OpenCV/opencv_contrib/modules/rgbd/test/test_odometry.cpp

// 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

// This code is also subject to the license terms in the LICENSE_KinectFusion.md file found in this module's directory

// This code is also subject to the license terms in the LICENSE_WillowGarage.md file found in this module's directory

#include "test_precomp.hpp"

namespace opencv_test { namespace {

#define SHOW_DEBUG_LOG     0
#define SHOW_DEBUG_IMAGES  0

static 
void warpFrame(const Mat& image, const Mat& depth, const Mat& rvec, const Mat& tvec, const Mat& K,
               Mat& warpedImage, Mat& warpedDepth)
{
    CV_Assert(!image.empty());
    CV_Assert(image.type() == CV_8UC1);
    
    CV_Assert(depth.size() == image.size());
    CV_Assert(depth.type() == CV_32FC1);
    
    CV_Assert(!rvec.empty());
    CV_Assert(rvec.total() == 3);
    CV_Assert(rvec.type() == CV_64FC1);
    
    CV_Assert(!tvec.empty());
    CV_Assert(tvec.size() == Size(1, 3));
    CV_Assert(tvec.type() == CV_64FC1);
    
    warpedImage.create(image.size(), CV_8UC1);
    warpedImage = Scalar(0);
    warpedDepth.create(image.size(), CV_32FC1);
    warpedDepth = Scalar(FLT_MAX);
    
    Mat cloud;
    depthTo3d(depth, K, cloud);
    Mat Rt = Mat::eye(4, 4, CV_64FC1);
    {
        Mat R, dst;
        Rodrigues(rvec, R);
        
        dst = Rt(Rect(0,0,3,3));
        R.copyTo(dst);
        
        dst = Rt(Rect(3,0,1,3));
        tvec.copyTo(dst);
    }
    Mat warpedCloud, warpedImagePoints;
    perspectiveTransform(cloud, warpedCloud, Rt);
    projectPoints(warpedCloud.reshape(3, 1), Mat(3,1,CV_32FC1, Scalar(0)), Mat(3,1,CV_32FC1, Scalar(0)), K, Mat(1,5,CV_32FC1, Scalar(0)), warpedImagePoints);
    warpedImagePoints = warpedImagePoints.reshape(2, cloud.rows);
    Rect r(0, 0, image.cols, image.rows);
    for(int y = 0; y < cloud.rows; y++)
    {
        for(int x = 0; x < cloud.cols; x++)
        {
            Point p = warpedImagePoints.at<Point2f>(y,x);
            if(r.contains(p))
            {
                float curDepth = warpedDepth.at<float>(p.y, p.x);
                float newDepth = warpedCloud.at<Point3f>(y, x).z;
                if(newDepth < curDepth && newDepth > 0)
                {
                    warpedImage.at<uchar>(p.y, p.x) = image.at<uchar>(y,x);
                    warpedDepth.at<float>(p.y, p.x) = newDepth;
                }
            }
        }
    }
    warpedDepth.setTo(std::numeric_limits<float>::quiet_NaN(), warpedDepth > 100);
}

static
void dilateFrame(Mat& image, Mat& depth)
{
    CV_Assert(!image.empty());
    CV_Assert(image.type() == CV_8UC1);

    CV_Assert(!depth.empty());
    CV_Assert(depth.type() == CV_32FC1);
    CV_Assert(depth.size() == image.size());

    Mat mask(image.size(), CV_8UC1, Scalar(255));
    for(int y = 0; y < depth.rows; y++)
        for(int x = 0; x < depth.cols; x++)
            if(cvIsNaN(depth.at<float>(y,x)) || depth.at<float>(y,x) > 10 || depth.at<float>(y,x) <= FLT_EPSILON)
                mask.at<uchar>(y,x) = 0;

    image.setTo(255, ~mask);
    Mat minImage;
    erode(image, minImage, Mat());

    image.setTo(0, ~mask);
    Mat maxImage;
    dilate(image, maxImage, Mat());

    depth.setTo(FLT_MAX, ~mask);
    Mat minDepth;
    erode(depth, minDepth, Mat());

    depth.setTo(0, ~mask);
    Mat maxDepth;
    dilate(depth, maxDepth, Mat());

