322 lines
8.1 KiB
C++
322 lines
8.1 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html
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// This code is also subject to the license terms in the LICENSE_KinectFusion.md file found in this module's directory
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#include "precomp.hpp"
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#include "fast_icp.hpp"
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#include "tsdf.hpp"
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#include "kinfu_frame.hpp"
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namespace cv {
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namespace kinfu {
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Ptr<Params> Params::defaultParams()
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{
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Params p;
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p.frameSize = Size(640, 480);
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float fx, fy, cx, cy;
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fx = fy = 525.f;
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cx = p.frameSize.width/2 - 0.5f;
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cy = p.frameSize.height/2 - 0.5f;
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p.intr = Matx33f(fx, 0, cx,
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0, fy, cy,
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0, 0, 1);
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// 5000 for the 16-bit PNG files
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// 1 for the 32-bit float images in the ROS bag files
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p.depthFactor = 5000;
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// sigma_depth is scaled by depthFactor when calling bilateral filter
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p.bilateral_sigma_depth = 0.04f; //meter
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p.bilateral_sigma_spatial = 4.5; //pixels
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p.bilateral_kernel_size = 7; //pixels
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p.icpAngleThresh = (float)(30. * CV_PI / 180.); // radians
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p.icpDistThresh = 0.1f; // meters
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p.icpIterations = {10, 5, 4};
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p.pyramidLevels = (int)p.icpIterations.size();
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p.tsdf_min_camera_movement = 0.f; //meters, disabled
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p.volumeDims = Vec3i::all(512); //number of voxels
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float volSize = 3.f;
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p.voxelSize = volSize/512.f; //meters
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// default pose of volume cube
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p.volumePose = Affine3f().translate(Vec3f(-volSize/2.f, -volSize/2.f, 0.5f));
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p.tsdf_trunc_dist = 0.04f; //meters;
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p.tsdf_max_weight = 64; //frames
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p.raycast_step_factor = 0.25f; //in voxel sizes
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// gradient delta factor is fixed at 1.0f and is not used
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//p.gradient_delta_factor = 0.5f; //in voxel sizes
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//p.lightPose = p.volume_pose.translation()/4; //meters
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p.lightPose = Vec3f::all(0.f); //meters
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// depth truncation is not used by default but can be useful in some scenes
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p.truncateThreshold = 0.f; //meters
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return makePtr<Params>(p);
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}
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Ptr<Params> Params::coarseParams()
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{
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Ptr<Params> p = defaultParams();
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p->icpIterations = {5, 3, 2};
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p->pyramidLevels = (int)p->icpIterations.size();
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float volSize = 3.f;
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p->volumeDims = Vec3i::all(128); //number of voxels
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p->voxelSize = volSize/128.f;
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p->raycast_step_factor = 0.75f; //in voxel sizes
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return p;
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}
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// T should be Mat or UMat
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template< typename T >
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class KinFuImpl : public KinFu
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{
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public:
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KinFuImpl(const Params& _params);
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virtual ~KinFuImpl();
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const Params& getParams() const CV_OVERRIDE;
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void render(OutputArray image, const Matx44f& cameraPose) const CV_OVERRIDE;
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void getCloud(OutputArray points, OutputArray normals) const CV_OVERRIDE;
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void getPoints(OutputArray points) const CV_OVERRIDE;
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void getNormals(InputArray points, OutputArray normals) const CV_OVERRIDE;
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void reset() CV_OVERRIDE;
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const Affine3f getPose() const CV_OVERRIDE;
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bool update(InputArray depth) CV_OVERRIDE;
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bool updateT(const T& depth);
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private:
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Params params;
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cv::Ptr<ICP> icp;
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cv::Ptr<TSDFVolume> volume;
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int frameCounter;
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Affine3f pose;
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std::vector<T> pyrPoints;
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std::vector<T> pyrNormals;
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};
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template< typename T >
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KinFuImpl<T>::KinFuImpl(const Params &_params) :
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params(_params),
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icp(makeICP(params.intr, params.icpIterations, params.icpAngleThresh, params.icpDistThresh)),
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volume(makeTSDFVolume(params.volumeDims, params.voxelSize, params.volumePose,
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params.tsdf_trunc_dist, params.tsdf_max_weight,
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params.raycast_step_factor)),
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pyrPoints(), pyrNormals()
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{
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reset();
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}
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template< typename T >
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void KinFuImpl<T>::reset()
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{
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frameCounter = 0;
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pose = Affine3f::Identity();
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volume->reset();
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}
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template< typename T >
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KinFuImpl<T>::~KinFuImpl()
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{ }
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template< typename T >
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const Params& KinFuImpl<T>::getParams() const
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{
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return params;
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}
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template< typename T >
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const Affine3f KinFuImpl<T>::getPose() const
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{
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return pose;
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}
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template<>
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bool KinFuImpl<Mat>::update(InputArray _depth)
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{
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CV_Assert(!_depth.empty() && _depth.size() == params.frameSize);
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Mat depth;
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if(_depth.isUMat())
