erdemhayir
erdemhayir

Reputation: 7

How to use ceres::evaluation_callbacks for inner iteration of ceres::cost functions

I am calculation visual image based on a paper and then optimize my parameters which are focal length, rotation and translation. For that reason I am creating cost function by travelling all the pixel bw real image and virtual image. In my ceres cost functions I basically subtracted normalized virtual image from normalized real image. the Virtual Image is calculated in evaluation_callback functor and the cost is calculated in cost function functor. The problem stems from cost functor. Optimization is terminated at first iteration because gradient is equals to 0. I am using ceres::Central for gradient calculation but virtual image creator functor just called once every iteration. However I need that functor to be called for f(x+h) and f(x-h) seperately.When I calculate normalized real image and normalized virtual image by 9 neighbours I have continuing iteration but every iteration takes 25 second which is not acceptable for my case. I need this evaluation_callback function but I could not make it work.

I look at the evaluation_callbacks definition. it is written that "NOTE: Evaluation callbacks are incompatible with inner iterations."

struct RcpAndFpOptimizer {
    RcpAndFpOptimizer(cv::Mat &V,  const cv::Mat I, int i,int j,double width, double height) : V_(V), I_(I), i_(i),
                               j_(j), width_(width), height_(height){}
    bool operator()(const double* const fp, const double* const rotation, const double* const translation, double* residuals) const {


       double intensity = V_.at<double>(j_, i_);



        double tmp = (double)I_.at<double>(j_,i_)-(double)intensity;
        residuals[0] = tmp;
        //std::cout<<"pixels(i,j): "<<i_<<" "<<j_<<" residual: "<<residuals[0]<<std::endl;
        return true;
    }

    const cv::Mat S_;
    cv::Mat& V_;
    const cv::Mat I_;
    const int i_,j_;
    double width_, height_;
};


virtual void PrepareForEvaluation(bool evaluateJacobians, bool newEvaluationPoint)
    {
        if(evaluateJacobians){
            std::cout<<"evaluation jacobian is called"<<std::endl;
        }
        if (newEvaluationPoint)
        {
            // do your stuff here, e.g. calculate integral image

            //Mat V(height_, width_, CV_8UC1);

            std::cout<<"preperation is called"<<std::endl;


            Intrinsic<double> intrinsicC = INTRINSIC_CAMERA;
            Intrinsic<double> intrinsicP= {(double)fP_[0],(double)fP_[0], double(width_/2), double(height_/2), 0, 0};

            //Convertion of array to  point3d
            Point3d bDist = Point3d(translation_[0],translation_[1], translation_[2]);

            //Convertion euler array to rotation matrix
            const Mat eulerAngles = (cv::Mat_<double>(3,1) << rotArray_[0], rotArray_[1], rotArray_[2]);

            Mat rotM = rcpFinder::euler2rot(eulerAngles);

            Mat tempVImg(height_, width_, CV_8UC1);

            for (int i = 0; i < width_; ++i) {
                for (int j = 0; j < height_ ; ++j) {
                    //std::cout<<"Virtual current x and y pixels: "<<i<<" "<<j<<std::endl;
                    Point3d unprojPRay = rcpFinder::unprojectPoints(Point2i(i,j),intrinsicC);

                    //Assigning the intensity from images
                    tempVImg.at<uchar>(j, i)= rcpFinder::genVirtualImg(S_, intrinsicP, bDist, unprojPRay,
                                                            planeNormalAndDistance_,  rotM);

                    auto pixelIntensity = tempVImg.at<uchar>(Point(j, i));
                    //std::cout<<"pixel intensity "<< pixelIntensity<<std::endl;

                }

            }

            //imshow("Virtual", tempVImg);
            Mat integralV;
            cv::integral(tempVImg, integralV);

            //std::cout<<"integral image type is "<<integralV.type()<<std::endl;

            rcpFinder::normalizePixelsImg(tempVImg, integralV, V_);





            /*imshow("Normalized Img", V_);
            waitKey(0);*/

        }
    }

    // stuff here
    const cv::Mat S_;
    cv::Mat& V_;
    int width_, height_;
    map<int, vector<Point3d>> planeNormalAndDistance_;
    double *translation_;
    double* rotArray_;
    double* fP_;

};

//Calling functors is like following

cv::Mat integralImgI;
    cv::integral(im1, integralImgI);
    cv::Mat normalizedRealImg;
    rcpFinder::normalizePixelsImg(im1, integralImgI, normalizedRealImg);

    Mat normalizedVirtualImg;

    //ceres::CostFunction* total_cost_function = 0;
    for (int i = 1; i < width-1; ++i) {
        for (int j = 1; j < height-1 ; ++j) {
            ceres::CostFunction* cost_function =
                    new ceres::NumericDiffCostFunction<RcpAndFpOptimizer, ceres::CENTRAL, 1, 1, 3, 3>(
                            new RcpAndFpOptimizer(normalizedVirtualImg, normalizedRealImg, i, j, width, height));

            problem.AddResidualBlock(cost_function, NULL, fp, rotationArray, translation);

        }
    }

    ceres::Solver::Options options;
    options.minimizer_progress_to_stdout = true;
    options.max_num_iterations = 50;
    options.update_state_every_iteration = true;



    options.evaluation_callback = (new evaluation_callback_functor(S, normalizedVirtualImg,width, height,
            mapNormalAndDist, translation,rotationArray, fp));

    ceres::Solver::Summary summary;
    ceres::Solve(options, &problem, &summary);

    std::cout << summary.BriefReport() << "\n";

I expected to ceres solver run more than one iteration at least and gradient should start from some values and must be decreasing by iteration.

I normalized the pizels with 9 neighbours. The current solution I have found calculating just 9 pixels of virtual image in cost functor and use them for one pixel normalization but that is too slow. I have 640x480 pixels and 9 times calculation for every pixel. Plus jacobian and gradient calculation in NumericalCOstFunction is too much. That's why I want to calculate virtual image in evaluation_callback functor and normalized it inside of that function and useing normalized image in cost functor. Thank you for your help.

Upvotes: 0

Views: 1325

Answers (1)

Sameer Agarwal
Sameer Agarwal

Reputation: 622

You cannot call evaluationcallback with inneriterations

https://groups.google.com/forum/#!topic/ceres-solver/zjQLIaSuAdQ

Upvotes: 0

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