+    EXPECT_EQ(0, (int)inliers.at<uchar>(2));
+}
+
+}} // namespace