Class cv::Odometry#
#include <opencv2/ptcloud/odometry.hpp>Collaboration diagram for cv::Odometry:
Constructor & Destructor Documentation#
Odometry()#
Python:
Odometry()#
cv::Odometry::Odometry(OdometryType otype)
Python:
Odometry()#
cv::Odometry::Odometry(
OdometryType otype,
const OdometrySettings & settings,
OdometryAlgoType algtype )
Python:
~Odometry()#
cv::Odometry::~Odometry()
Member Function Documentation#
compute()#
bool cv::Odometry::compute(
const OdometryFrame & srcFrame,
const OdometryFrame & dstFrame,
OutputArray Rt )
Python:
cv.Odometry.compute(srcFrame, dstFrame[, Rt]) -> retval, Rt
cv.Odometry.compute(srcDepth, dstDepth[, Rt]) -> retval, Rt
cv.Odometry.compute(srcDepth, srcRGB, dstDepth, dstRGB[, Rt]) -> retval, Rt
Compute Rigid Transformation between two frames so that Rt * src = dst Both frames, source and destination, should have been prepared by calling prepareFrame() first
Parameters
srcFrame— src frame (“original” image)dstFrame— dst frame (“rotated” image)Rt— Rigid transformation, which will be calculated, in form: { R_11 R_12 R_13 t_1 R_21 R_22 R_23 t_2 R_31 R_32 R_33 t_3 0 0 0 1 }
Returns
true on success, false if failed to find the transformation
compute()#
bool cv::Odometry::compute(
InputArray srcDepth,
InputArray dstDepth,
OutputArray Rt )
Python:
cv.Odometry.compute(srcFrame, dstFrame[, Rt]) -> retval, Rt
cv.Odometry.compute(srcDepth, dstDepth[, Rt]) -> retval, Rt
cv.Odometry.compute(srcDepth, srcRGB, dstDepth, dstRGB[, Rt]) -> retval, Rt
Compute Rigid Transformation between two frames so that Rt * src = dst.
Parameters
srcDepth— source depth (“original” image)dstDepth— destination depth (“rotated” image)Rt— Rigid transformation, which will be calculated, in form: { R_11 R_12 R_13 t_1 R_21 R_22 R_23 t_2 R_31 R_32 R_33 t_3 0 0 0 1 }
Returns
true on success, false if failed to find the transformation
compute()#
bool cv::Odometry::compute(
InputArray srcDepth,
InputArray srcRGB,
InputArray dstDepth,
InputArray dstRGB,
OutputArray Rt )
Python:
cv.Odometry.compute(srcFrame, dstFrame[, Rt]) -> retval, Rt
cv.Odometry.compute(srcDepth, dstDepth[, Rt]) -> retval, Rt
cv.Odometry.compute(srcDepth, srcRGB, dstDepth, dstRGB[, Rt]) -> retval, Rt
Compute Rigid Transformation between two frames so that Rt * src = dst.
Parameters
srcDepth— source depth (“original” image)srcRGB— source RGBdstDepth— destination depth (“rotated” image)dstRGB— destination RGBRt— Rigid transformation, which will be calculated, in form: { R_11 R_12 R_13 t_1 R_21 R_22 R_23 t_2 R_31 R_32 R_33 t_3 0 0 0 1 }
Returns
true on success, false if failed to find the transformation
getNormalsComputer()#
Ptr< RgbdNormals > cv::Odometry::getNormalsComputer()
Python:
cv.Odometry.getNormalsComputer() -> retval
Get the normals computer object used for normals calculation (if presented). The normals computer is generated at first need during prepareFrame when normals are required for the ICP algorithm but not presented by a user. Re-generated each time the related settings change or a new frame arrives with the different size.
prepareFrame()#
void cv::Odometry::prepareFrame(OdometryFrame & frame)
Python:
cv.Odometry.prepareFrame(frame)
Prepare frame for odometry calculation
Parameters
frame— odometry prepare this frame as src frame and dst frame simultaneously
prepareFrames()#
void cv::Odometry::prepareFrames(
OdometryFrame & srcFrame,
OdometryFrame & dstFrame )
Python:
cv.Odometry.prepareFrames(srcFrame, dstFrame)
Prepare frame for odometry calculation
Parameters
srcFrame— frame will be prepared as src frame (“original” image)dstFrame— frame will be prepared as dsr frame (“rotated” image)
Member Data Documentation#
impl#
Ptr< Impl > cv::Odometry::impl
Source file#
The documentation for this class was generated from the following file:
opencv2/ptcloud/odometry.hpp