opencv/samples/cpp/image_alignment.cpp

/*
* This sample demonstrates the use of the function
* findTransformECC that implements the image alignment ECC algorithm
*
*
* The demo loads an image (defaults to fruits.jpg) and it artificially creates
* a template image based on the given motion type. When two images are given,
* the first image is the input image and the second one defines the template image.
* In the latter case, you can also parse the warp's initialization.
*
* Input and output warp files consist of the raw warp (transform) elements
*
* Authors: G. Evangelidis, INRIA, Grenoble, France
*          M. Asbach, Fraunhofer IAIS, St. Augustin, Germany
*/
#include <opencv2/highgui.hpp>
#include <opencv2/video.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/core/utility.hpp>

#include <stdio.h>
#include <string>
#include <time.h>
#include <iostream>
#include <fstream>

using namespace cv;
using namespace std;

static void help(void);
static int readWarp(string iFilename, Mat& warp, int motionType);
static int saveWarp(string fileName, const Mat& warp, int motionType);
static void draw_warped_roi(Mat& image, const int width, const int height, Mat& W);

#define HOMO_VECTOR(H, x, y)\
    H.at<float>(0,0) = (float)(x);\
    H.at<float>(1,0) = (float)(y);\
    H.at<float>(2,0) = 1.;

#define GET_HOMO_VALUES(X, x, y)\
    (x) = static_cast<float> (X.at<float>(0,0)/X.at<float>(2,0));\
    (y) = static_cast<float> (X.at<float>(1,0)/X.at<float>(2,0));


const std::string keys =
    "{@inputImage    | fruits.jpg    | input image filename }"
    "{@templateImage |               | template image filename (optional)}"
    "{@inputWarp     |               | input warp (matrix) filename (optional)}"
    "{n numOfIter    | 50            | ECC's iterations }"
    "{e epsilon      | 0.0001        | ECC's convergence epsilon }"
    "{o outputWarp   | outWarp.ecc   | output warp (matrix) filename }"
    "{m motionType   | affine        | type of motion (translation, euclidean, affine, homography) }"
    "{v verbose      | 0             | display initial and final images }"
    "{w warpedImfile | warpedECC.png | warped input image }"
;


static void help(void)
{

    cout << "\nThis file demostrates the use of the ECC image alignment algorithm. When one image"
        " is given, the template image is artificially formed by a random warp. When both images"
        " are given, the initialization of the warp by command line parsing is possible. "
        "If inputWarp is missing, the identity transformation initializes the algorithm. \n" << endl;

    cout << "\nUsage example (one image): \n./ecc fruits.jpg -o=outWarp.ecc "
        "-m=euclidean -e=1e-6 -N=70 -v=1 \n" << endl;

    cout << "\nUsage example (two images with initialization): \n./ecc yourInput.png yourTemplate.png "
        "yourInitialWarp.ecc -o=outWarp.ecc -m=homography -e=1e-6 -N=70 -v=1 -w=yourFinalImage.png \n" << endl;

}

static int readWarp(string iFilename, Mat& warp, int motionType){

    // it reads from file a specific number of raw values:
    // 9 values for homography, 6 otherwise
    CV_Assert(warp.type()==CV_32FC1);
    int numOfElements;
    if (motionType==MOTION_HOMOGRAPHY)
        numOfElements=9;
    else
        numOfElements=6;

    int i;
    int ret_value;

    ifstream myfile(iFilename.c_str());
    if (myfile.is_open()){
        float* matPtr = warp.ptr<float>(0);
        for(i=0; i<numOfElements; i++){
            myfile >> matPtr[i];
        }
        ret_value = 1;
    }
    else {
        cout << "Unable to open file " << iFilename.c_str() << endl;
        ret_value = 0;
    }
    return ret_value;
}

static int saveWarp(string fileName, const Mat& warp, int motionType)
{
    // it saves the raw matrix elements in a file
    CV_Assert(warp.type()==CV_32FC1);

    const float* matPtr = warp.ptr<float>(0);
    int ret_value;

    ofstream outfile(fileName.c_str());
    if( !outfile ) {
        cerr << "error in saving "
            << "Couldn't open file '" << fileName.c_str() << "'!" << endl;
        ret_value = 0;
    }
    else {//save the warp's elements
        outfile << matPtr[0] << " " << matPtr[1] << " " << matPtr[2] << endl;
        outfile << matPtr[3] << " " << matPtr[4] << " " << matPtr[5] << endl;
        if (motionType==MOTION_HOMOGRAPHY){
            outfile << matPtr[6] << " " << matPtr[7] << " " << matPtr[8] << endl;
        }
        ret_value = 1;
    }
    return ret_value;

