cv::Stitcher Class Reference

High level image stitcher. More...

#include <opencv2/stitching.hpp>

Public Types
enum	Mode {   PANORAMA = 0,   SCANS = 1 }
enum	Status {   OK = 0,   ERR_NEED_MORE_IMGS = 1,   ERR_HOMOGRAPHY_EST_FAIL = 2,   ERR_CAMERA_PARAMS_ADJUST_FAIL = 3 }

Public Member Functions
Ptr< detail::Blender >	blender ()
const Ptr< detail::Blender >	blender () const
Ptr< detail::BundleAdjusterBase >	bundleAdjuster ()
const Ptr< detail::BundleAdjusterBase >	bundleAdjuster () const
std::vector< detail::CameraParams >	cameras () const
std::vector< int >	component () const
Status	composePanorama (OutputArray pano)
Status	composePanorama (InputArrayOfArrays images, OutputArray pano)
	These functions try to compose the given images (or images stored internally from the other function calls) into the final pano under the assumption that the image transformations were estimated before. More...
double	compositingResol () const
Status	estimateTransform (InputArrayOfArrays images, InputArrayOfArrays masks=noArray())
	These functions try to match the given images and to estimate rotations of each camera. More...
Ptr< detail::Estimator >	estimator ()
const Ptr< detail::Estimator >	estimator () const
Ptr< detail::ExposureCompensator >	exposureCompensator ()
const Ptr< detail::ExposureCompensator >	exposureCompensator () const
Ptr< Feature2D >	featuresFinder ()
const Ptr< Feature2D >	featuresFinder () const
Ptr< detail::FeaturesMatcher >	featuresMatcher ()
const Ptr< detail::FeaturesMatcher >	featuresMatcher () const
InterpolationFlags	interpolationFlags () const
const cv::UMat &	matchingMask () const
double	panoConfidenceThresh () const
double	registrationResol () const
UMat	resultMask () const
double	seamEstimationResol () const
Ptr< detail::SeamFinder >	seamFinder ()
const Ptr< detail::SeamFinder >	seamFinder () const
void	setBlender (Ptr< detail::Blender > b)
void	setBundleAdjuster (Ptr< detail::BundleAdjusterBase > bundle_adjuster)
void	setCompositingResol (double resol_mpx)
void	setEstimator (Ptr< detail::Estimator > estimator)
void	setExposureCompensator (Ptr< detail::ExposureCompensator > exposure_comp)
void	setFeaturesFinder (Ptr< Feature2D > features_finder)
void	setFeaturesMatcher (Ptr< detail::FeaturesMatcher > features_matcher)
void	setInterpolationFlags (InterpolationFlags interp_flags)
void	setMatchingMask (const cv::UMat &mask)
void	setPanoConfidenceThresh (double conf_thresh)
void	setRegistrationResol (double resol_mpx)
void	setSeamEstimationResol (double resol_mpx)
void	setSeamFinder (Ptr< detail::SeamFinder > seam_finder)
void	setWarper (Ptr< WarperCreator > creator)
void	setWaveCorrection (bool flag)
void	setWaveCorrectKind (detail::WaveCorrectKind kind)
Status	stitch (InputArrayOfArrays images, OutputArray pano)
Status	stitch (InputArrayOfArrays images, InputArrayOfArrays masks, OutputArray pano)
	These functions try to stitch the given images. More...
Ptr< WarperCreator >	warper ()
const Ptr< WarperCreator >	warper () const
bool	waveCorrection () const
detail::WaveCorrectKind	waveCorrectKind () const
double	workScale () const

Static Public Member Functions
static Ptr< Stitcher >	create (Mode mode=Stitcher::PANORAMA)
	Creates a Stitcher configured in one of the stitching modes. More...

Static Public Attributes
static const double	ORIG_RESOL

Detailed Description

High level image stitcher.

It's possible to use this class without being aware of the entire stitching pipeline. However, to be able to achieve higher stitching stability and quality of the final images at least being familiar with the theory is recommended.

