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d49958141e
Fixes #22799 Replaces #21559 which was taken as a base Connected PR in contrib: [#3388@contrib](https://github.com/opencv/opencv_contrib/pull/3388) ### Changes OK, now this is more Odometry-related PR than Volume-related. Anyway, * `Volume` class gets wrapped * The same was done for helper classes like `VolumeSettings`, `OdometryFrame` and `OdometrySettings` * `OdometryFrame` constructor signature changed to more convenient where depth goes on 1st place, RGB image on 2nd. This works better for depth-only `Odometry` algorithms. * `OdometryFrame` is checked for amount of pyramid layers inside `Odometry::compute()` * `Odometry` was fully wrapped + more docs added * Added Python tests for `Odometry`, `OdometryFrame` and `Volume` * Added Python sample for `Volume` * Minor fixes including better var names ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake
784 lines
26 KiB
C++
784 lines
26 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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namespace opencv_test { namespace {
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static
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void dilateFrame(Mat& image, Mat& depth)
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{
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CV_Assert(!image.empty());
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CV_Assert(image.type() == CV_8UC1);
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CV_Assert(!depth.empty());
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CV_Assert(depth.type() == CV_32FC1);
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CV_Assert(depth.size() == image.size());
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Mat mask(image.size(), CV_8UC1, Scalar(255));
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for(int y = 0; y < depth.rows; y++)
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for(int x = 0; x < depth.cols; x++)
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if(cvIsNaN(depth.at<float>(y,x)) || depth.at<float>(y,x) > 10 || depth.at<float>(y,x) <= FLT_EPSILON)
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mask.at<uchar>(y,x) = 0;
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image.setTo(255, ~mask);
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Mat minImage;
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erode(image, minImage, Mat());
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image.setTo(0, ~mask);
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Mat maxImage;
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dilate(image, maxImage, Mat());
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depth.setTo(FLT_MAX, ~mask);
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Mat minDepth;
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erode(depth, minDepth, Mat());
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depth.setTo(0, ~mask);
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Mat maxDepth;
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dilate(depth, maxDepth, Mat());
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Mat dilatedMask;
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dilate(mask, dilatedMask, Mat(), Point(-1,-1), 1);
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for(int y = 0; y < depth.rows; y++)
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for(int x = 0; x < depth.cols; x++)
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if(!mask.at<uchar>(y,x) && dilatedMask.at<uchar>(y,x))
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{
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image.at<uchar>(y,x) = static_cast<uchar>(0.5f * (static_cast<float>(minImage.at<uchar>(y,x)) +
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static_cast<float>(maxImage.at<uchar>(y,x))));
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depth.at<float>(y,x) = 0.5f * (minDepth.at<float>(y,x) + maxDepth.at<float>(y,x));
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}
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}
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class OdometryTest
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{
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public:
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OdometryTest(OdometryType _otype,
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OdometryAlgoType _algtype,
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double _maxError1,
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double _maxError5,
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double _idError = DBL_EPSILON) :
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otype(_otype),
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algtype(_algtype),
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maxError1(_maxError1),
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maxError5(_maxError5),
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idError(_idError)
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{ }
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void readData(Mat& image, Mat& depth) const;
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static Mat getCameraMatrix()
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{
