C++ OutputArray::getMat方法代码示例

/**
 * @brief Compute derivative kernels for sizes different than 3
 * @param _kx Horizontal kernel ues
 * @param _ky Vertical kernel values
 * @param dx Derivative order in X-direction (horizontal)
 * @param dy Derivative order in Y-direction (vertical)
 * @param scale_ Scale factor or derivative size
 */
void compute_derivative_kernels(cv::OutputArray _kx, cv::OutputArray _ky, int dx, int dy, int scale) {

    int ksize = 3 + 2 * (scale - 1);

    // The standard Scharr kernel
    if (scale == 1) {
        getDerivKernels(_kx, _ky, dx, dy, 0, true, CV_32F);
        return;
    }

    _kx.create(ksize, 1, CV_32F, -1, true);
    _ky.create(ksize, 1, CV_32F, -1, true);
    Mat kx = _kx.getMat();
    Mat ky = _ky.getMat();

    float w = 10.0f / 3.0f;
    float norm = 1.0f / (2.0f*scale*(w + 2.0f));

    for (int k = 0; k < 2; k++) {
        Mat* kernel = k == 0 ? &kx : &ky;
        int order = k == 0 ? dx : dy;
        std::vector<float> kerI(ksize, 0.0f);

        if (order == 0) {
            kerI[0] = norm, kerI[ksize / 2] = w*norm, kerI[ksize - 1] = norm;
        }
        else if (order == 1) {
            kerI[0] = -1, kerI[ksize / 2] = 0, kerI[ksize - 1] = 1;
        }

        Mat temp(kernel->rows, kernel->cols, CV_32F, &kerI[0]);
        temp.copyTo(*kernel);
    }
}

void stereo::stereoRectify(cv::InputArray _K1, cv::InputArray _K2, cv::InputArray _R, cv::InputArray _T,
                           cv::OutputArray _R1, cv::OutputArray _R2, cv::OutputArray _P1, cv::OutputArray _P2)
{
    Mat K1 = _K1.getMat(), K2 = _K2.getMat(), R = _R.getMat(), T = _T.getMat();
    _R1.create(3, 3, CV_32F);
    _R2.create(3, 3, CV_32F);
    Mat R1 = _R1.getMat();
    Mat R2 = _R2.getMat();
    _P1.create(3, 4, CV_32F);
    _P2.create(3, 4, CV_32F);
    Mat P1 = _P1.getMat();
    Mat P2 = _P2.getMat();

    if(K1.type()!=CV_32F)
        K1.convertTo(K1,CV_32F);
    if(K2.type()!=CV_32F)
        K2.convertTo(K2,CV_32F);
    if(R.type()!=CV_32F)
        R.convertTo(R,CV_32F);
    if(T.type()!=CV_32F)
        T.convertTo(T,CV_32F);
    if(T.rows != 3)
        T = T.t();

    // R and T is the transformation from the first to the second camera
    // Get the transformation from the second to the first camera
    Mat R_inv = R.t();
    Mat T_inv = -R.t()*T;

    Mat e1, e2, e3;
    e1 = T_inv.t() / norm(T_inv);
    /*Mat z = (Mat_<float>(1, 3) << 0.0,0.0,-1.0);
    e2 = e1.cross(z);
    e2 = e2 / norm(e2);*/
    e2 = (Mat_<float>(1,3) << T_inv.at<float>(1)*-1, T_inv.at<float>(0), 0.0 );
    e2 = e2 / (sqrt(e2.at<float>(0)*e2.at<float>(0) + e2.at<float>(1)*e2.at<float>(1)));
    e3 = e1.cross(e2);
    e3 = e3 / norm(e3);
    e1.copyTo(R1.row(0));
    e2.copyTo(R1.row(1));
    e3.copyTo(R1.row(2));
    R2 = R_inv * R1;

    P1.setTo(Scalar(0));
    R1.copyTo(P1.colRange(0, 3));
    P1 = K1 * P1;

    P2.setTo(Scalar(0));
    R2.copyTo(P2.colRange(0, 3));
    P2 = K2 * P2;

