C++ InputArray::type方法代码示例

RadiometricResponse::RadiometricResponse(cv::InputArray _response, ChannelOrder order) : order_(order) {
  if (_response.size().width != 256 || _response.size().height != 1)
    BOOST_THROW_EXCEPTION(RadiometricResponseException("Radiometric response should have 1 x 256 size")
                          << RadiometricResponseException::Size(_response.size()));
  if (_response.type() != CV_32FC3)
    BOOST_THROW_EXCEPTION(RadiometricResponseException("Radiometric response values should be 3-channel float")
                          << RadiometricResponseException::Type(_response.type()));
  response_ = _response.getMat();
  cv::log(response_, log_response_);
  cv::split(response_, response_channels_);
}

void IPPE::PoseSolver::solveGeneric(cv::InputArray _objectPoints, cv::InputArray _normalizedInputPoints,
                                    cv::OutputArray _Ma, cv::OutputArray _Mb)
{

    //argument checking:
    size_t n = _objectPoints.rows() * _objectPoints.cols(); //number of points
    int objType = _objectPoints.type();
    int type_input = _normalizedInputPoints.type();
    assert((objType == CV_32FC3) | (objType == CV_64FC3));
    assert((type_input == CV_32FC2) | (type_input == CV_64FC2));
    assert((_objectPoints.rows() == 1) | (_objectPoints.cols() == 1));
    assert((_objectPoints.rows() >= 4) | (_objectPoints.cols() >= 4));
    assert((_normalizedInputPoints.rows() == 1) | (_normalizedInputPoints.cols() == 1));
    assert(static_cast<size_t>(_objectPoints.rows() * _objectPoints.cols()) == n);

    cv::Mat normalizedInputPoints;
    if (type_input == CV_32FC2) {
        _normalizedInputPoints.getMat().convertTo(normalizedInputPoints, CV_64FC2);
    }
    else {
        normalizedInputPoints = _normalizedInputPoints.getMat();
    }

    cv::Mat objectInputPoints;
    if (type_input == CV_32FC3) {
        _objectPoints.getMat().convertTo(objectInputPoints, CV_64FC3);
    }
    else {
        objectInputPoints = _objectPoints.getMat();
    }

    cv::Mat canonicalObjPoints;
    cv::Mat MmodelPoints2Canonical;

    //transform object points to the canonical position (zero centred and on the plane z=0):
    makeCanonicalObjectPoints(objectInputPoints, canonicalObjPoints, MmodelPoints2Canonical);

    //compute the homography mapping the model's points to normalizedInputPoints
    cv::Mat H;
    HomographyHO::homographyHO(canonicalObjPoints, _normalizedInputPoints, H);

    //now solve
    cv::Mat MaCanon, MbCanon;
    solveCanonicalForm(canonicalObjPoints, normalizedInputPoints, H, MaCanon, MbCanon);

    //transform computed poses to account for canonical transform:
    cv::Mat Ma = MaCanon * MmodelPoints2Canonical;
    cv::Mat Mb = MbCanon * MmodelPoints2Canonical;

    //output poses:
    Ma.copyTo(_Ma);
    Mb.copyTo(_Mb);
}

void showWindow(const string &winName, cv::InputArray mat)
{
	Mat temp(mat.size(), mat.type());
	mat.getMat().copyTo(temp);
	namedWindow(winName, WINDOW_NORMAL); // Create a window for display.
	imshow(winName, temp); // Show our image inside it.
}

void Regression::write(cv::InputArray array)
{
    write() << "kind" << array.kind();
    write() << "type" << array.type();
    if (isVector(array))
    {
        int total = (int)array.total();
        int idx = regRNG.uniform(0, total);
        write() << "len" << total;
        write() << "idx" << idx;

        cv::Mat m = array.getMat(idx);

        if (m.total() * m.channels() < 26) //5x5 or smaller
            write() << "val" << m;
        else
            write(m);
    }
    else
    {
        if (array.total() * array.channels() < 26) //5x5 or smaller
            write() << "val" << array.getMat();
        else
            write(array.getMat());
    }
}

void warmify(cv::InputArray src, cv::OutputArray dst, uchar delta)
{
    CV_Assert(src.type() == CV_8UC3);
    Mat imgSrc = src.getMat();
    CV_Assert(imgSrc.data);
    dst.create(src.size(), CV_8UC3);
    Mat imgDst = dst.getMat();

    imgDst = imgSrc + Scalar(0, delta, delta);
}

  void FilterBase::apply(cv::InputArray _src, cv::OutputArray _dst, const int &ddepth){
    int stype = _src.type();
    int dcn = _src.channels();
    int depth = CV_MAT_DEPTH(stype);

    if (0 <= ddepth)
      depth = ddepth;