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float fx = 525.0f, // default
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fy = 525.0f,
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cx = 319.5f,
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cy = 239.5f;
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Matx33f K(fx, 0, cx,
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0, fy, cy,
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0, 0, 1);
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return Mat(K);
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}
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static void generateRandomTransformation(Mat& R, Mat& t);
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void run();
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void checkUMats();
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void prepareFrameCheck();
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OdometryType otype;
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OdometryAlgoType algtype;
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double maxError1;
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double maxError5;
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double idError;
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};
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void OdometryTest::readData(Mat& image, Mat& depth) const
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{
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std::string dataPath = cvtest::TS::ptr()->get_data_path();
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std::string imageFilename = dataPath + "/cv/rgbd/rgb.png";
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std::string depthFilename = dataPath + "/cv/rgbd/depth.png";
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image = imread(imageFilename, 0);
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depth = imread(depthFilename, -1);
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ASSERT_FALSE(image.empty()) << "Image " << imageFilename.c_str() << " can not be read" << std::endl;
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ASSERT_FALSE(depth.empty()) << "Depth " << depthFilename.c_str() << "can not be read" << std::endl;
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CV_DbgAssert(image.type() == CV_8UC1);
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CV_DbgAssert(depth.type() == CV_16UC1);
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{
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Mat depth_flt;
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depth.convertTo(depth_flt, CV_32FC1, 1.f/5000.f);
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depth_flt.setTo(std::numeric_limits<float>::quiet_NaN(), depth_flt < FLT_EPSILON);
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depth = depth_flt;
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}
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}
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void OdometryTest::generateRandomTransformation(Mat& rvec, Mat& tvec)
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{
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const float maxRotation = (float)(3.f / 180.f * CV_PI); //rad
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const float maxTranslation = 0.02f; //m
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RNG& rng = theRNG();
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rvec.create(3, 1, CV_64FC1);
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tvec.create(3, 1, CV_64FC1);
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randu(rvec, Scalar(-1000), Scalar(1000));
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normalize(rvec, rvec, rng.uniform(0.007f, maxRotation));
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randu(tvec, Scalar(-1000), Scalar(1000));
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normalize(tvec, tvec, rng.uniform(0.008f, maxTranslation));
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}
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void OdometryTest::checkUMats()
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{
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Mat K = getCameraMatrix();
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Mat image, depth;
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readData(image, depth);
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UMat uimage, udepth;
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image.copyTo(uimage);
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depth.copyTo(udepth);
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OdometrySettings ods;
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ods.setCameraMatrix(K);
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Odometry odometry = Odometry(otype, ods, algtype);
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OdometryFrame odf(udepth, uimage);
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Mat calcRt;
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uimage.release();
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udepth.release();
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odometry.prepareFrame(odf);