Note

• A basic example on image stitching can be found at opencv_source_code/samples/cpp/stitching.cpp
• A basic example on image stitching in Python can be found at opencv_source_code/samples/python/stitching.py
• A detailed example on image stitching can be found at opencv_source_code/samples/cpp/stitching_detailed.cpp

Member Enumeration Documentation

Mode

enum cv::Stitcher::Mode

Enumerator
PANORAMA	Mode for creating photo panoramas. Expects images under perspective transformation and projects resulting pano to sphere. See also detail::BestOf2NearestMatcher SphericalWarper
SCANS	Mode for composing scans. Expects images under affine transformation does not compensate exposure by default. See also detail::AffineBestOf2NearestMatcher AffineWarper

Status

enum cv::Stitcher::Status

Enumerator
OK
ERR_NEED_MORE_IMGS
ERR_HOMOGRAPHY_EST_FAIL
ERR_CAMERA_PARAMS_ADJUST_FAIL

Member Function Documentation

blender() [1/2]

Ptr<detail::Blender> cv::Stitcher::blender ( )

inline

blender() [2/2]

const Ptr<detail::Blender> cv::Stitcher::blender ( ) const

inline

bundleAdjuster() [1/2]

Ptr<detail::BundleAdjusterBase> cv::Stitcher::bundleAdjuster ( )

inline

bundleAdjuster() [2/2]

const Ptr<detail::BundleAdjusterBase> cv::Stitcher::bundleAdjuster ( ) const

inline

cameras()

std::vector<detail::CameraParams> cv::Stitcher::cameras ( ) const

inline

component()

std::vector<int> cv::Stitcher::component ( ) const

inline

composePanorama() [1/2]

Status cv::Stitcher::composePanorama

(

OutputArray

pano

)

Python:
	retval, pano	=	cv.Stitcher.composePanorama(	[, pano]	)

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

composePanorama() [2/2]

Status cv::Stitcher::composePanorama	(	InputArrayOfArrays	images,
		OutputArray	pano
	)

Python:
	retval, pano	=	cv.Stitcher.composePanorama(	[, pano]	)

These functions try to compose the given images (or images stored internally from the other function calls) into the final pano under the assumption that the image transformations were estimated before.

Note

Use the functions only if you're aware of the stitching pipeline, otherwise use Stitcher::stitch.

Parameters

images	Input images.
pano	Final pano.

Returns

Status code.

compositingResol()

double cv::Stitcher::compositingResol ( ) const

inline

Python:
	retval	=	cv.Stitcher.compositingResol(		)

create()

static Ptr<Stitcher> cv::Stitcher::create ( Mode  mode = Stitcher::PANORAMA )

static

Python:
	retval	=	cv.Stitcher_create(	[, mode]	)

Creates a Stitcher configured in one of the stitching modes.

Parameters

mode	Scenario for stitcher operation. This is usually determined by source of images to stitch and their transformation. Default parameters will be chosen for operation in given scenario.

Returns

Stitcher class instance.

estimateTransform()

Status cv::Stitcher::estimateTransform	(	InputArrayOfArrays	images,
		InputArrayOfArrays	masks = noArray()
	)

Python:
	retval	=	cv.Stitcher.estimateTransform(	images[, masks]	)

These functions try to match the given images and to estimate rotations of each camera.

Note

Use the functions only if you're aware of the stitching pipeline, otherwise use Stitcher::stitch.

Parameters

images	Input images.
masks	Masks for each input image specifying where to look for keypoints (optional).

Returns

Status code.

estimator() [1/2]

Ptr<detail::Estimator> cv::Stitcher::estimator ( )

inline

estimator() [2/2]

const Ptr<detail::Estimator> cv::Stitcher::estimator ( ) const

inline

exposureCompensator() [1/2]

Ptr<detail::ExposureCompensator> cv::Stitcher::exposureCompensator ( )

inline

exposureCompensator() [2/2]

const Ptr<detail::ExposureCompensator> cv::Stitcher::exposureCompensator ( ) const

inline

featuresFinder() [1/2]

Ptr<Feature2D> cv::Stitcher::featuresFinder ( )

inline

featuresFinder() [2/2]

const Ptr<Feature2D> cv::Stitcher::featuresFinder ( ) const

inline

featuresMatcher() [1/2]

Ptr<detail::FeaturesMatcher> cv::Stitcher::featuresMatcher ( )

inline

featuresMatcher() [2/2]

const Ptr<detail::FeaturesMatcher> cv::Stitcher::featuresMatcher ( ) const

inline

interpolationFlags()

InterpolationFlags cv::Stitcher::interpolationFlags ( ) const

inline

Python:
	retval	=	cv.Stitcher.interpolationFlags(		)

matchingMask()

const cv::UMat& cv::Stitcher::matchingMask ( ) const

inline

panoConfidenceThresh()

double cv::Stitcher::panoConfidenceThresh ( ) const

inline

Python:
	retval	=	cv.Stitcher.panoConfidenceThresh(		)

registrationResol()

double cv::Stitcher::registrationResol ( ) const

inline

Python:
	retval	=	cv.Stitcher.registrationResol(		)

resultMask()

