eVision::EPatternFinder Class Reference

Manages a complete finding context in EasyFind. More...

#include <eVision/EasyFind/EPatternFinder.h>

Collaboration diagram for eVision::EPatternFinder:

Public Member Functions
	EPatternFinder ()
	Constructs a EPatternFinder::EPatternFinder context.
	EPatternFinder (const eVision::EPatternFinder &other)
	Constructs a EPatternFinder::EPatternFinder context.
virtual	~EPatternFinder () throw ()
eVision::EPatternFinder &	operator= (const eVision::EPatternFinder &other)
	Assignment operator.
void	Learn (const eVision::EROIBW8 *pattern)
	Learns a given pattern and stores it in the EPatternFinder::EPatternFinder object.
void	Learn (const eVision::EROIBW8 *pattern, const eVision::ERegion &region)
	Learns a given pattern and stores it in the EPatternFinder::EPatternFinder object.
void	Learn (const eVision::EROIBW8 *pattern, const eVision::ERegion &region, const eVision::EFrame &frame)
	Learns a given pattern and stores it in the EPatternFinder::EPatternFinder object.
void	Learn (const eVision::EROIBW8 *pattern, const eVision::EFrame &frame)
	Learns a given pattern and stores it in the EPatternFinder::EPatternFinder object.
void	Learn (eVision::EVectorModel &model)
	Learns a given pattern and stores it in the EPatternFinder::EPatternFinder object.
void	Learn (const eVision::EROIBW8 *pattern, eVision::EROIBW8 *dontCare)
	Learns a given pattern and stores it in the EPatternFinder::EPatternFinder object.
void	LearnPatterns (const std::vector< eVision::EROIBW8 > &patterns)
	Learns multiple (at least two) patterns.
void	LearnPatterns (const std::vector< eVision::EROIBW8 > &patterns, const std::vector< eVision::ERegion > &regions)
	Learns multiple (at least two) patterns.
void	LearnPatterns (const std::vector< eVision::EROIBW8 > &patterns, const std::vector< eVision::ERegion > &regions, const eVision::EFrame &frame)
	Learns multiple (at least two) patterns.
void	LearnPatterns (const std::vector< eVision::EROIBW8 > &patterns, const eVision::EFrame &frame)
	Learns multiple (at least two) patterns.
void	LearnPatterns (const std::vector< eVision::EImageBW8 > &patterns)
	Learns multiple (at least two) patterns.
void	LearnPatterns (const std::vector< eVision::EImageBW8 > &patterns, const std::vector< eVision::ERegion > &regions)
	Learns multiple (at least two) patterns.
void	LearnPatterns (const std::vector< eVision::EImageBW8 > &patterns, const std::vector< eVision::ERegion > &regions, const eVision::EFrame &frame)
	Learns multiple (at least two) patterns.
void	LearnPatterns (const std::vector< eVision::EImageBW8 > &patterns, const eVision::EFrame &frame)
	Learns multiple (at least two) patterns.
void	LearnPatterns (const std::vector< eVision::EROIBW8 * > &patterns)
	Learns multiple (at least two) patterns.
void	LearnPatterns (const std::vector< eVision::EROIBW8 * > &patterns, const std::vector< eVision::ERegion * > &regions)
	Learns multiple (at least two) patterns.
void	LearnPatterns (const std::vector< eVision::EROIBW8 * > &patterns, const std::vector< eVision::ERegion * > &regions, const eVision::EFrame &frame)
	Learns multiple (at least two) patterns.
void	LearnPatterns (const std::vector< eVision::EROIBW8 * > &patterns, const eVision::EFrame &frame)
	Learns multiple (at least two) patterns.
uint32_t	GetNumLearnedPatterns () const
	Indicates the number of patterns learnt. 0 is returned if no learning was performed.
bool	GetLearningDone () const
	Indicates whether a pattern has already been learned.
bool	GetLearningHasRegion () const
	Indicates whether a ERegion was used alongside the learned pattern. Returns false if no learning was performed.
void	CopyLearntPattern (eVision::EImageBW8 &image, bool maskWithDontCare, uint32_t learntPatternIndex) const
	Copies the learned pattern in the supplied image. If no pattern has been learned, an exception with code EError::EError_NoPatternLearnt will be thrown.
void	CopyLearntPattern (eVision::EImageBW8 &image, bool maskWithDontCare) const
	Copies the learned pattern in the supplied image. If no pattern has been learned, an exception with code EError::EError_NoPatternLearnt will be thrown.
void	CopyLearntPattern (eVision::EImageBW8 &image) const
	Copies the learned pattern in the supplied image. If no pattern has been learned, an exception with code EError::EError_NoPatternLearnt will be thrown.
std::vector< eVision::EFoundPattern >	Find (eVision::EROIBW8 *source)
	Locates a set of possible occurrences of the learned pattern in the supplied search field.
std::vector< eVision::EFoundPattern >	Find (eVision::EROIBW8 *source, const eVision::ERegion &region)
	Locates a set of possible occurrences of the learned pattern in the supplied search field.
std::vector< eVision::EFoundPattern >	Find (eVision::EROIBW8 *source, const eVision::ERegion &region, const eVision::EFrame &frame)
	Locates a set of possible occurrences of the learned pattern in the supplied search field.
std::vector< eVision::EFoundPattern >	Find (eVision::EROIBW8 *source, const eVision::EFrame &frame)
	Locates a set of possible occurrences of the learned pattern in the supplied search field.
float	GetAngleBias () const
	Angle bias, expressed in the current angle unit.
void	SetAngleBias (float angleBias)
	Angle bias, expressed in the current angle unit.
float	GetAngleTolerance () const
	Angle tolerance, expressed in the current angle unit.
void	SetAngleTolerance (float angleTolerance)
	Angle tolerance, expressed in the current angle unit.