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bool isComputed = odometry.compute(odf, odf, calcRt);
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ASSERT_TRUE(isComputed);
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double diff = cv::norm(calcRt, Mat::eye(4, 4, CV_64FC1));
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ASSERT_LE(diff, idError) << "Incorrect transformation between the same frame (not the identity matrix)" << std::endl;
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}
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void OdometryTest::run()
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{
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Mat K = getCameraMatrix();
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Mat image, depth;
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readData(image, depth);
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OdometrySettings ods;
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ods.setCameraMatrix(K);
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Odometry odometry = Odometry(otype, ods, algtype);
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OdometryFrame odf(depth, image);
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Mat calcRt;
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// 1. Try to find Rt between the same frame (try masks also).
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Mat mask(image.size(), CV_8UC1, Scalar(255));
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odometry.prepareFrame(odf);
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bool isComputed = odometry.compute(odf, odf, calcRt);
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ASSERT_TRUE(isComputed) << "Can not find Rt between the same frame" << std::endl;
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double ndiff = cv::norm(calcRt, Mat::eye(4,4,CV_64FC1));
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ASSERT_LE(ndiff, idError) << "Incorrect transformation between the same frame (not the identity matrix)" << std::endl;
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// 2. Generate random rigid body motion in some ranges several times (iterCount).
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// On each iteration an input frame is warped using generated transformation.
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// Odometry is run on the following pair: the original frame and the warped one.
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// Comparing a computed transformation with an applied one we compute 2 errors:
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// better_1time_count - count of poses which error is less than ground truth pose,
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// better_5times_count - count of poses which error is 5 times less than ground truth pose.
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int iterCount = 100;
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int better_1time_count = 0;
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int better_5times_count = 0;
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for (int iter = 0; iter < iterCount; iter++)
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{
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Mat rvec, tvec;
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generateRandomTransformation(rvec, tvec);
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Affine3d rt(rvec, tvec);
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Mat warpedImage, warpedDepth;
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warpFrame(depth, image, noArray(), rt.matrix, K, warpedDepth, warpedImage);
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dilateFrame(warpedImage, warpedDepth); // due to inaccuracy after warping
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OdometryFrame odfSrc(depth, image);
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OdometryFrame odfDst(warpedDepth, warpedImage);
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odometry.prepareFrames(odfSrc, odfDst);
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isComputed = odometry.compute(odfSrc, odfDst, calcRt);
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if (!isComputed)
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{
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CV_LOG_INFO(NULL, "Iter " << iter << "; Odometry compute returned false");
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continue;
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}
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Mat calcR = calcRt(Rect(0, 0, 3, 3)), calcRvec;
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cv::Rodrigues(calcR, calcRvec);
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calcRvec = calcRvec.reshape(rvec.channels(), rvec.rows);
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Mat calcTvec = calcRt(Rect(3,0,1,3));
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if (cvtest::debugLevel >= 10)
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{
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imshow("image", image);
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imshow("warpedImage", warpedImage);
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Mat resultImage, resultDepth;