}

  /**
   * Get the average image at the given altitude.
   * If the altitude is not located exactly at one of the altitude bins,
   * the average image is interpolated between any overlapping bins.
   * @param _dst the output image (zeros at desired resolution)
   * @param alt the altitude the image was taken at
   * @param pitch the pitch of the vehicle
   * @param roll the roll of the vehicle
   */
  void getAverage(cv::OutputArray _dst, double alt, double pitch, double roll) {
    Mat dst = _dst.getMat();
    int width = dst.size().width;
    int height = dst.size().height;
    Mat D = Mat::zeros(height, width, CV_32F);
    double width_m = width * cameras.pixel_sep;
    double height_m = height * cameras.pixel_sep;
    interp::distance_map(D, alt, pitch, roll, width_m, height_m, cameras.focal_length);
    // now discretize into slices
    int i = 0;
    Mat W = Mat::zeros(D.size(), CV_32F);
    while(cv::countNonZero(W) == 0) {
      interp::dist_weight(D, W, alt_step, i++);
    }
    while(cv::countNonZero(W) > 0) {
      Slice<int>* slice = getSlice(i);
      Mat sAverage;
      // get the slice average
      boost::mutex* mutex = slice->get_mutex();
      { // protect slice with mutex to prevent interleaved read/write operations
	boost::lock_guard<boost::mutex> lock(*mutex);
	sAverage = slice->getLightfield()->getAverage();
      }
      dst += sAverage.mul(W); // multiply by slice weight
      interp::dist_weight(D, W, alt_step, i++);
    }
  }

void stereo_disparity_normal(cv::InputArray left_image, cv::InputArray right_image, cv::OutputArray disp_, 
					  int max_dis_level, int scale, float sigma) {
	cv::Mat imL = left_image.getMat();
	cv::Mat imR = right_image.getMat();
	
	CV_Assert(imL.size() == imR.size());
	CV_Assert(imL.type() == CV_8UC3 && imR.type() == CV_8UC3);

	cv::Size imageSize = imL.size();

	disp_.create(imageSize, CV_8U);
	cv::Mat disp = disp_.getMat();
	
	CDisparityHelper dispHelper;
	
//step 1: cost initialization
	cv::Mat costVol = dispHelper.GetMatchingCost(imL, imR, max_dis_level);

//step 2: cost aggregation
	CSegmentTree stree;
	CColorWeight cWeight(imL);
	stree.BuildSegmentTree(imL.size(), sigma, TAU, cWeight);
	stree.Filter(costVol, max_dis_level);

//step 3: disparity computation
	cv::Mat disparity = dispHelper.GetDisparity_WTA((float*)costVol.data, 
		imageSize.width, imageSize.height, max_dis_level);

	MeanFilter(disparity, disparity, 3);

	disparity *= scale;
	disparity.copyTo(disp);
}

void EdgeDetector_<ParallelUtils::eGLSL>::getLatestEdgeMask(cv::OutputArray _oLastEdgeMask) {
    _oLastEdgeMask.create(m_oFrameSize,CV_8UC1);
    cv::Mat oLastEdgeMask = _oLastEdgeMask.getMat();
    if(!GLImageProcAlgo::m_bFetchingOutput)
    glAssert(GLImageProcAlgo::setOutputFetching(true))
    GLImageProcAlgo::fetchLastOutput(oLastEdgeMask);
}

void textureFlattening(cv::InputArray _src,
                       cv::InputArray _mask,
                       cv::OutputArray _dst,
                       double low_threshold,
                       double high_threshold,
                       int kernel_size)
{

    Mat src  = _src.getMat();
    Mat mask  = _mask.getMat();
    _dst.create(src.size(), src.type());
    Mat blend = _dst.getMat();

    Mat gray = Mat::zeros(mask.size(), CV_8UC1);

    if(mask.channels() == 3)
        cvtColor(mask, gray, COLOR_BGR2GRAY);
    else
        gray = mask;

    Mat cs_mask = Mat::zeros(src.size(), CV_8UC3);

    src.copyTo(cs_mask, gray);

    Cloning obj;
    obj.texture_flatten(src, cs_mask, gray, low_threshold, high_threshold, kernel_size, blend);
}

void illuminationChange(cv::InputArray _src,
                        cv::InputArray _mask,
                        cv::OutputArray _dst,
                        float a,
                        float b)
{