float	GetScaleBias () const
	Scale bias, expressed in units (not in percent).
void	SetScaleBias (float scaleBias)
	Scale bias, expressed in units (not in percent).
float	GetMaxOverlap () const
	Overlapping tolerance.
void	SetMaxOverlap (float maxOverlap)
	Overlapping tolerance.
float	GetMaximumOverlapping () const
void	SetMaximumOverlapping (float maximumOverlapping)
float	GetScaleTolerance () const
	Scale tolerance, expressed in units (not in percent).
void	SetScaleTolerance (float scaleTolerance)
	Scale tolerance, expressed in units (not in percent).
bool	GetInterpolate () const
	Whether interpolation is performed when searching for a pattern occurrence.
void	SetInterpolate (bool interpolate)
	Whether interpolation is performed when searching for a pattern occurrence.
bool	GetComputePerFeaturePointScore () const
	Whether the EPatternFinder should compute a score for each feature point. The scores are then displayed as a Red-Yellow-Green colormap by EFoundPattern::Draw. Note that the scores correspond to the Point-By-Point variants of EPatternFinder::GetContrastMode, so if EPatternFinder::GetContrastMode is not a Point-By-Point variant, EFoundPattern::GetScore isn't exactly the average of the displayed scores for each feature point.
void	SetComputePerFeaturePointScore (bool compute)
	Whether the EPatternFinder should compute a score for each feature point. The scores are then displayed as a Red-Yellow-Green colormap by EFoundPattern::Draw. Note that the scores correspond to the Point-By-Point variants of EPatternFinder::GetContrastMode, so if EPatternFinder::GetContrastMode is not a Point-By-Point variant, EFoundPattern::GetScore isn't exactly the average of the displayed scores for each feature point.
eVision::EFindContrastMode	GetContrastMode () const
	Contrast of the instance, as defined in EFindContrastMode.
void	SetContrastMode (eVision::EFindContrastMode eContrastMode)
	Contrast of the instance, as defined in EFindContrastMode.
eVision::EReductionMode	GetReductionMode () const
	The reduction mode that is to be used when learning the model (automatic or manual), as defined in EReductionMode.
void	SetReductionMode (eVision::EReductionMode eReductionMode)
	The reduction mode that is to be used when learning the model (automatic or manual), as defined in EReductionMode.
void	SetLocalSearchMode (eVision::ELocalSearchMode eLocalSearchMode)
	Sets the local search mode.
eVision::ELocalSearchMode	GetLocalSearchMode () const
	Sets the local search mode.
void	SetAngleSearchExtent (int32_t extent)
	The angular extension of the search neighborhood. Only odd values are allowed for this parameter. See the EPatternFinder::SetLocalSearchMode property description for further details.
int32_t	GetAngleSearchExtent () const
	The angular extension of the search neighborhood. Only odd values are allowed for this parameter. See the EPatternFinder::SetLocalSearchMode property description for further details.
void	SetScaleSearchExtent (int32_t extent)
	The scaling extension of the search neighborhood. Only odd values are allowed for this parameter. See the EPatternFinder::SetLocalSearchMode property description for further details.
int32_t	GetScaleSearchExtent () const
	The scaling extension of the search neighborhood. Only odd values are allowed for this parameter. See the EPatternFinder::SetLocalSearchMode property description for further details.
void	SetXSearchExtent (int32_t extent)
	The X-axis extension of the search neighborhood. Only odd values are allowed for this parameter. See the EPatternFinder::SetLocalSearchMode property description for further details.
int32_t	GetXSearchExtent () const
	The X-axis extension of the search neighborhood. Only odd values are allowed for this parameter. See the EPatternFinder::SetLocalSearchMode property description for further details.
void	SetYSearchExtent (int32_t extent)
	The Y-axis extension of the search neighborhood. Only odd values are allowed for this parameter. See the EPatternFinder::SetLocalSearchMode property description for further details.
int32_t	GetYSearchExtent () const
	The Y-axis extension of the search neighborhood. Only odd values are allowed for this parameter. See the EPatternFinder::SetLocalSearchMode property description for further details.
uint32_t	GetMaxInstances () const
	Maximum number of instances to be found.
void	SetMaxInstances (uint32_t maxInstances)
	Maximum number of instances to be found.
uint32_t	GetMaxInitialCandidates () const
	Maximum number of initial candidates.
void	SetMaxInitialCandidates (uint32_t maxCandidate)
	Maximum number of initial candidates.
float	GetMinScore () const
	Minimum score of found instances, between [-1.0, 1.0].
void	SetMinScore (float minScore)
	Minimum score of found instances, between [-1.0, 1.0].
float	GetReductionStrength () const
	The reduction strength that is to be used when learning the model, between 0 and 1.
void	SetReductionStrength (float reductionStrength)
	The reduction strength that is to be used when learning the model, between 0 and 1.
uint32_t	GetMinFeaturePoints () const
	Minimum number of feature points at the coarse stage.
void	SetMinFeaturePoints (uint32_t minFeaturePoints)
	Minimum number of feature points at the coarse stage.
uint32_t	GetMaxFeaturePoints () const
	Maximum number of feature points at the fine stage.
void	SetMaxFeaturePoints (uint32_t maxFeaturePoints)
	Maximum number of feature points at the fine stage.
eVision::EPatternType	GetPatternType () const