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warpFrame(depth, image, noArray(), calcRt, K, resultDepth, resultImage);
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imshow("resultImage", resultImage);
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waitKey(100);
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}
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// compare rotation
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double possibleError = algtype == OdometryAlgoType::COMMON ? 0.015f : 0.01f;
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Affine3f src = Affine3f(Vec3f(rvec), Vec3f(tvec));
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Affine3f res = Affine3f(Vec3f(calcRvec), Vec3f(calcTvec));
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Affine3f src_inv = src.inv();
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Affine3f diff = res * src_inv;
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double rdiffnorm = cv::norm(diff.rvec());
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double tdiffnorm = cv::norm(diff.translation());
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if (rdiffnorm < possibleError && tdiffnorm < possibleError)
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better_1time_count++;
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if (5. * rdiffnorm < possibleError && 5 * tdiffnorm < possibleError)
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better_5times_count++;
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CV_LOG_INFO(NULL, "Iter " << iter);
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CV_LOG_INFO(NULL, "rdiff: " << Vec3f(diff.rvec()) << "; rdiffnorm: " << rdiffnorm);
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CV_LOG_INFO(NULL, "tdiff: " << Vec3f(diff.translation()) << "; tdiffnorm: " << tdiffnorm);
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CV_LOG_INFO(NULL, "better_1time_count " << better_1time_count << "; better_5time_count " << better_5times_count);
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}
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if(static_cast<double>(better_1time_count) < maxError1 * static_cast<double>(iterCount))
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{
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FAIL() << "Incorrect count of accurate poses [1st case]: "
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<< static_cast<double>(better_1time_count) << " / "
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<< maxError1 * static_cast<double>(iterCount) << std::endl;
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}
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if(static_cast<double>(better_5times_count) < maxError5 * static_cast<double>(iterCount))
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{
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FAIL() << "Incorrect count of accurate poses [2nd case]: "
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<< static_cast<double>(better_5times_count) << " / "
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<< maxError5 * static_cast<double>(iterCount) << std::endl;
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}
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}
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void OdometryTest::prepareFrameCheck()
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{
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Mat K = getCameraMatrix();
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Mat gtImage, gtDepth;
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readData(gtImage, gtDepth);
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OdometrySettings ods;
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ods.setCameraMatrix(K);
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Odometry odometry = Odometry(otype, ods, algtype);
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OdometryFrame odf(gtDepth, gtImage);
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odometry.prepareFrame(odf);
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std::vector<int> iters;
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ods.getIterCounts(iters);
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size_t nlevels = iters.size();
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Mat points, mask, depth, gray, rgb, scaled;
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odf.getMask(mask);
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int masknz = countNonZero(mask);
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ASSERT_GT(masknz, 0);
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odf.getDepth(depth);
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Mat patchedDepth = depth.clone();
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patchNaNs(patchedDepth, 0);
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int depthnz = countNonZero(patchedDepth);
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double depthNorm = cv::norm(depth, gtDepth, NORM_INF, mask);
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ASSERT_LE(depthNorm, 0.0);
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Mat gtGray;
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if (otype == OdometryType::RGB || otype == OdometryType::RGB_DEPTH)
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{
