Merge pull request #8852 from BKNio:testsForVideoStab

modules/videostab/test/test_main.cpp

@@ -0,0 +1,3 @@
+#include "test_precomp.hpp"
+
+CV_TEST_MAIN("cv")

modules/videostab/test/test_motion_estimation.cpp

@@ -0,0 +1,171 @@
+// 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 testUtil
+{
+
+cv::RNG rng(/*std::time(0)*/0);
+
+const float sigma = 1.f;
+const float pointsMaxX = 500.f;
+const float pointsMaxY = 500.f;
+const int testRun = 5000;
+
+void generatePoints(cv::Mat points);
+void addNoise(cv::Mat points);
+
+cv::Mat generateTransform(const cv::videostab::MotionModel model);
+
+double performTest(const cv::videostab::MotionModel model, int size);
+
+}
+
+void testUtil::generatePoints(cv::Mat points)
+{
+    CV_Assert(!points.empty());
+    for(int i = 0; i < points.cols; ++i)
+    {
+        points.at<float>(0, i) = rng.uniform(0.f, pointsMaxX);
+        points.at<float>(1, i) = rng.uniform(0.f, pointsMaxY);
+        points.at<float>(2, i) = 1.f;
+    }
+}
+
+void testUtil::addNoise(cv::Mat points)
+{
+    CV_Assert(!points.empty());
+    for(int i = 0; i < points.cols; i++)
+    {
+        points.at<float>(0, i) += static_cast<float>(rng.gaussian(sigma));
+        points.at<float>(1, i) += static_cast<float>(rng.gaussian(sigma));
+
+    }
+}
+
+
+cv::Mat testUtil::generateTransform(const cv::videostab::MotionModel model)
+{
+    /*----------Params----------*/
+    const float minAngle = 0.f, maxAngle = static_cast<float>(CV_PI);
+    const float minScale = 0.5f, maxScale = 2.f;
+    const float maxTranslation = 100.f;
+    const float affineCoeff = 3.f;
+    /*----------Params----------*/
+
+    cv::Mat transform = cv::Mat::eye(3, 3, CV_32F);
+
+    if(model != cv::videostab::MM_ROTATION)
+    {
+        transform.at<float>(0,2) = rng.uniform(-maxTranslation, maxTranslation);
+        transform.at<float>(1,2) = rng.uniform(-maxTranslation, maxTranslation);
+    }
+
+    if(model != cv::videostab::MM_AFFINE)
+    {
+
+        if(model != cv::videostab::MM_TRANSLATION_AND_SCALE &&
+                model != cv::videostab::MM_TRANSLATION)
+        {
+            const float angle = rng.uniform(minAngle, maxAngle);
+
+            transform.at<float>(1,1) = transform.at<float>(0,0) = std::cos(angle);
+            transform.at<float>(0,1) = std::sin(angle);
+            transform.at<float>(1,0) = -transform.at<float>(0,1);
+
+        }
+
+        if(model == cv::videostab::MM_TRANSLATION_AND_SCALE ||
+                model == cv::videostab::MM_SIMILARITY)
+        {
+            const float scale = rng.uniform(minScale, maxScale);
+
+            transform.at<float>(0,0) *= scale;
+            transform.at<float>(1,1) *= scale;
+
+        }
+
+    }
+    else
+    {
+        transform.at<float>(0,0) = rng.uniform(-affineCoeff, affineCoeff);
+        transform.at<float>(0,1) = rng.uniform(-affineCoeff, affineCoeff);
+        transform.at<float>(1,0) = rng.uniform(-affineCoeff, affineCoeff);
+        transform.at<float>(1,1) = rng.uniform(-affineCoeff, affineCoeff);
+    }
+
+    return transform;
+}
+
+
+double testUtil::performTest(const cv::videostab::MotionModel model, int size)
+{
+    cv::Ptr<cv::videostab::MotionEstimatorRansacL2> estimator = cv::makePtr<cv::videostab::MotionEstimatorRansacL2>(model);
+
+    estimator->setRansacParams(cv::videostab::RansacParams(size, 3.f*testUtil::sigma /*3 sigma rule*/, 0.5f, 0.5f));
+
+    double disparity = 0.;
+
+    for(int attempt = 0; attempt < testUtil::testRun; attempt++)
+    {
+        const cv::Mat transform = testUtil::generateTransform(model);
+
+        const int pointsNumber = testUtil::rng.uniform(10, 100);
+
+        cv::Mat points(3, pointsNumber, CV_32F);
+
+        testUtil::generatePoints(points);
+
+        cv::Mat transformedPoints = transform * points;
+
+        testUtil::addNoise(transformedPoints);
+
+        const cv::Mat src = points.rowRange(0,2).t();
+        const cv::Mat dst = transformedPoints.rowRange(0,2).t();
+
+        bool isOK = false;
+        const cv::Mat estTransform = estimator->estimate(src.reshape(2), dst.reshape(2), &isOK);
+
+        CV_Assert(isOK);
+        const cv::Mat testPoints = estTransform * points;
+
+        const double norm = cv::norm(testPoints, transformedPoints, cv::NORM_INF);
+
+        disparity = std::max(disparity, norm);
+    }
+
+    return disparity;
+
+}
+
+TEST(Regression, MM_TRANSLATION)
+{
+    EXPECT_LT(testUtil::performTest(cv::videostab::MM_TRANSLATION, 2), 7.f);
+}
+
+TEST(Regression, MM_TRANSLATION_AND_SCALE)
+{
+    EXPECT_LT(testUtil::performTest(cv::videostab::MM_TRANSLATION_AND_SCALE, 3), 7.f);
+}
+
+TEST(Regression, MM_ROTATION)
+{
+    EXPECT_LT(testUtil::performTest(cv::videostab::MM_ROTATION, 2), 7.f);
+}
+
+TEST(Regression, MM_RIGID)
+{
+    EXPECT_LT(testUtil::performTest(cv::videostab::MM_RIGID, 3), 7.f);
+}
+
+TEST(Regression, MM_SIMILARITY)
+{
+    EXPECT_LT(testUtil::performTest(cv::videostab::MM_SIMILARITY, 4), 7.f);
+}
+
+TEST(Regression, MM_AFFINE)
+{
+    EXPECT_LT(testUtil::performTest(cv::videostab::MM_AFFINE, 6), 9.f);
+}

modules/videostab/test/test_precomp.hpp

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+#ifdef __GNUC__
+#  pragma GCC diagnostic ignored "-Wmissing-declarations"
+#  if defined __clang__ || defined __APPLE__
+#    pragma GCC diagnostic ignored "-Wmissing-prototypes"
+#    pragma GCC diagnostic ignored "-Wextra"
+#  endif
+#endif
+
+#ifndef __OPENCV_TEST_PRECOMP_HPP__
+#define __OPENCV_TEST_PRECOMP_HPP__
+
+#include <iostream>
+#include "opencv2/ts.hpp"
+#include "opencv2/videostab.hpp"
+
+#endif