/*
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license. If you do not agree to this license, do not download, install,
copy or use the software.

                          License Agreement
               For Open Source Computer Vision Library
                       (3-clause BSD License)

Copyright (C) 2013, OpenCV Foundation, all rights reserved.
Third party copyrights are property of their respective owners.

Redistribution and use in source and binary forms, with or without modification,
are permitted provided that the following conditions are met:

  * Redistributions of source code must retain the above copyright notice,
    this list of conditions and the following disclaimer.

  * Redistributions in binary form must reproduce the above copyright notice,
    this list of conditions and the following disclaimer in the documentation
    and/or other materials provided with the distribution.

  * Neither the names of the copyright holders nor the names of the contributors
    may be used to endorse or promote products derived from this software
    without specific prior written permission.

This software is provided by the copyright holders and contributors "as is" and
any express or implied warranties, including, but not limited to, the implied
warranties of merchantability and fitness for a particular purpose are
disclaimed. In no event shall copyright holders or contributors be liable for
any direct, indirect, incidental, special, exemplary, or consequential damages
(including, but not limited to, procurement of substitute goods or services;
loss of use, data, or profits; or business interruption) however caused
and on any theory of liability, whether in contract, strict liability,
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the use of this software, even if advised of the possibility of such damage.
*/


#include <opencv2/highgui.hpp>
#include <opencv2/aruco.hpp>
#include <vector>
#include <iostream>

using namespace std;
using namespace cv;

namespace {
const char* about = "Pose estimation using a ArUco Planar Grid board";
const char* keys  =
        "{w        |       | Number of squares in X direction }"
        "{h        |       | Number of squares in Y direction }"
        "{l        |       | Marker side lenght (in pixels) }"
        "{s        |       | Separation between two consecutive markers in the grid (in pixels)}"
        "{d        |       | dictionary: DICT_4X4_50=0, DICT_4X4_100=1, DICT_4X4_250=2,"
        "DICT_4X4_1000=3, DICT_5X5_50=4, DICT_5X5_100=5, DICT_5X5_250=6, DICT_5X5_1000=7, "
        "DICT_6X6_50=8, DICT_6X6_100=9, DICT_6X6_250=10, DICT_6X6_1000=11, DICT_7X7_50=12,"
        "DICT_7X7_100=13, DICT_7X7_250=14, DICT_7X7_1000=15, DICT_ARUCO_ORIGINAL = 16}"
        "{c        |       | Output file with calibrated camera parameters }"
        "{v        |       | Input from video file, if ommited, input comes from camera }"
        "{ci       | 0     | Camera id if input doesnt come from video (-v) }"
        "{dp       |       | File of marker detector parameters }"
        "{rs       |       | Apply refind strategy }"
        "{r        |       | show rejected candidates too }";
}

/**
 */
static bool readCameraParameters(string filename, Mat &camMatrix, Mat &distCoeffs) {
    FileStorage fs(filename, FileStorage::READ);
    if(!fs.isOpened())
        return false;
    fs["camera_matrix"] >> camMatrix;
    fs["distortion_coefficients"] >> distCoeffs;
    return true;
}



/**
 */
static bool readDetectorParameters(string filename, Ptr<aruco::DetectorParameters> &params) {
    FileStorage fs(filename, FileStorage::READ);
    if(!fs.isOpened())
        return false;
    fs["adaptiveThreshWinSizeMin"] >> params->adaptiveThreshWinSizeMin;
    fs["adaptiveThreshWinSizeMax"] >> params->adaptiveThreshWinSizeMax;
    fs["adaptiveThreshWinSizeStep"] >> params->adaptiveThreshWinSizeStep;
    fs["adaptiveThreshConstant"] >> params->adaptiveThreshConstant;
    fs["minMarkerPerimeterRate"] >> params->minMarkerPerimeterRate;
    fs["maxMarkerPerimeterRate"] >> params->maxMarkerPerimeterRate;
    fs["polygonalApproxAccuracyRate"] >> params->polygonalApproxAccuracyRate;
    fs["minCornerDistanceRate"] >> params->minCornerDistanceRate;
    fs["minDistanceToBorder"] >> params->minDistanceToBorder;
    fs["minMarkerDistanceRate"] >> params->minMarkerDistanceRate;
    fs["cornerRefinementMethod"] >> params->cornerRefinementMethod;
    fs["cornerRefinementWinSize"] >> params->cornerRefinementWinSize;
    fs["cornerRefinementMaxIterations"] >> params->cornerRefinementMaxIterations;
    fs["cornerRefinementMinAccuracy"] >> params->cornerRefinementMinAccuracy;
    fs["markerBorderBits"] >> params->markerBorderBits;
    fs["perspectiveRemovePixelPerCell"] >> params->perspectiveRemovePixelPerCell;
    fs["perspectiveRemoveIgnoredMarginPerCell"] >> params->perspectiveRemoveIgnoredMarginPerCell;
    fs["maxErroneousBitsInBorderRate"] >> params->maxErroneousBitsInBorderRate;
    fs["minOtsuStdDev"] >> params->minOtsuStdDev;
    fs["errorCorrectionRate"] >> params->errorCorrectionRate;
    return true;
}