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odf.getGrayImage(gray);
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odf.getImage(rgb);
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double rgbNorm = cv::norm(rgb, gtImage);
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ASSERT_LE(rgbNorm, 0.0);
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if (gtImage.channels() == 3)
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cvtColor(gtImage, gtGray, COLOR_BGR2GRAY);
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else
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gtGray = gtImage;
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gtGray.convertTo(gtGray, CV_8U);
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double grayNorm = cv::norm(gray, gtGray);
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ASSERT_LE(grayNorm, 0.0);
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}
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odf.getProcessedDepth(scaled);
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int scalednz = countNonZero(scaled);
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EXPECT_EQ(scalednz, depthnz);
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std::vector<Mat> gtPyrDepth, gtPyrMask;
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//TODO: this depth calculation would become incorrect when we implement bilateral filtering, fixit
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buildPyramid(gtDepth, gtPyrDepth, nlevels - 1);
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for (const auto& gd : gtPyrDepth)
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{
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Mat pm = (gd > ods.getMinDepth()) & (gd < ods.getMaxDepth());
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gtPyrMask.push_back(pm);
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}
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size_t npyr = odf.getPyramidLevels();
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ASSERT_EQ(npyr, nlevels);
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Matx33f levelK = K;
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for (size_t i = 0; i < nlevels; i++)
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{
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Mat depthi, cloudi, maski;
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odf.getPyramidAt(maski, OdometryFramePyramidType::PYR_MASK, i);
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ASSERT_FALSE(maski.empty());
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double mnorm = cv::norm(maski, gtPyrMask[i]);
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EXPECT_LE(mnorm, 16 * 255.0) << "Mask diff is too big at pyr level " << i;
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odf.getPyramidAt(depthi, OdometryFramePyramidType::PYR_DEPTH, i);
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ASSERT_FALSE(depthi.empty());
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double dnorm = cv::norm(depthi, gtPyrDepth[i], NORM_INF, maski);
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EXPECT_LE(dnorm, 8.e-7) << "Depth diff norm is too big at pyr level " << i;
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odf.getPyramidAt(cloudi, OdometryFramePyramidType::PYR_CLOUD, i);
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ASSERT_FALSE(cloudi.empty());
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Mat gtCloud;
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depthTo3d(depthi, levelK, gtCloud);
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double cnorm = cv::norm(cloudi, gtCloud, NORM_INF, maski);
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EXPECT_LE(cnorm, 0.0) << "Cloud diff norm is too big at pyr level " << i;
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// downscale camera matrix for next pyramid level
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levelK = 0.5f * levelK;
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levelK(2, 2) = 1.f;
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}
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if (otype == OdometryType::RGB || otype == OdometryType::RGB_DEPTH)
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{
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std::vector<Mat> gtPyrImage;
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buildPyramid(gtGray, gtPyrImage, nlevels - 1);
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for (size_t i = 0; i < nlevels; i++)
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{
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Mat rgbi, texi, dixi, diyi, maski;
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odf.getPyramidAt(maski, OdometryFramePyramidType::PYR_MASK, i);
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odf.getPyramidAt(rgbi, OdometryFramePyramidType::PYR_IMAGE, i);
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ASSERT_FALSE(rgbi.empty());
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double rnorm = cv::norm(rgbi, gtPyrImage[i], NORM_INF);
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EXPECT_LE(rnorm, 1.0) << "RGB diff is too big at pyr level " << i;
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odf.getPyramidAt(texi, OdometryFramePyramidType::PYR_TEXMASK, i);