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{
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_depth.copyTo(depth);
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return updateT(depth);
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}
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else
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{
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return updateT(_depth.getMat());
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}
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}
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template<>
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bool KinFuImpl<UMat>::update(InputArray _depth)
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{
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CV_Assert(!_depth.empty() && _depth.size() == params.frameSize);
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UMat depth;
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if(!_depth.isUMat())
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{
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_depth.copyTo(depth);
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return updateT(depth);
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}
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else
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{
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return updateT(_depth.getUMat());
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}
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}
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template< typename T >
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bool KinFuImpl<T>::updateT(const T& _depth)
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{
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CV_TRACE_FUNCTION();
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T depth;
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if(_depth.type() != DEPTH_TYPE)
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_depth.convertTo(depth, DEPTH_TYPE);
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else
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depth = _depth;
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std::vector<T> newPoints, newNormals;
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makeFrameFromDepth(depth, newPoints, newNormals, params.intr,
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params.pyramidLevels,
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params.depthFactor,
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params.bilateral_sigma_depth,
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params.bilateral_sigma_spatial,
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params.bilateral_kernel_size,
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params.truncateThreshold);
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if(frameCounter == 0)
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{
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// use depth instead of distance
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volume->integrate(depth, params.depthFactor, pose, params.intr);
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pyrPoints = newPoints;
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pyrNormals = newNormals;
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}
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else
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{
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Affine3f affine;
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bool success = icp->estimateTransform(affine, pyrPoints, pyrNormals, newPoints, newNormals);
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if(!success)
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return false;
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pose = pose * affine;
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float rnorm = (float)cv::norm(affine.rvec());
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float tnorm = (float)cv::norm(affine.translation());
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// We do not integrate volume if camera does not move
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if((rnorm + tnorm)/2 >= params.tsdf_min_camera_movement)
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{
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// use depth instead of distance
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volume->integrate(depth, params.depthFactor, pose, params.intr);
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}
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T& points = pyrPoints [0];
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T& normals = pyrNormals[0];
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volume->raycast(pose, params.intr, params.frameSize, points, normals);
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// build a pyramid of points and normals
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buildPyramidPointsNormals(points, normals, pyrPoints, pyrNormals,
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params.pyramidLevels);
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}
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frameCounter++;
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return true;
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}
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template< typename T >
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void KinFuImpl<T>::render(OutputArray image, const Matx44f& _cameraPose) const
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{
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CV_TRACE_FUNCTION();
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Affine3f cameraPose(_cameraPose);
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const Affine3f id = Affine3f::Identity();
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if((cameraPose.rotation() == pose.rotation() && cameraPose.translation() == pose.translation()) ||
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(cameraPose.rotation() == id.rotation() && cameraPose.translation() == id.translation()))
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{
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renderPointsNormals(pyrPoints[0], pyrNormals[0], image, params.lightPose);
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}
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else
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{
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T points, normals;
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volume->raycast(cameraPose, params.intr, params.frameSize, points, normals);
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renderPointsNormals(points, normals, image, params.lightPose);
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}
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}
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template< typename T >
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void KinFuImpl<T>::getCloud(OutputArray p, OutputArray n) const
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{
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volume->fetchPointsNormals(p, n);
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}
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template< typename T >
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void KinFuImpl<T>::getPoints(OutputArray points) const
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{
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volume->fetchPointsNormals(points, noArray());
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}
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template< typename T >
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void KinFuImpl<T>::getNormals(InputArray points, OutputArray normals) const
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{
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volume->fetchNormals(points, normals);
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}
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// importing class
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#ifdef OPENCV_ENABLE_NONFREE
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Ptr<KinFu> KinFu::create(const Ptr<Params>& params)
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{
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#ifdef HAVE_OPENCL
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if(cv::ocl::useOpenCL())
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return makePtr< KinFuImpl<UMat> >(*params);
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#endif
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return makePtr< KinFuImpl<Mat> >(*params);
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}
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#else
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Ptr<KinFu> KinFu::create(const Ptr<Params>& /*params*/)
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{
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CV_Error(Error::StsNotImplemented,
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"This algorithm is patented and is excluded in this configuration; "
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"Set OPENCV_ENABLE_NONFREE CMake option and rebuild the library");
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}
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#endif
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KinFu::~KinFu() {}
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} // namespace kinfu
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} // namespace cv
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