    Mat src, dst;
    src = _src.getMat();

    Size sz = src.size();

    _dst.create(sz, CV_MAKETYPE(depth, dcn));
    dst = _dst.getMat();

    int imageWidth = src.rows;
    int imageHeight = src.cols;

    Mat srcChannels[3];
    split(src, srcChannels);

    int margineWidth = kernel.cols / 2;
    int margineHeight = kernel.rows / 2;
    double kernelElemCount = (double)(kernel.cols * kernel.rows);

    for(int ch = 0; ch < dcn; ++ch){
      for(int y = 0; y < imageHeight; ++y){
	Vec3d  *ptr = dst.ptr<Vec3d>(y);
	for(int x = 0; x < imageWidth; ++x){
	  if (isEdge(x, y, imageWidth, imageHeight, margineWidth, margineWidth)){
	    ptr[x][ch]
	      = calcKernelOutputAtEdge(srcChannels[ch],
				       kernel, x, y,
				       imageWidth, imageHeight,
				       margineWidth, margineHeight);
	  }else{
	    ptr[x][ch]
	      = calcKernelOutput(srcChannels[ch],
				 kernel, x, y,
				 margineWidth, margineHeight,				 
				 kernelElemCount);
	  }
	}
      }
    }
  }

void HomographyHO::normalizeDataIsotropic(cv::InputArray _Data, cv::OutputArray _DataN, cv::OutputArray _T, cv::OutputArray _Ti)
{
    cv::Mat Data = _Data.getMat();
    int numPoints = Data.rows * Data.cols;
    assert((Data.rows == 1) | (Data.cols == 1));
    assert((Data.channels() == 2) | (Data.channels() == 3));
    assert(numPoints >= 4);

    int dataType = _Data.type();
    assert((dataType == CV_64FC2) | (dataType == CV_64FC3) | (dataType == CV_32FC2) | (dataType == CV_32FC3));

    _DataN.create(2, numPoints, CV_64FC1);

    _T.create(3, 3, CV_64FC1);
    _Ti.create(3, 3, CV_64FC1);

    cv::Mat DataN = _DataN.getMat();
    cv::Mat T = _T.getMat();
    cv::Mat Ti = _Ti.getMat();

    _T.setTo(0);
    _Ti.setTo(0);

    double xm, ym;
    int numChannels = Data.channels();

    xm = 0;
    ym = 0;
    for (int i = 0; i < numPoints; i++) {
        if (numChannels == 2) {
            if (dataType == CV_32FC2) {
                xm = xm + Data.at<Vec2f>(i)[0];
                ym = ym + Data.at<Vec2f>(i)[1];
            }
            else {
                xm = xm + Data.at<Vec2d>(i)[0];
                ym = ym + Data.at<Vec2d>(i)[1];
            }
        }
        else {
            if (dataType == CV_32FC3) {
                xm = xm + Data.at<Vec3f>(i)[0];
                ym = ym + Data.at<Vec3f>(i)[1];
            }
            else {
                xm = xm + Data.at<Vec3d>(i)[0];
                ym = ym + Data.at<Vec3d>(i)[1];
            }
        }
    }
    xm = xm / (double)numPoints;
    ym = ym / (double)numPoints;

    double kappa = 0;
    double xh, yh;

    for (int i = 0; i < numPoints; i++) {

        if (numChannels == 2) {
            if (dataType == CV_32FC2) {
                xh = Data.at<Vec2f>(i)[0] - xm;
                yh = Data.at<Vec2f>(i)[1] - ym;
            }
            else {
                xh = Data.at<Vec2d>(i)[0] - xm;
                yh = Data.at<Vec2d>(i)[1] - ym;
            }
        }
        else {
            if (dataType == CV_32FC3) {
                xh = Data.at<Vec3f>(i)[0] - xm;
                yh = Data.at<Vec3f>(i)[1] - ym;
            }
            else {
                xh = Data.at<Vec3d>(i)[0] - xm;
                yh = Data.at<Vec3d>(i)[1] - ym;
            }
        }