    Mat src  = _src.getMat();
    Mat mask  = _mask.getMat();
    _dst.create(src.size(), src.type());
    Mat blend = _dst.getMat();
    float alpha = a;
    float beta = b;

    Mat gray = Mat::zeros(mask.size(), CV_8UC1);

    if(mask.channels() == 3)
        cvtColor(mask, gray, COLOR_BGR2GRAY);
    else
        gray = mask;

    Mat cs_mask = Mat::zeros(src.size(), CV_8UC3);

    src.copyTo(cs_mask, gray);

    Cloning obj;
    obj.illum_change(src, cs_mask, gray, blend, alpha, beta);

}

void colorChange(cv::InputArray _src,
                 cv::InputArray _mask,
                 cv::OutputArray _dst,
                 float r,
                 float g,
                 float b)
{
    Mat src  = _src.getMat();
    Mat mask  = _mask.getMat();
    _dst.create(src.size(), src.type());
    Mat blend = _dst.getMat();

    float red = r;
    float green = g;
    float blue = b;

    Mat gray = Mat::zeros(mask.size(), CV_8UC1);

    if(mask.channels() == 3)
        cvtColor(mask, gray, COLOR_BGR2GRAY);
    else
        gray = mask;

    Mat cs_mask = Mat::zeros(src.size(), CV_8UC3);

    src.copyTo(cs_mask, gray);

    Cloning obj;
    obj.local_color_change(src, cs_mask, gray, blend, red, green, blue);
}

    void BackgroundSubtractorMedian::operator()(cv::InputArray _image, cv::OutputArray _fgmask, double learningRate)
    {
	framecount++;
	cv::Mat image = _image.getMat();
	if (image.channels() > 1) {
	    cvtColor(image,image,CV_BGR2GRAY);
	}
	if (image.cols == 0 || image.rows == 0) {
	    return;
	}
	_fgmask.create(image.size(), CV_8U);
	cv::Mat fgmask = _fgmask.getMat();
	if (!init)
	{
	    init = true;
	    bgmodel = cv::Mat(image.size(), CV_8U);
	}
	//printf("(%d,%d)(%d) ",image.cols,image.rows,image.type());
	//printf("(%d,%d)(%d)\n",bgmodel.cols,bgmodel.rows,bgmodel.type());

	cv::Mat cmpArr = cv::Mat(image.size(),CV_8U);
	cv::compare(image, bgmodel, cmpArr, CV_CMP_GT);
	cv::bitwise_and(cmpArr, 1, cmpArr);
	cv::add(bgmodel, cmpArr, bgmodel);

	cmpArr = cv::Mat(image.size(),CV_8U);
	cv::compare(image, bgmodel, cmpArr, CV_CMP_LT);
	cv::bitwise_and(cmpArr, 1, cmpArr);
	cv::subtract(bgmodel, cmpArr, bgmodel);

	cv::absdiff(image, bgmodel,fgmask);
	cv::threshold(fgmask,fgmask,fg_threshold,255,CV_THRESH_TOZERO);
	cv::medianBlur(fgmask,fgmask,median_filter_level);
    }

int boostColor(cv::InputArray src, cv::OutputArray dst, float intensity)
{
    const int MAX_INTENSITY = 255;

    Mat srcImg = src.getMat();

    CV_Assert(srcImg.channels() == 3);
    CV_Assert(intensity >= 0.0f && intensity <= 1.0f);

    if (srcImg.type() != CV_8UC3)
    {
        srcImg.convertTo(srcImg, CV_8UC3);
    }

    Mat srcHls;
    cvtColor(srcImg, srcHls, CV_BGR2HLS);
    
    int intensityInt = intensity * MAX_INTENSITY;
    srcHls += Scalar(0, 0, intensityInt);
    
    cvtColor(srcHls, dst, CV_HLS2BGR);
    
    dst.getMat().convertTo(dst, srcImg.type());
    return 0;
}

void IBackgroundSubtractor_GLSL::getLatestForegroundMask(cv::OutputArray _oLastFGMask) {
    _oLastFGMask.create(m_oImgSize,CV_8UC1);
    cv::Mat oLastFGMask = _oLastFGMask.getMat();
    glAssert(GLImageProcAlgo::m_bFetchingOutput || GLImageProcAlgo::setOutputFetching(true))
    if(GLImageProcAlgo::m_nInternalFrameIdx>0)
        GLImageProcAlgo::fetchLastOutput(oLastFGMask);
    else
        oLastFGMask = cv::Scalar_<uchar>(0);
}