    Mat dilatedMask;
    dilate(mask, dilatedMask, Mat(), Point(-1,-1), 1);
    for(int y = 0; y < depth.rows; y++)
        for(int x = 0; x < depth.cols; x++)
            if(!mask.at<uchar>(y,x) && dilatedMask.at<uchar>(y,x))
            {
                image.at<uchar>(y,x) = static_cast<uchar>(0.5f * (static_cast<float>(minImage.at<uchar>(y,x)) +
                                                                  static_cast<float>(maxImage.at<uchar>(y,x))));
                depth.at<float>(y,x) = 0.5f * (minDepth.at<float>(y,x) + maxDepth.at<float>(y,x));
            }
}

class CV_OdometryTest : public cvtest::BaseTest
{
public:
    CV_OdometryTest(const Ptr<Odometry>& _odometry,
                    double _maxError1,
                    double _maxError5,
                    double _idError = DBL_EPSILON) :
        odometry(_odometry),
        maxError1(_maxError1),
        maxError5(_maxError5),
        idError(_idError)
    { }

protected:
    bool readData(Mat& image, Mat& depth) const;
    static void generateRandomTransformation(Mat& R, Mat& t);

    virtual void run(int);

    Ptr<Odometry> odometry;
    double maxError1;
    double maxError5;
    double idError;
};

bool CV_OdometryTest::readData(Mat& image, Mat& depth) const
{
    std::string imageFilename = ts->get_data_path() + "rgbd/rgb.png";
    std::string depthFilename = ts->get_data_path() + "rgbd/depth.png";
    
    image = imread(imageFilename,  0);
    depth = imread(depthFilename, -1);
    
    if(image.empty())
    {
        ts->printf( cvtest::TS::LOG, "Image %s can not be read.\n", imageFilename.c_str() );
        ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
        return false;
    }
    if(depth.empty())
    {
        ts->printf( cvtest::TS::LOG, "Depth %s can not be read.\n", depthFilename.c_str() );
        ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
        ts->set_gtest_status();
        return false;
    }
    
    CV_DbgAssert(image.type() == CV_8UC1);
    CV_DbgAssert(depth.type() == CV_16UC1);
    {
        Mat depth_flt;
        depth.convertTo(depth_flt, CV_32FC1, 1.f/5000.f);
        depth_flt.setTo(std::numeric_limits<float>::quiet_NaN(), depth_flt < FLT_EPSILON);
        depth = depth_flt;
    }
    
    return true;
}

void CV_OdometryTest::generateRandomTransformation(Mat& rvec, Mat& tvec)
{
    const float maxRotation = (float)(3.f / 180.f * CV_PI); //rad
    const float maxTranslation = 0.02f; //m

    RNG& rng = theRNG();
    rvec.create(3, 1, CV_64FC1);
    tvec.create(3, 1, CV_64FC1);

    randu(rvec, Scalar(-1000), Scalar(1000));
    normalize(rvec, rvec, rng.uniform(0.007f, maxRotation));

    randu(tvec, Scalar(-1000), Scalar(1000));
    normalize(tvec, tvec, rng.uniform(0.008f, maxTranslation));
}

void CV_OdometryTest::run(int)
{
    float fx = 525.0f, // default
          fy = 525.0f,
          cx = 319.5f,
          cy = 239.5f;
    Mat K = Mat::eye(3,3,CV_32FC1);
    {
        K.at<float>(0,0) = fx;
        K.at<float>(1,1) = fy;
        K.at<float>(0,2) = cx;
        K.at<float>(1,2) = cy;
    }
    
    Mat image, depth;
    if(!readData(image, depth))
        return;
        
    odometry->setCameraMatrix(K);
    
    Mat calcRt;
    
    // 1. Try to find Rt between the same frame (try masks also).
    bool isComputed = odometry->compute(image, depth, Mat(image.size(), CV_8UC1, Scalar(255)),
                                        image, depth, Mat(image.size(), CV_8UC1, Scalar(255)),
                                        calcRt);
    if(!isComputed)
    {
        ts->printf(cvtest::TS::LOG, "Can not find Rt between the same frame");
        ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
    }
    double diff = cv::norm(calcRt, Mat::eye(4,4,CV_64FC1));
    if(diff > idError)
    {
        ts->printf(cvtest::TS::LOG, "Incorrect transformation between the same frame (not the identity matrix), diff = %f", diff);
        ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
    }
    