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ASSERT_FALSE(texi.empty());
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int tnz = countNonZero(texi);
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EXPECT_GE(tnz, 1000) << "Texture mask has too few valid pixels at pyr level " << i;
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Mat gtDixi, gtDiyi;
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Sobel(rgbi, gtDixi, CV_16S, 1, 0, ods.getSobelSize());
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odf.getPyramidAt(dixi, OdometryFramePyramidType::PYR_DIX, i);
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ASSERT_FALSE(dixi.empty());
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double dixnorm = cv::norm(dixi, gtDixi, NORM_INF, maski);
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EXPECT_LE(dixnorm, 0) << "dI/dx diff is too big at pyr level " << i;
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Sobel(rgbi, gtDiyi, CV_16S, 0, 1, ods.getSobelSize());
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odf.getPyramidAt(diyi, OdometryFramePyramidType::PYR_DIY, i);
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ASSERT_FALSE(diyi.empty());
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double diynorm = cv::norm(diyi, gtDiyi, NORM_INF, maski);
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EXPECT_LE(diynorm, 0) << "dI/dy diff is too big at pyr level " << i;
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}
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}
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if (otype == OdometryType::DEPTH || otype == OdometryType::RGB_DEPTH)
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{
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Ptr<RgbdNormals> normalComputer = odometry.getNormalsComputer();
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ASSERT_FALSE(normalComputer.empty());
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Mat normals;
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odf.getNormals(normals);
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std::vector<Mat> gtPyrNormals;
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buildPyramid(normals, gtPyrNormals, nlevels - 1);
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for (size_t i = 0; i < nlevels; i++)
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{
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Mat gtNormal = gtPyrNormals[i];
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CV_Assert(gtNormal.type() == CV_32FC4);
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for (int y = 0; y < gtNormal.rows; y++)
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{
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Vec4f *normals_row = gtNormal.ptr<Vec4f>(y);
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for (int x = 0; x < gtNormal.cols; x++)
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{
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Vec4f n4 = normals_row[x];
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Point3f n(n4[0], n4[1], n4[2]);
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double nrm = cv::norm(n);
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n *= 1.f / nrm;
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normals_row[x] = Vec4f(n.x, n.y, n.z, 0);
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}
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}
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Mat normmaski;
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odf.getPyramidAt(normmaski, OdometryFramePyramidType::PYR_NORMMASK, i);
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ASSERT_FALSE(normmaski.empty());
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int nnm = countNonZero(normmaski);
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EXPECT_GE(nnm, 1000) << "Normals mask has too few valid pixels at pyr level " << i;
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Mat ptsi;
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odf.getPyramidAt(ptsi, OdometryFramePyramidType::PYR_CLOUD, i);
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Mat normi;
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odf.getPyramidAt(normi, OdometryFramePyramidType::PYR_NORM, i);
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ASSERT_FALSE(normi.empty());
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double nnorm = cv::norm(normi, gtNormal, NORM_INF, normmaski);
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EXPECT_LE(nnorm, 1.8e-7) << "Normals diff is too big at pyr level " << i;
|
|
|
|
if (i == 0)
|
|
{
|
|
double pnnorm = cv::norm(normals, normi, NORM_INF, normmaski);
|
|
EXPECT_GE(pnnorm, 0);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
/****************************************************************************************\
|
|
* Tests registrations *
|
|
\****************************************************************************************/
|
|
|
|
TEST(RGBD_Odometry_Rgb, algorithmic)
|
|
{
|
|
OdometryTest test(OdometryType::RGB, OdometryAlgoType::COMMON, 0.99, 0.99);
|
|
test.run();
|
|
}
|
|
|
|
TEST(RGBD_Odometry_ICP, algorithmic)
|
|
{
|
|
OdometryTest test(OdometryType::DEPTH, OdometryAlgoType::COMMON, 0.99, 0.99);
|
|
test.run();
|
|
}