UMat cv::Stitcher::resultMask ( ) const

inline

seamEstimationResol()

double cv::Stitcher::seamEstimationResol ( ) const

inline

Python:
	retval	=	cv.Stitcher.seamEstimationResol(		)

seamFinder() [1/2]

Ptr<detail::SeamFinder> cv::Stitcher::seamFinder ( )

inline

seamFinder() [2/2]

const Ptr<detail::SeamFinder> cv::Stitcher::seamFinder ( ) const

inline

setBlender()

void cv::Stitcher::setBlender ( Ptr< detail::Blender >  b )

inline

setBundleAdjuster()

void cv::Stitcher::setBundleAdjuster ( Ptr< detail::BundleAdjusterBase >  bundle_adjuster )

inline

setCompositingResol()

void cv::Stitcher::setCompositingResol ( double  resol_mpx )

inline

Python:
	None	=	cv.Stitcher.setCompositingResol(	resol_mpx	)

setEstimator()

void cv::Stitcher::setEstimator ( Ptr< detail::Estimator >  estimator )

inline

setExposureCompensator()

void cv::Stitcher::setExposureCompensator ( Ptr< detail::ExposureCompensator >  exposure_comp )

inline

setFeaturesFinder()

void cv::Stitcher::setFeaturesFinder ( Ptr< Feature2D >  features_finder )

inline

setFeaturesMatcher()

void cv::Stitcher::setFeaturesMatcher ( Ptr< detail::FeaturesMatcher >  features_matcher )

inline

setInterpolationFlags()

void cv::Stitcher::setInterpolationFlags ( InterpolationFlags  interp_flags )

inline

Python:
	None	=	cv.Stitcher.setInterpolationFlags(	interp_flags	)

setMatchingMask()

void cv::Stitcher::setMatchingMask ( const cv::UMat &  mask )

inline

setPanoConfidenceThresh()

void cv::Stitcher::setPanoConfidenceThresh ( double  conf_thresh )

inline

Python:
	None	=	cv.Stitcher.setPanoConfidenceThresh(	conf_thresh	)

setRegistrationResol()

void cv::Stitcher::setRegistrationResol ( double  resol_mpx )

inline

Python:
	None	=	cv.Stitcher.setRegistrationResol(	resol_mpx	)

setSeamEstimationResol()

void cv::Stitcher::setSeamEstimationResol ( double  resol_mpx )

inline

Python:
	None	=	cv.Stitcher.setSeamEstimationResol(	resol_mpx	)

setSeamFinder()

void cv::Stitcher::setSeamFinder ( Ptr< detail::SeamFinder >  seam_finder )

inline

setWarper()

void cv::Stitcher::setWarper ( Ptr< WarperCreator >  creator )

inline

setWaveCorrection()

void cv::Stitcher::setWaveCorrection ( bool  flag )

inline

Python:
	None	=	cv.Stitcher.setWaveCorrection(	flag	)

setWaveCorrectKind()

void cv::Stitcher::setWaveCorrectKind ( detail::WaveCorrectKind  kind )

inline

stitch() [1/2]

Status cv::Stitcher::stitch	(	InputArrayOfArrays	images,
		OutputArray	pano
	)

Python:
	retval, pano	=	cv.Stitcher.stitch(	images[, pano]	)
	retval, pano	=	cv.Stitcher.stitch(	images, masks[, pano]	)

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

stitch() [2/2]

Status cv::Stitcher::stitch	(	InputArrayOfArrays	images,
		InputArrayOfArrays	masks,
		OutputArray	pano
	)

Python:
	retval, pano	=	cv.Stitcher.stitch(	images[, pano]	)
	retval, pano	=	cv.Stitcher.stitch(	images, masks[, pano]	)

These functions try to stitch the given images.

Parameters

images	Input images.
masks	Masks for each input image specifying where to look for keypoints (optional).
pano	Final pano.

Returns

Status code.

warper() [1/2]

Ptr<WarperCreator> cv::Stitcher::warper ( )

inline

warper() [2/2]

const Ptr<WarperCreator> cv::Stitcher::warper ( ) const

inline

waveCorrection()

bool cv::Stitcher::waveCorrection ( ) const

inline

Python:
	retval	=	cv.Stitcher.waveCorrection(		)

waveCorrectKind()

detail::WaveCorrectKind cv::Stitcher::waveCorrectKind ( ) const

inline

workScale()

double cv::Stitcher::workScale ( ) const

inline

Python:
	retval	=	cv.Stitcher.workScale(		)

Member Data Documentation

ORIG_RESOL

const double cv::Stitcher::ORIG_RESOL

static

When setting a resolution for stitching, this values is a placeholder for preserving the original resolution.

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The documentation for this class was generated from the following file:

• opencv2/stitching.hpp