	Pattern type, as defined in EPatternType.
void	SetPatternType (eVision::EPatternType patternType)
	Pattern type, as defined in EPatternType.
int32_t	GetFindExtension () const
	Extension value, that is the pattern margin size (in pixels) that is allowed to go out of the search field.
void	SetFindExtension (int32_t extension)
	Extension value, that is the pattern margin size (in pixels) that is allowed to go out of the search field.
void	SetLightBalance (float lightBalance)
	Light balance, between [-1.0, 1.0].
float	GetLightBalance () const
	Light balance, between [-1.0, 1.0].
void	SetThinStructureMode (eVision::EThinStructureMode thinStructureMode)
	Mode for EPatternType::EPatternType_ThinStructure, as defined in EThinStructureMode.
eVision::EThinStructureMode	GetThinStructureMode () const
	Mode for EPatternType::EPatternType_ThinStructure, as defined in EThinStructureMode.
void	DrawModel (eVision::EDrawAdapter *graphicContext, float zoomX, float zoomY, float panX, float panY) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModel (eVision::EDrawAdapter *graphicContext, float zoomX, float zoomY, float panX) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModel (eVision::EDrawAdapter *graphicContext, float zoomX, float zoomY) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModel (eVision::EDrawAdapter *graphicContext, float zoomX) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModel (eVision::EDrawAdapter *graphicContext) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModel (eVision::EDrawAdapter *graphicContext, uint32_t learntPatternIndex, float zoomX, float zoomY, float panX, float panY) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModel (eVision::EDrawAdapter *graphicContext, uint32_t learntPatternIndex, float zoomX, float zoomY, float panX) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModel (eVision::EDrawAdapter *graphicContext, uint32_t learntPatternIndex, float zoomX, float zoomY) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModel (eVision::EDrawAdapter *graphicContext, uint32_t learntPatternIndex, float zoomX) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModel (eVision::EDrawAdapter *graphicContext, uint32_t learntPatternIndex) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModel (HDC graphicContext, float zoomX, float zoomY, float panX, float panY) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModel (HDC graphicContext, float zoomX, float zoomY, float panX) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModel (HDC graphicContext, float zoomX, float zoomY) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModel (HDC graphicContext, float zoomX) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModel (HDC graphicContext) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModel (HDC graphicContext, const eVision::ERGBColor &color, float zoomX, float zoomY, float panX, float panY) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModel (HDC graphicContext, const eVision::ERGBColor &color, float zoomX, float zoomY, float panX) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModel (HDC graphicContext, const eVision::ERGBColor &color, float zoomX, float zoomY) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModel (HDC graphicContext, const eVision::ERGBColor &color, float zoomX) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModel (HDC graphicContext, const eVision::ERGBColor &color) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModelWithCurrentPen (HDC graphicContext, float zoomX, float zoomY, float panX, float panY) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModelWithCurrentPen (HDC graphicContext, float zoomX, float zoomY, float panX) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModelWithCurrentPen (HDC graphicContext, float zoomX, float zoomY) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModelWithCurrentPen (HDC graphicContext, float zoomX) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
void	DrawModelWithCurrentPen (HDC graphicContext) const
	Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.
std::vector< eVision::EFindFeaturePoint >	GetFeaturePoints () const
	The feature points used by the model.
std::vector< eVision::EFindFeaturePoint >	GetFeaturePoints (uint32_t learntPatternIndex) const
	The feature points used by the model.
eVision::EPoint	GetPivot () const
	Reference point in the model.
void	SetPivot (const eVision::EPoint &pivot)
	Reference point in the model.
uint64_t	GetLearnTimeOut () const
	Time-out for the EPatternFinder::Learn and EPatternFinder::LearnPatterns methods.
void	SetLearnTimeOut (uint64_t value)
	Time-out for the EPatternFinder::Learn and EPatternFinder::LearnPatterns methods.
uint64_t	GetFindTimeOut () const
	Time-out for the EPatternFinder::Find method.
void	SetFindTimeOut (uint64_t value)
	Time-out for the EPatternFinder::Find method.
void	Save (const std::string &path)
	Loads an EPatternFinder.The given EPatternFinder must have been created for writing.
void	Save (eVision::ESerializer *serializer)
	Loads an EPatternFinder.The given EPatternFinder must have been created for writing.
void	Load (const std::string &path)
	Loads an EPatternFinder.The given EPatternFinder must have been created for reading.
void	Load (eVision::ESerializer *serializer)
	Loads an EPatternFinder.The given EPatternFinder must have been created for reading.
	EPatternFinder (CppWrapperInternal::InternalConstructor)