|
|
|
|
TEST(RGBD_Odometry_RgbdICP, algorithmic)
|
|
{
|
|
OdometryTest test(OdometryType::RGB_DEPTH, OdometryAlgoType::COMMON, 0.99, 0.99);
|
|
test.run();
|
|
}
|
|
|
|
TEST(RGBD_Odometry_FastICP, algorithmic)
|
|
{
|
|
OdometryTest test(OdometryType::DEPTH, OdometryAlgoType::FAST, 0.99, 0.87, 1.84e-5);
|
|
test.run();
|
|
}
|
|
|
|
|
|
TEST(RGBD_Odometry_Rgb, UMats)
|
|
{
|
|
OdometryTest test(OdometryType::RGB, OdometryAlgoType::COMMON, 0.99, 0.99);
|
|
test.checkUMats();
|
|
}
|
|
|
|
TEST(RGBD_Odometry_ICP, UMats)
|
|
{
|
|
OdometryTest test(OdometryType::DEPTH, OdometryAlgoType::COMMON, 0.99, 0.99);
|
|
test.checkUMats();
|
|
}
|
|
|
|
TEST(RGBD_Odometry_RgbdICP, UMats)
|
|
{
|
|
OdometryTest test(OdometryType::RGB_DEPTH, OdometryAlgoType::COMMON, 0.99, 0.99);
|
|
test.checkUMats();
|
|
}
|
|
|
|
TEST(RGBD_Odometry_FastICP, UMats)
|
|
{
|
|
// OpenCL version has slightly less accuracy than CPU version
|
|
OdometryTest test(OdometryType::DEPTH, OdometryAlgoType::FAST, 0.99, 0.99, 1.84e-5);
|
|
test.checkUMats();
|
|
}
|
|
|
|
|
|
TEST(RGBD_Odometry_Rgb, prepareFrame)
|
|
{
|
|
OdometryTest test(OdometryType::RGB, OdometryAlgoType::COMMON, 0.99, 0.99);
|
|
test.prepareFrameCheck();
|
|
}
|
|
|
|
TEST(RGBD_Odometry_ICP, prepareFrame)
|
|
{
|
|
OdometryTest test(OdometryType::DEPTH, OdometryAlgoType::COMMON, 0.99, 0.99);
|
|
test.prepareFrameCheck();
|
|
}
|
|
|
|
TEST(RGBD_Odometry_RgbdICP, prepareFrame)
|
|
{
|
|
OdometryTest test(OdometryType::RGB_DEPTH, OdometryAlgoType::COMMON, 0.99, 0.99);
|
|
test.prepareFrameCheck();
|
|
}
|
|
|
|
TEST(RGBD_Odometry_FastICP, prepareFrame)
|
|
{
|
|
OdometryTest test(OdometryType::DEPTH, OdometryAlgoType::FAST, 0.99, 0.99, FLT_EPSILON);
|
|
test.prepareFrameCheck();
|
|
}
|
|
|
|
|
|
struct WarpFrameTest
|
|
{
|
|
WarpFrameTest() :
|
|
srcDepth(), srcRgb(), srcMask(),
|
|
dstDepth(), dstRgb(), dstMask(),
|
|
warpedDepth(), warpedRgb(), warpedMask()
|
|
{}
|
|
|
|
void run(bool needRgb, bool scaleDown, bool checkMask, bool identityTransform, int depthType, int imageType);
|
|
|
|
Mat srcDepth, srcRgb, srcMask;
|
|
Mat dstDepth, dstRgb, dstMask;
|
|
Mat warpedDepth, warpedRgb, warpedMask;
|
|
};
|
|
|
|
void WarpFrameTest::run(bool needRgb, bool scaleDown, bool checkMask, bool identityTransform, int depthType, int rgbType)
|
|
{
|
|
std::string dataPath = cvtest::TS::ptr()->get_data_path();
|
|
std::string srcDepthFilename = dataPath + "/cv/rgbd/depth.png";
|
|
std::string srcRgbFilename = dataPath + "/cv/rgbd/rgb.png";
|
|
// The depth was generated using the script at testdata/cv/rgbd/warped_depth_generator/warp_test.py
|
|
std::string warpedDepthFilename = dataPath + "/cv/rgbd/warpedDepth.png";
|
|
std::string warpedRgbFilename = dataPath + "/cv/rgbd/warpedRgb.png";
|
|
|
|
srcDepth = imread(srcDepthFilename, IMREAD_UNCHANGED);
|
|
ASSERT_FALSE(srcDepth.empty()) << "Depth " << srcDepthFilename.c_str() << "can not be read" << std::endl;
|
|
|
|
if (identityTransform)
|
|
{
|
|
warpedDepth = srcDepth;
|
|
}
|
|
else
|
|
{
|
|
warpedDepth = imread(warpedDepthFilename, IMREAD_UNCHANGED);
|
|
ASSERT_FALSE(warpedDepth.empty()) << "Depth " << warpedDepthFilename.c_str() << "can not be read" << std::endl;
|
|
}
|
|
|
|
ASSERT_TRUE(srcDepth.type() == CV_16UC1);
|
|
ASSERT_TRUE(warpedDepth.type() == CV_16UC1);
|
|
|
|
Mat epsSrc = srcDepth > 0, epsWarped = warpedDepth > 0;
|
|
|
|
const double depthFactor = 5000.0;
|
|
// scale float types only
|
|
double depthScaleCoeff = scaleDown ? ( depthType == CV_16U ? 1. : 1./depthFactor ) : 1.;
|
|
double transScaleCoeff = scaleDown ? ( depthType == CV_16U ? depthFactor : 1. ) : depthFactor;
|
|
|
|
Mat srcDepthCvt, warpedDepthCvt;
|
|
srcDepth.convertTo(srcDepthCvt, depthType, depthScaleCoeff);
|
|
srcDepth = srcDepthCvt;
|
|
warpedDepth.convertTo(warpedDepthCvt, depthType, depthScaleCoeff);
|
|
warpedDepth = warpedDepthCvt;
|
|
|
|
Scalar badVal;
|
|
switch (depthType)
|
|
{
|
|
case CV_16U:
|
|
badVal = 0;
|
|
break;
|
|
case CV_32F:
|
|
badVal = std::numeric_limits<float>::quiet_NaN();
|
|
break;
|
|
case CV_64F:
|
|
badVal = std::numeric_limits<double>::quiet_NaN();
|
|
break;
|
|
default:
|
|
CV_Error(Error::StsBadArg, "Unsupported depth data type");
|
|
}
|
|
|
|
srcDepth.setTo(badVal, ~epsSrc);
|
|
warpedDepth.setTo(badVal, ~epsWarped);
|
|
|
|
if (checkMask)
|
|
{
|
|
srcMask = epsSrc; warpedMask = epsWarped;
|
|
}
|
|
else
|
|
{
|
|
srcMask = Mat(); warpedMask = Mat();
|
|
}
|
|
|
|
if (needRgb)
|
|
{
|
|
srcRgb = imread(srcRgbFilename, rgbType == CV_8UC1 ? IMREAD_GRAYSCALE : IMREAD_COLOR);
|
|
ASSERT_FALSE(srcRgb.empty()) << "Image " << srcRgbFilename.c_str() << "can not be read" << std::endl;
|
|
|
|
if (identityTransform)
|
|
{
|
|
srcRgb.copyTo(warpedRgb, epsSrc);
|
|
}
|
|
else
|
|
{
|
|
warpedRgb = imread(warpedRgbFilename, rgbType == CV_8UC1 ? IMREAD_GRAYSCALE : IMREAD_COLOR);
|
|
ASSERT_FALSE (warpedRgb.empty()) << "Image " << warpedRgbFilename.c_str() << "can not be read" << std::endl;
|
|
}
|
|
|
|
if (rgbType == CV_8UC4)
|
|
{
|
|
Mat newSrcRgb, newWarpedRgb;
|
|
cvtColor(srcRgb, newSrcRgb, COLOR_RGB2RGBA);
|
|
srcRgb = newSrcRgb;
|
|
// let's keep alpha channel
|
|
std::vector<Mat> warpedRgbChannels;
|
|
split(warpedRgb, warpedRgbChannels);
|
|
warpedRgbChannels.push_back(epsWarped);
|
|
merge(warpedRgbChannels, newWarpedRgb);
|
|
warpedRgb = newWarpedRgb;
|
|
}
|
|
|
|
ASSERT_TRUE(srcRgb.type() == rgbType);
|
|