        DataN.at<double>(0, i) = xh;
        DataN.at<double>(1, i) = yh;
        kappa = kappa + xh * xh + yh * yh;
    }
    double beta = sqrt(2 * numPoints / kappa);
    DataN = DataN * beta;

    T.at<double>(0, 0) = 1.0 / beta;
    T.at<double>(1, 1) = 1.0 / beta;

    T.at<double>(0, 2) = xm;
    T.at<double>(1, 2) = ym;

    T.at<double>(2, 2) = 1;

    Ti.at<double>(0, 0) = beta;
    Ti.at<double>(1, 1) = beta;

    Ti.at<double>(0, 2) = -beta * xm;
    Ti.at<double>(1, 2) = -beta * ym;

//.........这里部分代码省略.........

void unprojectPointsFisheye( cv::InputArray distorted, cv::OutputArray undistorted, cv::InputArray K, cv::InputArray D, cv::InputArray R, cv::InputArray P)
{
    // will support only 2-channel data now for points
    CV_Assert(distorted.type() == CV_32FC2 || distorted.type() == CV_64FC2);
    undistorted.create(distorted.size(), CV_MAKETYPE(distorted.depth(), 3));

    CV_Assert(P.empty() || P.size() == cv::Size(3, 3) || P.size() == cv::Size(4, 3));
    CV_Assert(R.empty() || R.size() == cv::Size(3, 3) || R.total() * R.channels() == 3);
    CV_Assert(D.total() == 4 && K.size() == cv::Size(3, 3) && (K.depth() == CV_32F || K.depth() == CV_64F));

    cv::Vec2d f, c;
    if (K.depth() == CV_32F)
    {
        cv::Matx33f camMat = K.getMat();
        f = cv::Vec2f(camMat(0, 0), camMat(1, 1));
        c = cv::Vec2f(camMat(0, 2), camMat(1, 2));
    }
    else
    {
        cv::Matx33d camMat = K.getMat();
        f = cv::Vec2d(camMat(0, 0), camMat(1, 1));
        c = cv::Vec2d(camMat(0, 2), camMat(1, 2));
    }

    cv::Vec4d k = D.depth() == CV_32F ? (cv::Vec4d)*D.getMat().ptr<cv::Vec4f>(): *D.getMat().ptr<cv::Vec4d>();

    cv::Matx33d RR = cv::Matx33d::eye();
    if (!R.empty() && R.total() * R.channels() == 3)
    {
        cv::Vec3d rvec;
        R.getMat().convertTo(rvec, CV_64F);
        RR = cv::Affine3d(rvec).rotation();
    }
    else if (!R.empty() && R.size() == cv::Size(3, 3))
        R.getMat().convertTo(RR, CV_64F);

    if(!P.empty())
    {
        cv::Matx33d PP;
        P.getMat().colRange(0, 3).convertTo(PP, CV_64F);
        RR = PP * RR;
    }

    // start undistorting
    const cv::Vec2f* srcf = distorted.getMat().ptr<cv::Vec2f>();
    const cv::Vec2d* srcd = distorted.getMat().ptr<cv::Vec2d>();
    cv::Vec3f* dstf = undistorted.getMat().ptr<cv::Vec3f>();
    cv::Vec3d* dstd = undistorted.getMat().ptr<cv::Vec3d>();

    size_t n = distorted.total();
    int sdepth = distorted.depth();

    for(size_t i = 0; i < n; i++ )
    {
        cv::Vec2d pi = sdepth == CV_32F ? (cv::Vec2d)srcf[i] : srcd[i];  // image point
        cv::Vec2d pw((pi[0] - c[0])/f[0], (pi[1] - c[1])/f[1]);      // world point