}


static void draw_warped_roi(Mat& image, const int width, const int height, Mat& W)
{
    Point2f top_left, top_right, bottom_left, bottom_right;

    Mat  H = Mat (3, 1, CV_32F);
    Mat  U = Mat (3, 1, CV_32F);

    Mat warp_mat = Mat::eye (3, 3, CV_32F);

    for (int y = 0; y < W.rows; y++)
        for (int x = 0; x < W.cols; x++)
            warp_mat.at<float>(y,x) = W.at<float>(y,x);

    //warp the corners of rectangle

    // top-left
    HOMO_VECTOR(H, 1, 1);
    gemm(warp_mat, H, 1, 0, 0, U);
    GET_HOMO_VALUES(U, top_left.x, top_left.y);

    // top-right
    HOMO_VECTOR(H, width, 1);
    gemm(warp_mat, H, 1, 0, 0, U);
    GET_HOMO_VALUES(U, top_right.x, top_right.y);

    // bottom-left
    HOMO_VECTOR(H, 1, height);
    gemm(warp_mat, H, 1, 0, 0, U);
    GET_HOMO_VALUES(U, bottom_left.x, bottom_left.y);

    // bottom-right
    HOMO_VECTOR(H, width, height);
    gemm(warp_mat, H, 1, 0, 0, U);
    GET_HOMO_VALUES(U, bottom_right.x, bottom_right.y);

    // draw the warped perimeter
    line(image, top_left, top_right, Scalar(255,0,255));
    line(image, top_right, bottom_right, Scalar(255,0,255));
    line(image, bottom_right, bottom_left, Scalar(255,0,255));
    line(image, bottom_left, top_left, Scalar(255,0,255));
}

int main (const int argc, const char * argv[])
{

    CommandLineParser parser(argc, argv, keys);
    parser.about("ECC demo");

    if (argc<2) {
        parser.printMessage();
        help();
        return 1;
    }

    string imgFile = parser.get<string>(0);
    string tempImgFile = parser.get<string>(1);
    string inWarpFile = parser.get<string>(2);

    int number_of_iterations = parser.get<int>("n");
    double termination_eps = parser.get<double>("e");
    string warpType = parser.get<string>("m");
    int verbose = parser.get<int>("v");
    string finalWarp = parser.get<string>("o");
    string warpedImFile = parser.get<string>("w");

    if (!(warpType == "translation" || warpType == "euclidean"
        || warpType == "affine" || warpType == "homography"))
    {
        cerr << "Invalid motion transformation" << endl;
        return -1;
    }

    int mode_temp;
    if (warpType == "translation")
        mode_temp = MOTION_TRANSLATION;
    else if (warpType == "euclidean")
        mode_temp = MOTION_EUCLIDEAN;
    else if (warpType == "affine")
        mode_temp = MOTION_AFFINE;
    else
        mode_temp = MOTION_HOMOGRAPHY;

    Mat inputImage = imread(imgFile,0);
    if (inputImage.empty())
    {
        cerr << "Unable to load the inputImage" <<  endl;
        return -1;
    }

    Mat target_image;
    Mat template_image;

    if (tempImgFile!="") {
        inputImage.copyTo(target_image);
        template_image = imread(tempImgFile,0);
        if (template_image.empty()){
            cerr << "Unable to load the template image" << endl;
            return -1;
        }

    }
    else{ //apply random waro to input image
        resize(inputImage, target_image, Size(216, 216));
        Mat warpGround;
        cv::RNG rng;
        double angle;
        switch (mode_temp) {
        case MOTION_TRANSLATION:
            warpGround = (Mat_<float>(2,3) << 1, 0, (rng.uniform(10.f, 20.f)),
                0, 1, (rng.uniform(10.f, 20.f)));
            warpAffine(target_image, template_image, warpGround,
                Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);
            break;
        case MOTION_EUCLIDEAN:
            angle = CV_PI/30 + CV_PI*rng.uniform((double)-2.f, (double)2.f)/180;

            warpGround = (Mat_<float>(2,3) << cos(angle), -sin(angle), (rng.uniform(10.f, 20.f)),
                sin(angle), cos(angle), (rng.uniform(10.f, 20.f)));
            warpAffine(target_image, template_image, warpGround,
                Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);
            break;
        case MOTION_AFFINE:

            warpGround = (Mat_<float>(2,3) << (1-rng.uniform(-0.05f, 0.05f)),
                (rng.uniform(-0.03f, 0.03f)), (rng.uniform(10.f, 20.f)),
                (rng.uniform(-0.03f, 0.03f)), (1-rng.uniform(-0.05f, 0.05f)),
                (rng.uniform(10.f, 20.f)));
            warpAffine(target_image, template_image, warpGround,
                Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);
            break;
        case MOTION_HOMOGRAPHY:
            warpGround = (Mat_<float>(3,3) << (1-rng.uniform(-0.05f, 0.05f)),
                (rng.uniform(-0.03f, 0.03f)), (rng.uniform(10.f, 20.f)),
                (rng.uniform(-0.03f, 0.03f)), (1-rng.uniform(-0.05f, 0.05f)),(rng.uniform(10.f, 20.f)),
                (rng.uniform(0.0001f, 0.0003f)), (rng.uniform(0.0001f, 0.0003f)), 1.f);
            warpPerspective(target_image, template_image, warpGround,
                Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);
            break;
        }
    }


    const int warp_mode = mode_temp;

    // initialize or load the warp matrix
    Mat warp_matrix;
    if (warpType == "homography")
        warp_matrix = Mat::eye(3, 3, CV_32F);
    else
        warp_matrix = Mat::eye(2, 3, CV_32F);

    if (inWarpFile!=""){
        int readflag = readWarp(inWarpFile, warp_matrix, warp_mode);
        if ((!readflag) || warp_matrix.empty())
        {
            cerr << "-> Check warp initialization file" << endl << flush;
            return -1;
        }
    }
    else {

        printf("\n ->Perfomarnce Warning: Identity warp ideally assumes images of "
            "similar size. If the deformation is strong, the identity warp may not "
            "be a good initialization. \n");

    }

    if (number_of_iterations > 200)
        cout << "-> Warning: too many iterations " << endl;

    if (warp_mode != MOTION_HOMOGRAPHY)
        warp_matrix.rows = 2;

    // start timing
    const double tic_init = (double) getTickCount ();
    double cc = findTransformECC (template_image, target_image, warp_matrix, warp_mode,
        TermCriteria (TermCriteria::COUNT+TermCriteria::EPS,
        number_of_iterations, termination_eps));

    if (cc == -1)
    {
        cerr << "The execution was interrupted. The correlation value is going to be minimized." << endl;
        cerr << "Check the warp initialization and/or the size of images." << endl << flush;
    }

    // end timing
    const double toc_final  = (double) getTickCount ();
    const double total_time = (toc_final-tic_init)/(getTickFrequency());
    if (verbose){
        cout << "Alignment time (" << warpType << " transformation): "
            << total_time << " sec" << endl << flush;
        //  cout << "Final correlation: " << cc << endl << flush;

    }

    // save the final warp matrix
    saveWarp(finalWarp, warp_matrix, warp_mode);

    if (verbose){
        cout << "\nThe final warp has been saved in the file: " << finalWarp << endl << flush;
    }

    // save the final warped image
    Mat warped_image = Mat(template_image.rows, template_image.cols, CV_32FC1);
    if (warp_mode != MOTION_HOMOGRAPHY)
        warpAffine      (target_image, warped_image, warp_matrix, warped_image.size(),
        INTER_LINEAR + WARP_INVERSE_MAP);
    else
        warpPerspective (target_image, warped_image, warp_matrix, warped_image.size(),
        INTER_LINEAR + WARP_INVERSE_MAP);

    //save the warped image
    imwrite(warpedImFile, warped_image);

    // display resulting images
    if (verbose)
    {

        cout << "The warped image has been saved in the file: " << warpedImFile << endl << flush;

        namedWindow ("image",    WINDOW_AUTOSIZE);
        namedWindow ("template", WINDOW_AUTOSIZE);
        namedWindow ("warped image",   WINDOW_AUTOSIZE);
        namedWindow ("error (black: no error)", WINDOW_AUTOSIZE);

        moveWindow  ("template", 350, 350);
        moveWindow  ("warped image",   600, 300);
        moveWindow  ("error (black: no error)", 900, 300);

        // draw boundaries of corresponding regions
        Mat identity_matrix = Mat::eye(3,3,CV_32F);

        draw_warped_roi (target_image,   template_image.cols-2, template_image.rows-2, warp_matrix);
        draw_warped_roi (template_image, template_image.cols-2, template_image.rows-2, identity_matrix);

        Mat errorImage;
        subtract(template_image, warped_image, errorImage);
        double max_of_error;
        minMaxLoc(errorImage, NULL, &max_of_error);

        // show images
        cout << "Press any key to exit the demo (you might need to click on the images before)." << endl << flush;

        imshow ("image",    target_image);
        waitKey (200);
        imshow ("template", template_image);
        waitKey (200);
        imshow ("warped image",   warped_image);
        waitKey(200);
        imshow ("error (black: no error)",  abs(errorImage)*255/max_of_error);
        waitKey(0);

    }

    // done
    return 0;
}