Public Attributes
CppWrapperInternal::WrappedClass	wrappedClass_

Detailed Description

Manages a complete finding context in EasyFind.

License(s): EasyFind

Constructor & Destructor Documentation

EPatternFinder() [1/3]

eVision::EPatternFinder::EPatternFinder

(

)

Constructs a EPatternFinder::EPatternFinder context.

All properties are initialized to their respective default values.

EPatternFinder() [2/3]

eVision::EPatternFinder::EPatternFinder

(

const eVision::EPatternFinder &

other

)

Constructs a EPatternFinder::EPatternFinder context.

Parameters

other

Another EPatternFinder object to be copied in the new EPatternFinder object.

All properties are initialized to their respective default values.

~EPatternFinder()

eVision::EPatternFinder::~EPatternFinder ( ) throw (  )

virtual

EPatternFinder() [3/3]

eVision::EPatternFinder::EPatternFinder

(

CppWrapperInternal::InternalConstructor

)

Member Function Documentation

CopyLearntPattern() [1/3]

void eVision::EPatternFinder::CopyLearntPattern

(

eVision::EImageBW8 &

image

)

const

Copies the learned pattern in the supplied image. If no pattern has been learned, an exception with code EError::EError_NoPatternLearnt will be thrown.

Parameters

image

Pointer to the image in which the learned pattern will be returned.