void sadTemplate(cv::InputArray tar, cv::InputArray tmp, cv::OutputArray res, int *minx, int *miny){
	//引数の入力をMatとして受け取る
	cv::Mat tarM = tar.getMat();	
	cv::Mat tmpM = tmp.getMat();
	cv::Mat resM = res.getMat();

	//sadが最小値のところがマッチングしたい箇所なので
	int minsad = std::numeric_limits<int>::max();	
	int sad = 0;  //各回のsadを格納
	int diff;	//sadに加算する前の作業変数
	int tarx,tary;	//目的のxy座標


	for(int y=0;y<tarM.rows - tmpM.rows;y++){
		for(int x=0;x<tarM.cols - tmpM.cols;x++){
			sad = 0;	//次の領域の計算の前に初期化
			//探索
			for(int yt = 0; yt < tmpM.rows; yt++){
				for(int xt = 0; xt < tmpM.cols; xt++){
					diff = (int)(tarM.at<uchar>(y+yt,x+xt) - tmpM.at<uchar>(yt,xt));
					if(diff < 0){  //負なら正に変換
						diff = -diff;
					}
					sad += diff;
					////残差逐次検定法
					if(sad > minsad){
						yt = tmpM.rows;	
						break;
					}
				}
			}

			//探索結果：sadが今までで最小なら
			if(sad < minsad){
				minsad = sad;	//最小値を更新
				//目的のxyを格納
				tarx = x;
				tary = y;
			}
		}
	}

	//outputに出力
	for(int y=0;y<resM.rows;y++){
		for(int x=0;x<resM.cols;x++){
			if(x==tarx && y==tary){
				resM.at<uchar>(y,x) = (uchar)0;
			}else{
				resM.at<uchar>(y,x) = (uchar)255;
			}
		}
	}
	std::cout << "最小値＝" << minsad << std::endl;
	std::cout << "最小点＝[" << tarx << ", " << tary << "]" <<  std::endl;
	*minx = tarx;
	*miny = tary;
}

bool OpenNI2Grabber::grabFrame(cv::OutputArray _color) {
  if (_color.kind() != cv::_InputArray::MAT)
    BOOST_THROW_EXCEPTION(GrabberException("Grabbing only into cv::Mat"));

  _color.create(p->color_image_resolution.height, p->color_image_resolution.width, CV_8UC3);
  cv::Mat color = _color.getMat();

  return p->grabFrame(color);
}

void BackgroundSubtractor_<ParallelUtils::eGLSL>::getLatestForegroundMask(cv::OutputArray _oLastFGMask) {
    _oLastFGMask.create(m_oImgSize,CV_8UC1);
    cv::Mat oLastFGMask = _oLastFGMask.getMat();
    if(!GLImageProcAlgo::m_bFetchingOutput)
    glAssert(GLImageProcAlgo::setOutputFetching(true))
    else if(m_nFrameIdx>0)
        GLImageProcAlgo::fetchLastOutput(oLastFGMask);
    else
        oLastFGMask = cv::Scalar_<uchar>(0);
}

void IEdgeDetector_GLSL::getLatestEdgeMask(cv::OutputArray _oLastEdgeMask) {
    lvAssert_(GLImageProcAlgo::m_bGLInitialized,"algo must be initialized first");
    _oLastEdgeMask.create(GLImageProcAlgo::m_oFrameSize,CV_8UC1);
    cv::Mat oLastEdgeMask = _oLastEdgeMask.getMat();
    lvAssert_(GLImageProcAlgo::m_bFetchingOutput || GLImageProcAlgo::setOutputFetching(true),"algo not initialized with mat output support")
    if(GLImageProcAlgo::m_nInternalFrameIdx>0)
        GLImageProcAlgo::fetchLastOutput(oLastEdgeMask);
    else
        oLastEdgeMask = cv::Scalar_<uchar>(0);
}