        double theta_d = sqrt(pw[0]*pw[0] + pw[1]*pw[1]);
        double theta = theta_d;
        if (theta_d > 1e-8)
        {
            // compensate distortion iteratively
            for(int j = 0; j < 10; j++ )
            {
                double theta2 = theta*theta, theta4 = theta2*theta2, theta6 = theta4*theta2, theta8 = theta6*theta2;
                theta = theta_d / (1 + k[0] * theta2 + k[1] * theta4 + k[2] * theta6 + k[3] * theta8);
            }
        }
        double z = std::cos(theta);
        double r = std::sin(theta);

        cv::Vec3d pu = cv::Vec3d(r*pw[0], r*pw[1], z); //undistorted point

        // reproject
        cv::Vec3d pr = RR * pu; // rotated point optionally multiplied by new camera matrix
        cv::Vec3d fi;       // final
        normalize(pr, fi);

        if( sdepth == CV_32F )
            dstf[i] = fi;
        else
            dstd[i] = fi;
    }
}

bool VideoWriter_IntelMFX::write_one(cv::InputArray bgr)
{
    mfxStatus res;
    mfxFrameSurface1 *workSurface = 0;
    mfxSyncPoint sync;

    if (!bgr.empty() && (bgr.dims() != 2 || bgr.type() != CV_8UC3 || bgr.size() != frameSize))
    {
        MSG(cerr << "MFX: invalid frame passed to encoder: "
            << "dims/depth/cn=" << bgr.dims() << "/" << bgr.depth() << "/" << bgr.channels()
            << ", size=" << bgr.size() << endl);
        return false;

    }
    if (!bgr.empty())
    {
        workSurface = pool->getFreeSurface();
        if (!workSurface)
        {
            // not enough surfaces
            MSG(cerr << "MFX: Failed to get free surface" << endl);
            return false;
        }
        const int rows = workSurface->Info.Height;
        const int cols = workSurface->Info.Width;
        Mat Y(rows, cols, CV_8UC1, workSurface->Data.Y, workSurface->Data.Pitch);
        Mat UV(rows / 2, cols, CV_8UC1, workSurface->Data.UV, workSurface->Data.Pitch);
        to_nv12(bgr, Y, UV);
        CV_Assert(Y.ptr() == workSurface->Data.Y);
        CV_Assert(UV.ptr() == workSurface->Data.UV);
    }

    while (true)
    {
        outSurface = 0;
        DBG(cout << "Calling with surface: " << workSurface << endl);
        res = encoder->EncodeFrameAsync(NULL, workSurface, &bs->stream, &sync);
        if (res == MFX_ERR_NONE)
        {
            res = session->SyncOperation(sync, 1000); // 1 sec, TODO: provide interface to modify timeout
            if (res == MFX_ERR_NONE)
            {
                // ready to write
                if (!bs->write())
                {
                    MSG(cerr << "MFX: Failed to write bitstream" << endl);
                    return false;
                }
                else
                {
                    DBG(cout << "Write bitstream" << endl);
                    return true;
                }
            }
            else
            {
                MSG(cerr << "MFX: Sync error: " << res << endl);
                return false;
            }
        }
        else if (res == MFX_ERR_MORE_DATA)
        {
            DBG(cout << "ERR_MORE_DATA" << endl);
            return false;
        }
        else if (res == MFX_WRN_DEVICE_BUSY)
        {
            DBG(cout << "Waiting for device" << endl);
            sleep(1);
            continue;
        }
        else
        {
            MSG(cerr << "MFX: Bad status: " << res << endl);
            return false;
        }
    }
}

void Regression::verify(cv::FileNode node, cv::InputArray array, double eps, ERROR_TYPE err)
{
    int expected_kind = (int)node["kind"];
    int expected_type = (int)node["type"];
    ASSERT_EQ(expected_kind, array.kind()) << "  Argument \"" << node.name() << "\" has unexpected kind";
    ASSERT_EQ(expected_type, array.type()) << "  Argument \"" << node.name() << "\" has unexpected type";

    cv::FileNode valnode = node["val"];
    if (isVector(array))
    {
        int expected_length = (int)node["len"];
        ASSERT_EQ(expected_length, (int)array.total()) << "  Vector \"" << node.name() << "\" has unexpected length";
        int idx = node["idx"];

        cv::Mat actual = array.getMat(idx);

