code_device/hgdriver/ImageProcess/ImageApplyDogEarDetection.cpp

#include "ImageApplyDogEarDetection.h"
#include "ImageProcess_Public.h"

CImageApplyDogEarDetection::CImageApplyDogEarDetection()
    : m_threshold(40)
    , m_zoom_x(1.0)
    , m_zoom_y(1.0)
    , m_distance1(50)
    , m_distance2(50)
    , m_result(0)
{

}

CImageApplyDogEarDetection::CImageApplyDogEarDetection(double threshlod, double zoom_x, double zoom_y, double distance1, double distance2)
    : m_threshold(threshlod)
    , m_zoom_x(zoom_x)
    , m_zoom_y(zoom_y)
    , m_distance1(distance1)
    , m_distance2(distance2)
    , m_result(0)
{

}

CImageApplyDogEarDetection::~CImageApplyDogEarDetection()
{

}

#define EDGE_ABS 4
void CImageApplyDogEarDetection::apply(cv::Mat& pDib, int side)
{
    m_result = 0;
    (void)side;
    if (pDib.empty()) return;
    cv::Mat src;
    if (m_zoom_x != 1.0 && m_zoom_y != 1.0)
        cv::resize(pDib, src, cv::Size(), m_zoom_x, m_zoom_y, cv::INTER_NEAREST);
    else
        src = pDib;

    cv::Mat thre;
    hg::threshold_Mat(src, thre, m_threshold);

    cv::Mat element = getStructuringElement(cv::MORPH_RECT, cv::Size(5, 1));
    cv::morphologyEx(thre, thre, cv::MORPH_OPEN, element, cv::Point(-1, -1), 1, cv::BORDER_CONSTANT, cv::Scalar::all(0));

    std::vector<cv::Vec4i> hierarchy;
    std::vector<std::vector<cv::Point>> contours;
    hg::findContours(thre, contours, hierarchy, cv::RETR_EXTERNAL);

    std::vector<cv::Point> maxContour = hg::getMaxContour(contours, hierarchy);
    if (maxContour.size() == 0)
    {
        m_result = true;
        return;
    }
    hg::convexHull(maxContour, maxContour);
    cv::RotatedRect rect = hg::getBoundingRect(maxContour);
    cv::Point2f vertexes[4];
    rect.points(vertexes);

    double distance;
    for (int i = 0; i < 4; i++)
    {
        distance = -cv::pointPolygonTest(maxContour, vertexes[i], true);

        //<2F>ж<EFBFBD><D0B6>Ƿ<EFBFBD>Ϊ<EFBFBD><CEAA>ͨ<EFBFBD>۽<EFBFBD>
        if (distance > (m_distance1 / m_zoom_x))
        {
            if (cv::Rect(0, 0, src.cols, src.rows).contains(vertexes[i]))
                m_result = 1;
            else if (vertexes[i].x < 0 && cv::abs(distance + vertexes[i].x) > EDGE_ABS)   //<2F><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>Խ<EFBFBD><D4BD><EFBFBD>۽ǣ<DBBD><C7A3>޸<EFBFBD>m_resultֵ<74><D6B5><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>Ҫ<EFBFBD><D2AA><EFBFBD><EFBFBD><EFBFBD>жϣ<D0B6><CFA3><EFBFBD>ֹ©<D6B9><C2A9><EFBFBD><EFBFBD>ͨ<EFBFBD>۽<EFBFBD>
                m_result = 1;
            else if (vertexes[i].y < 0 && cv::abs(distance + vertexes[i].y) > EDGE_ABS)
                m_result = 1;
            else if (vertexes[i].x > src.cols && cv::abs(distance + src.cols - vertexes[i].x) > EDGE_ABS)
                m_result = 1;
            else if (vertexes[i].y > src.rows && cv::abs(distance + src.rows - vertexes[i].y) > EDGE_ABS)
                m_result = 1;
        }

        if (m_result == 1)
            return;

        //<2F>ж<EFBFBD><D0B6>Ƿ<EFBFBD>Ϊɨ<CEAA><C9A8>Խ<EFBFBD>絼<EFBFBD>µ<EFBFBD><C2B5>۽<EFBFBD>
        if (distance > (m_distance2 / m_zoom_x))
        {
            if (vertexes[i].x < 0 && cv::abs(distance + vertexes[i].x) < EDGE_ABS)   //<2F><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>Խ<EFBFBD><D4BD><EFBFBD>۽ǣ<DBBD><C7A3>޸<EFBFBD>m_resultֵ<74><D6B5><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>Ҫ<EFBFBD><D2AA><EFBFBD><EFBFBD><EFBFBD>жϣ<D0B6><CFA3><EFBFBD>ֹ©<D6B9><C2A9><EFBFBD><EFBFBD>ͨ<EFBFBD>۽<EFBFBD>
                m_result = 2;
            else if (vertexes[i].y < 0 && cv::abs(distance + vertexes[i].y) < EDGE_ABS)
                m_result = 2;
            else if (vertexes[i].x > src.cols && cv::abs(distance + src.cols - vertexes[i].x) < EDGE_ABS)
                m_result = 2;
            else if (vertexes[i].y > src.rows && cv::abs(distance + src.rows - vertexes[i].y) < EDGE_ABS)
                m_result = 2;
        }
    }
}

void CImageApplyDogEarDetection::apply(std::vector<cv::Mat>& mats, bool isTwoSide)
{
    (void)mats;
    (void)isTwoSide;
}