/**
 */
int main(int argc, char *argv[]) {
    CommandLineParser parser(argc, argv, keys);
    parser.about(about);

    if(argc < 7) {
        parser.printMessage();
        return 0;
    }

    int markersX = parser.get<int>("w");
    int markersY = parser.get<int>("h");
    float markerLength = parser.get<float>("l");
    float markerSeparation = parser.get<float>("s");
    int dictionaryId = parser.get<int>("d");
    bool showRejected = parser.has("r");
    bool refindStrategy = parser.has("rs");
    int camId = parser.get<int>("ci");


    Mat camMatrix, distCoeffs;
    if(parser.has("c")) {
        bool readOk = readCameraParameters(parser.get<string>("c"), camMatrix, distCoeffs);
        if(!readOk) {
            cerr << "Invalid camera file" << endl;
            return 0;
        }
    }

    Ptr<aruco::DetectorParameters> detectorParams = aruco::DetectorParameters::create();
    if(parser.has("dp")) {
        bool readOk = readDetectorParameters(parser.get<string>("dp"), detectorParams);
        if(!readOk) {
            cerr << "Invalid detector parameters file" << endl;
            return 0;
        }
    }
    detectorParams->cornerRefinementMethod = aruco::CORNER_REFINE_SUBPIX; // do corner refinement in markers

    String video;
    if(parser.has("v")) {
        video = parser.get<String>("v");
    }

    if(!parser.check()) {
        parser.printErrors();
        return 0;
    }

    Ptr<aruco::Dictionary> dictionary =
        aruco::getPredefinedDictionary(aruco::PREDEFINED_DICTIONARY_NAME(dictionaryId));

    VideoCapture inputVideo;
    int waitTime;
    if(!video.empty()) {
        inputVideo.open(video);
        waitTime = 0;
    } else {
        inputVideo.open(camId);
        waitTime = 10;
    }

    float axisLength = 0.5f * ((float)min(markersX, markersY) * (markerLength + markerSeparation) +
                               markerSeparation);

    // create board object
    Ptr<aruco::GridBoard> gridboard =
        aruco::GridBoard::create(markersX, markersY, markerLength, markerSeparation, dictionary);
    Ptr<aruco::Board> board = gridboard.staticCast<aruco::Board>();

    double totalTime = 0;
    int totalIterations = 0;

    while(inputVideo.grab()) {
        Mat image, imageCopy;
        inputVideo.retrieve(image);

        double tick = (double)getTickCount();

        vector< int > ids;
        vector< vector< Point2f > > corners, rejected;
        Vec3d rvec, tvec;

        // detect markers
        aruco::detectMarkers(image, dictionary, corners, ids, detectorParams, rejected);

        // refind strategy to detect more markers
        if(refindStrategy)
            aruco::refineDetectedMarkers(image, board, corners, ids, rejected, camMatrix,
                                         distCoeffs);

        // estimate board pose
        int markersOfBoardDetected = 0;
        if(ids.size() > 0)
            markersOfBoardDetected =
                aruco::estimatePoseBoard(corners, ids, board, camMatrix, distCoeffs, rvec, tvec);

        double currentTime = ((double)getTickCount() - tick) / getTickFrequency();
        totalTime += currentTime;
        totalIterations++;
        if(totalIterations % 30 == 0) {
            cout << "Detection Time = " << currentTime * 1000 << " ms "
                 << "(Mean = " << 1000 * totalTime / double(totalIterations) << " ms)" << endl;
        }

        // draw results
        image.copyTo(imageCopy);
        if(ids.size() > 0) {
            aruco::drawDetectedMarkers(imageCopy, corners, ids);
        }

        if(showRejected && rejected.size() > 0)
            aruco::drawDetectedMarkers(imageCopy, rejected, noArray(), Scalar(100, 0, 255));

        if(markersOfBoardDetected > 0)
            aruco::drawAxis(imageCopy, camMatrix, distCoeffs, rvec, tvec, axisLength);

        imshow("out", imageCopy);
        char key = (char)waitKey(waitTime);
        if(key == 27) break;
    }

    return 0;
}