ASSERT_TRUE(warpedRgb.type() == rgbType);
|
|
}
|
|
else
|
|
{
|
|
srcRgb = Mat(); warpedRgb = Mat();
|
|
}
|
|
|
|
// test data used to generate warped depth and rgb
|
|
// the script used to generate is in opencv_extra repo
|
|
// at testdata/cv/rgbd/warped_depth_generator/warp_test.py
|
|
double fx = 525.0, fy = 525.0,
|
|
cx = 319.5, cy = 239.5;
|
|
Matx33d K(fx, 0, cx,
|
|
0, fy, cy,
|
|
0, 0, 1);
|
|
cv::Affine3d rt;
|
|
cv::Vec3d tr(-0.04, 0.05, 0.6);
|
|
rt = identityTransform ? cv::Affine3d() : cv::Affine3d(cv::Vec3d(0.1, 0.2, 0.3), tr * transScaleCoeff);
|
|
|
|
warpFrame(srcDepth, srcRgb, srcMask, rt.matrix, K, dstDepth, dstRgb, dstMask);
|
|
}
|
|
|
|
typedef std::pair<int, int> WarpFrameInputTypes;
|
|
typedef testing::TestWithParam<WarpFrameInputTypes> WarpFrameInputs;
|
|
|
|
TEST_P(WarpFrameInputs, checkTypes)
|
|
{
|
|
const double shortl2diff = 233.983;
|
|
const double shortlidiff = 1;
|
|
const double floatl2diff = 0.038209;
|
|
const double floatlidiff = 0.00020004;
|
|
|
|
int depthType = GetParam().first;
|
|
int rgbType = GetParam().second;
|
|
|
|
WarpFrameTest w;
|
|
// scale down does not happen on CV_16U
|
|
// to avoid integer overflow
|
|
w.run(/* needRgb */ true, /* scaleDown*/ true,
|
|
/* checkMask */ true, /* identityTransform */ false, depthType, rgbType);
|
|
|
|
double rgbDiff = cv::norm(w.dstRgb, w.warpedRgb, NORM_L2);
|
|
double maskDiff = cv::norm(w.dstMask, w.warpedMask, NORM_L2);
|
|
|
|
EXPECT_EQ(0, maskDiff);
|
|
EXPECT_EQ(0, rgbDiff);
|
|
|
|
double l2diff = cv::norm(w.dstDepth, w.warpedDepth, NORM_L2, w.warpedMask);
|
|
double lidiff = cv::norm(w.dstDepth, w.warpedDepth, NORM_INF, w.warpedMask);
|
|
|
|
double l2threshold = depthType == CV_16U ? shortl2diff : floatl2diff;
|
|
double lithreshold = depthType == CV_16U ? shortlidiff : floatlidiff;
|
|
|
|
EXPECT_LE(l2diff, l2threshold);
|
|
EXPECT_LE(lidiff, lithreshold);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(RGBD_Odometry, WarpFrameInputs, ::testing::Values(
|
|
WarpFrameInputTypes { CV_16U, CV_8UC3 },
|
|
WarpFrameInputTypes { CV_32F, CV_8UC3 },
|
|
WarpFrameInputTypes { CV_64F, CV_8UC3 },
|
|
WarpFrameInputTypes { CV_32F, CV_8UC1 },
|
|
WarpFrameInputTypes { CV_32F, CV_8UC4 }));
|
|
|
|
|
|
TEST(RGBD_Odometry_WarpFrame, identity)
|
|
{
|
|
WarpFrameTest w;
|
|
w.run(/* needRgb */ true, /* scaleDown*/ true, /* checkMask */ true, /* identityTransform */ true, CV_32F, CV_8UC3);
|
|
|
|
double rgbDiff = cv::norm(w.dstRgb, w.warpedRgb, NORM_L2);
|
|
double maskDiff = cv::norm(w.dstMask, w.warpedMask, NORM_L2);
|
|
|
|
ASSERT_EQ(0, rgbDiff);
|
|
ASSERT_EQ(0, maskDiff);
|
|
|
|
double depthDiff = cv::norm(w.dstDepth, w.warpedDepth, NORM_L2, w.dstMask);
|
|
|
|
ASSERT_LE(depthDiff, DBL_EPSILON);
|
|
}
|
|
|
|
TEST(RGBD_Odometry_WarpFrame, noRgb)
|
|
{
|
|
WarpFrameTest w;
|
|
w.run(/* needRgb */ false, /* scaleDown*/ true, /* checkMask */ true, /* identityTransform */ false, CV_32F, CV_8UC3);
|
|
|
|
double maskDiff = cv::norm(w.dstMask, w.warpedMask, NORM_L2);
|
|
ASSERT_EQ(0, maskDiff);
|
|
|
|
double l2diff = cv::norm(w.dstDepth, w.warpedDepth, NORM_L2, w.warpedMask);
|
|
double lidiff = cv::norm(w.dstDepth, w.warpedDepth, NORM_INF, w.warpedMask);
|
|
|
|
ASSERT_LE(l2diff, 0.038209);
|
|
ASSERT_LE(lidiff, 0.00020004);
|
|
}
|
|
|
|
TEST(RGBD_Odometry_WarpFrame, nansAreMasked)
|
|
{
|
|
WarpFrameTest w;
|
|
w.run(/* needRgb */ true, /* scaleDown*/ true, /* checkMask */ false, /* identityTransform */ false, CV_32F, CV_8UC3);
|
|
|
|
double rgbDiff = cv::norm(w.dstRgb, w.warpedRgb, NORM_L2);
|
|
|
|
ASSERT_EQ(0, rgbDiff);
|
|
|
|
Mat goodVals = (w.warpedDepth == w.warpedDepth);
|
|
|
|
double l2diff = cv::norm(w.dstDepth, w.warpedDepth, NORM_L2, goodVals);
|
|
double lidiff = cv::norm(w.dstDepth, w.warpedDepth, NORM_INF, goodVals);
|
|
|
|
ASSERT_LE(l2diff, 0.038209);
|
|
ASSERT_LE(lidiff, 0.00020004);
|
|
}
|
|
|
|
TEST(RGBD_Odometry_WarpFrame, bigScale)
|
|
{
|
|
WarpFrameTest w;
|
|
w.run(/* needRgb */ true, /* scaleDown*/ false, /* checkMask */ true, /* identityTransform */ false, CV_32F, CV_8UC3);
|
|
|
|
double rgbDiff = cv::norm(w.dstRgb, w.warpedRgb, NORM_L2);
|
|
double maskDiff = cv::norm(w.dstMask, w.warpedMask, NORM_L2);
|
|
|
|
ASSERT_EQ(0, maskDiff);
|
|
ASSERT_EQ(0, rgbDiff);
|
|
|
|
double l2diff = cv::norm(w.dstDepth, w.warpedDepth, NORM_L2, w.warpedMask);
|
|
double lidiff = cv::norm(w.dstDepth, w.warpedDepth, NORM_INF, w.warpedMask);
|
|
|
|
ASSERT_LE(l2diff, 191.026565);
|
|
ASSERT_LE(lidiff, 0.99951172);
|
|
}
|
|
|
|
TEST(RGBD_DepthTo3D, mask)
|
|
{
|
|
std::string dataPath = cvtest::TS::ptr()->get_data_path();
|
|
std::string srcDepthFilename = dataPath + "/cv/rgbd/depth.png";
|
|
|
|
Mat srcDepth = imread(srcDepthFilename, IMREAD_UNCHANGED);
|
|
ASSERT_FALSE(srcDepth.empty()) << "Depth " << srcDepthFilename.c_str() << "can not be read" << std::endl;
|
|
ASSERT_TRUE(srcDepth.type() == CV_16UC1);
|
|
|
|
Mat srcMask = srcDepth > 0;
|
|
|
|
// test data used to generate warped depth and rgb
|
|
// the script used to generate is in opencv_extra repo
|
|
// at testdata/cv/rgbd/warped_depth_generator/warp_test.py
|
|
double fx = 525.0, fy = 525.0,
|
|
cx = 319.5, cy = 239.5;
|
|
Matx33d intr(fx, 0, cx,
|
|
0, fy, cy,
|
|
0, 0, 1);
|
|
|
|
Mat srcCloud;
|
|
depthTo3d(srcDepth, intr, srcCloud, srcMask);
|
|
size_t npts = countNonZero(srcMask);
|
|
|
|
ASSERT_EQ(npts, srcCloud.total());
|
|
}
|
|
|
|
}} // namespace
|