    // 2. Generate random rigid body motion in some ranges several times (iterCount).
    // On each iteration an input frame is warped using generated transformation.
    // Odometry is run on the following pair: the original frame and the warped one.
    // Comparing a computed transformation with an applied one we compute 2 errors:
    // better_1time_count - count of poses which error is less than ground truth pose,
    // better_5times_count - count of poses which error is 5 times less than ground truth pose.
    int iterCount = 100;
    int better_1time_count = 0;
    int better_5times_count = 0;
    for(int iter = 0; iter < iterCount; iter++)
    {
        Mat rvec, tvec;
        generateRandomTransformation(rvec, tvec);
        Mat warpedImage, warpedDepth;
        warpFrame(image, depth, rvec, tvec, K, warpedImage, warpedDepth);
        dilateFrame(warpedImage, warpedDepth); // due to inaccuracy after warping
        
        Mat imageMask(image.size(), CV_8UC1, Scalar(255));
        isComputed = odometry->compute(image, depth, imageMask, warpedImage, warpedDepth, imageMask, calcRt);
        if(!isComputed)
            continue;
                
        Mat calcR = calcRt(Rect(0,0,3,3)), calcRvec;
        Rodrigues(calcR, calcRvec);
        calcRvec = calcRvec.reshape(rvec.channels(), rvec.rows);
        Mat calcTvec = calcRt(Rect(3,0,1,3));

#if SHOW_DEBUG_IMAGES
        imshow("image", image);
        imshow("warpedImage", warpedImage);
        Mat resultImage, resultDepth;
        warpFrame(image, depth, calcRvec, calcTvec, K, resultImage, resultDepth);
        imshow("resultImage", resultImage);
        waitKey();
#endif

        // compare rotation
        double rdiffnorm = cv::norm(rvec - calcRvec),
               rnorm = cv::norm(rvec);
        double tdiffnorm = cv::norm(tvec - calcTvec),
               tnorm = cv::norm(tvec);
        if(rdiffnorm < rnorm &&  tdiffnorm < tnorm)
            better_1time_count++;
        if(5. * rdiffnorm < rnorm && 5 * tdiffnorm < tnorm)
            better_5times_count++;

#if SHOW_DEBUG_LOG
        std::cout << "Iter " << iter << std::endl;
        std::cout << "rdiffnorm " << rdiffnorm << "; rnorm " << rnorm << std::endl;
        std::cout << "tdiffnorm " << tdiffnorm << "; tnorm " << tnorm << std::endl;
        
        std::cout << "better_1time_count " << better_1time_count << "; better_5time_count " << better_5times_count << std::endl;
#endif
    }

    
    if(static_cast<double>(better_1time_count) < maxError1 * static_cast<double>(iterCount))
    {
        ts->printf(cvtest::TS::LOG, "\nIncorrect count of accurate poses [1st case]: %f / %f", static_cast<double>(better_1time_count), maxError1 * static_cast<double>(iterCount));
        ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
    }
    
    if(static_cast<double>(better_5times_count) < maxError5 * static_cast<double>(iterCount))
    {
        ts->printf(cvtest::TS::LOG, "\nIncorrect count of accurate poses [2nd case]: %f / %f", static_cast<double>(better_5times_count), maxError5 * static_cast<double>(iterCount));
        ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
    }
}

/****************************************************************************************\
*                                Tests registrations                                     *
\****************************************************************************************/

TEST(RGBD_Odometry_Rgbd, algorithmic)
{
    CV_OdometryTest test(cv::rgbd::Odometry::create("RgbdOdometry"), 0.99, 0.89);
    test.safe_run();
}

TEST(RGBD_Odometry_ICP, algorithmic)
{
    CV_OdometryTest test(cv::rgbd::Odometry::create("ICPOdometry"), 0.99, 0.99);
    test.safe_run();
}

TEST(RGBD_Odometry_RgbdICP, algorithmic)
{
    CV_OdometryTest test(cv::rgbd::Odometry::create("RgbdICPOdometry"), 0.99, 0.99);
    test.safe_run();
}

TEST(RGBD_Odometry_FastICP, algorithmic)
{
    CV_OdometryTest test(cv::rgbd::Odometry::create("FastICPOdometry"), 0.99, 0.99, FLT_EPSILON);
    test.safe_run();
}


}} // namespace