        if (valnode.isNone())
        {
            ASSERT_LE((size_t)26, actual.total() * (size_t)actual.channels())
                    << "  \"" << node.name() << "[" <<  idx << "]\" has unexpected number of elements";
            verify(node, actual, eps, cv::format("%s[%d]", node.name().c_str(), idx), err);
        }
        else
        {
            cv::Mat expected;
            valnode >> expected;

            if(expected.empty())
            {
                ASSERT_TRUE(actual.empty())
                    << "  expected empty " << node.name() << "[" <<  idx<< "]";
            }
            else
            {
                ASSERT_EQ(expected.size(), actual.size())
                        << "  " << node.name() << "[" <<  idx<< "] has unexpected size";

                cv::Mat diff;
                cv::absdiff(expected, actual, diff);

                if (err == ERROR_ABSOLUTE)
                {
                    if (!cv::checkRange(diff, true, 0, 0, eps))
                    {
                        if(expected.total() * expected.channels() < 12)
                            std::cout << " Expected: " << std::endl << expected << std::endl << " Actual:" << std::endl << actual << std::endl;

                        double max;
                        cv::minMaxIdx(diff.reshape(1), 0, &max);

                        FAIL() << "  Absolute difference (=" << max << ") between argument \""
                               << node.name() << "[" <<  idx << "]\" and expected value is greater than " << eps;
                    }
                }
                else if (err == ERROR_RELATIVE)
                {
                    double maxv, maxa;
                    int violations = countViolations(expected, actual, diff, eps, &maxv, &maxa);
                    if (violations > 0)
                    {
                        FAIL() << "  Relative difference (" << maxv << " of " << maxa << " allowed) between argument \""
                               << node.name() << "[" <<  idx << "]\" and expected value is greater than " << eps << " in " << violations << " points";
                    }
                }
            }
        }
    }
    else
    {
        if (valnode.isNone())

	void disparityFitPlane(cv::InputArray disparity, cv::InputArray image, cv::OutputArray dest, int slicRegionSize, float slicRegularization, float slicMinRegionRatio, int slicMaxIteration, int ransacNumofSample, float ransacThreshold)
	{
		//disparityFitTest(ransacNumofSample, ransacThreshold);
		//cv::FileStorage pointxml("planePoint.xml", cv::FileStorage::WRITE); int err = 0;

		Mat segment;
		SLIC(image, segment, slicRegionSize, slicRegularization, slicMinRegionRatio, slicMaxIteration);
		
		vector<vector<Point3f>> points;
		SLICSegment2Vector3D_<float>(segment, disparity, 0, points);

		Mat disp32f = Mat::zeros(dest.size(), CV_32F);

		for (int i = 0; i < points.size(); ++i)
		{	
			if (points[i].size() < 3)
			{
				if (!points[i].empty())
				{
					for (int j = 0; j < points[i].size(); ++j)
					{
						points[i][j].z = 0.f;
					}
				}
			}
			else
			{
				Point3f abc;

				fitPlaneRANSAC(points[i], abc, ransacNumofSample, ransacThreshold, 1);

				//for refinement(if nessesary)
				int v = countArrowablePointDistanceZ(points[i], abc, ransacThreshold);
				/*double rate = (double)v / points[i].size() * 100;
				int itermax = 1;
				for (int n = 0; n < itermax;n++)
				{
					if (rate < 30)
					{
						//pointxml <<format("point%03d",err++)<< points[i];
						fitPlaneRANSAC(points[i], abc, ransacNumofSample, ransacThreshold, 1);
						v = countArrowablePointDistanceZ(points[i], abc, ransacThreshold);
						rate = (double)v / points[i].size() * 100;
					}
				}*/
	
				for (int j = 0; j < points[i].size(); ++j)
				{
					points[i][j].z = points[i][j].x*abc.x + points[i][j].y*abc.y + abc.z;
				}			
			}
		}

		SLICVector3D2Signal(points, image.size(), disp32f);
		if (disparity.depth() == CV_32F)
		{
			disp32f.copyTo(dest);
		}
		else if (disparity.depth() == CV_8U || disparity.depth() == CV_16U || disparity.depth() == CV_16S || disparity.depth() == CV_32S)
		{
			disp32f.convertTo(dest, disparity.type(), 1.0, 0.5);
		}
		else
		{
			disp32f.convertTo(dest, disparity.type());
		}
	}