/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
 * Copyright 2012 The MITRE Corporation                                      *
 *                                                                           *
 * Licensed under the Apache License, Version 2.0 (the "License");           *
 * you may not use this file except in compliance with the License.          *
 * You may obtain a copy of the License at                                   *
 *                                                                           *
 *     http://www.apache.org/licenses/LICENSE-2.0                            *
 *                                                                           *
 * Unless required by applicable law or agreed to in writing, software       *
 * distributed under the License is distributed on an "AS IS" BASIS,         *
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.  *
 * See the License for the specific language governing permissions and       *
 * limitations under the License.                                            *
 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */

#include <opencv2/imgproc/imgproc.hpp>
#include <openbr_plugin.h>

using namespace cv;
using namespace br;

/*!
 * \ingroup transforms
 * \brief Applies an eliptical mask
 * \author Josh Klontz \cite jklontz
 */
class Mask : public UntrainableTransform
{
    Q_OBJECT

    void project(const Template &src, Template &dst) const
    {
        const Mat &m = src;
        Mat mask(m.size(), CV_8UC1);
        mask.setTo(1);
        const float SCALE = 1.1;
        ellipse(mask, RotatedRect(Point2f(m.cols/2, m.rows/2), Size2f(SCALE*m.cols, SCALE*m.rows), 0), 0, -1);
        dst = m.clone();
        dst.m().setTo(0, mask);
    }
};

BR_REGISTER(Transform, Mask)

/*!
 * \ingroup transforms
 * \brief Masks image according to pixel change.
 * \author Josh Klontz \cite jklontz
 */
class GradientMask : public UntrainableTransform
{
    Q_OBJECT
    Q_PROPERTY(int delta READ get_delta WRITE set_delta RESET reset_delta STORED false)
    BR_PROPERTY(int, delta, 1)

    void project(const Template &src, Template &dst) const
    {
        const Mat &m = src.m();
        if (m.type() != CV_8UC1) qFatal("GradientMask operates on 8UC1 matrices.");
        Mat n = Mat(m.rows, m.cols, CV_8UC1);
        n.setTo(255);
        for (int i=0; i<m.rows; i++) {
            for (int j=0; j<m.cols; j++) {
                if ((i>0)        && (abs(m.at<quint8>(i-1,j)-m.at<quint8>(i,j)) > delta)) { n.at<quint8>(i,j) = 0; continue; }
                if ((j+1<m.cols) && (abs(m.at<quint8>(i,j+1)-m.at<quint8>(i,j)) > delta)) { n.at<quint8>(i,j) = 0; continue; }
                if ((i+1<m.rows) && (abs(m.at<quint8>(i+1,j)-m.at<quint8>(i,j)) > delta)) { n.at<quint8>(i,j) = 0; continue; }
                if ((j>0)        && (abs(m.at<quint8>(i,j-1)-m.at<quint8>(i,j)) > delta)) { n.at<quint8>(i,j) = 0; continue; }
            }
        }
        dst = n;
    }
};

BR_REGISTER(Transform, GradientMask)

/*!
 * \ingroup transforms
 * \brief http://worldofcameras.wordpress.com/tag/skin-detection-opencv/
 * \author Josh Klontz \cite jklontz
 */
class SkinMask : public UntrainableTransform
{
    Q_OBJECT

    void project(const Template &src, Template &dst) const
    {
        Mat m;
        cvtColor(src, m, CV_BGR2YCrCb);
        std::vector<Mat> mv;
        split(m, mv);
        Mat mask = Mat(m.rows, m.cols, CV_8UC1);

        for (int i=0; i<m.rows; i++) {
            for (int j=0; j<m.cols; j++) {
                int Cr= mv[1].at<quint8>(i,j);
                int Cb =mv[2].at<quint8>(i,j);
                mask.at<quint8>(i, j) = (Cr>130 && Cr<170) && (Cb>70 && Cb<125) ? 255 : 0;
            }
        }

        dst = mask;
    }
};

BR_REGISTER(Transform, SkinMask)

/*!
 * \ingroup transforms
 * \brief Morphological operator
 * \author Josh Klontz \cite jklontz
 */
class Morph : public UntrainableTransform
{
    Q_OBJECT
    Q_ENUMS(Op)
    Q_PROPERTY(Op op READ get_op WRITE set_op RESET reset_op STORED false)
    Q_PROPERTY(int radius READ get_radius WRITE set_radius RESET reset_radius STORED false)

public:
    /*!< */
    enum Op { Erode = MORPH_ERODE,
              Dilate = MORPH_DILATE,
              Open = MORPH_OPEN,
              Close = MORPH_CLOSE,
              Gradient = MORPH_GRADIENT,
              TopHat = MORPH_TOPHAT,
              BlackHat = MORPH_BLACKHAT };

private:
    BR_PROPERTY(Op, op, Close)
    BR_PROPERTY(int, radius, 1)

    Mat kernel;

    void init()
    {
        Mat kernel = Mat(radius, radius, CV_8UC1);
        kernel.setTo(255);
    }

    void project(const Template &src, Template &dst) const
    {
        morphologyEx(src, dst, op, kernel);
    }
};

BR_REGISTER(Transform, Morph)

/*!
 * \ingroup transforms
 * \brief Set the template's label to the area of the largest convex hull.
 * \author Josh Klontz \cite jklontz
 */
class LargestConvexArea : public UntrainableTransform
{
    Q_OBJECT

    void project(const Template &src, Template &dst) const
    {
        std::vector< std::vector<Point> > contours;
        findContours(src.clone(), contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);
        double maxArea = 0;
        foreach (const std::vector<Point> &contour, contours) {
            std::vector<Point> hull;
            convexHull(contour, hull);
            double area = contourArea(contour);
            double hullArea = contourArea(hull);
            if (area / hullArea > 0.98)
                maxArea = std::max(maxArea, area);
        }
        dst.file.setLabel(maxArea);
    }
};

BR_REGISTER(Transform, LargestConvexArea)

#include "mask.moc"