CopyLearntPattern() [2/3]

void eVision::EPatternFinder::CopyLearntPattern	(	eVision::EImageBW8 &	image,
		bool	maskWithDontCare ) const

Copies the learned pattern in the supplied image. If no pattern has been learned, an exception with code EError::EError_NoPatternLearnt will be thrown.

Parameters

image	Pointer to the image in which the learned pattern will be returned.
maskWithDontCare	If true and a don't care Area or Region was used when learning, masked pixels will be displayed in black. Default: false.

CopyLearntPattern() [3/3]

void eVision::EPatternFinder::CopyLearntPattern	(	eVision::EImageBW8 &	image,
		bool	maskWithDontCare,
		uint32_t	learntPatternIndex ) const

Copies the learned pattern in the supplied image. If no pattern has been learned, an exception with code EError::EError_NoPatternLearnt will be thrown.

Parameters

image	Pointer to the image in which the learned pattern will be returned.
maskWithDontCare	If true and a don't care Area or Region was used when learning, masked pixels will be displayed in black. Default: false.
learntPatternIndex	Index of the learnt pattern. Default: 0.

DrawModel() [1/20]

void eVision::EPatternFinder::DrawModel

(

eVision::EDrawAdapter *

graphicContext

)

const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext

Handle to the device context of the destination windows.

DrawModel() [2/20]

void eVision::EPatternFinder::DrawModel	(	eVision::EDrawAdapter *	graphicContext,
		float	zoomX ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
zoomX	Horizontal zooming factor.

DrawModel() [3/20]

void eVision::EPatternFinder::DrawModel	(	eVision::EDrawAdapter *	graphicContext,
		float	zoomX,
		float	zoomY ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
zoomX	Horizontal zooming factor.
zoomY	Vertical zooming factor. If set to 0, the horizontal zooming factor will be used for isotropic zooming.

DrawModel() [4/20]

void eVision::EPatternFinder::DrawModel	(	eVision::EDrawAdapter *	graphicContext,
		float	zoomX,
		float	zoomY,
		float	panX ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
zoomX	Horizontal zooming factor.
zoomY	Vertical zooming factor. If set to 0, the horizontal zooming factor will be used for isotropic zooming.
panX	Horizontal panning value expressed in pixels. By default, no panning occurs.

DrawModel() [5/20]

void eVision::EPatternFinder::DrawModel	(	eVision::EDrawAdapter *	graphicContext,
		float	zoomX,
		float	zoomY,
		float	panX,
		float	panY ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
zoomX	Horizontal zooming factor.
zoomY	Vertical zooming factor. If set to 0, the horizontal zooming factor will be used for isotropic zooming.
panX	Horizontal panning value expressed in pixels. By default, no panning occurs.
panY	Vertical panning value expressed in pixels. By default, no panning occurs.

DrawModel() [6/20]

void eVision::EPatternFinder::DrawModel	(	eVision::EDrawAdapter *	graphicContext,
		uint32_t	learntPatternIndex ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
learntPatternIndex	Index of the learnt pattern. Defaults to 0.

DrawModel() [7/20]

void eVision::EPatternFinder::DrawModel	(	eVision::EDrawAdapter *	graphicContext,
		uint32_t	learntPatternIndex,
		float	zoomX ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
learntPatternIndex	Index of the learnt pattern. Defaults to 0.
zoomX	Horizontal zooming factor.

DrawModel() [8/20]

void eVision::EPatternFinder::DrawModel	(	eVision::EDrawAdapter *	graphicContext,
		uint32_t	learntPatternIndex,
		float	zoomX,
		float	zoomY ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
learntPatternIndex	Index of the learnt pattern. Defaults to 0.
zoomX	Horizontal zooming factor.
zoomY	Vertical zooming factor. If set to 0, the horizontal zooming factor will be used for isotropic zooming.

DrawModel() [9/20]

void eVision::EPatternFinder::DrawModel	(	eVision::EDrawAdapter *	graphicContext,
		uint32_t	learntPatternIndex,
		float	zoomX,
		float	zoomY,
		float	panX ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
learntPatternIndex	Index of the learnt pattern. Defaults to 0.
zoomX	Horizontal zooming factor.
zoomY	Vertical zooming factor. If set to 0, the horizontal zooming factor will be used for isotropic zooming.
panX	Horizontal panning value expressed in pixels. By default, no panning occurs.

DrawModel() [10/20]

void eVision::EPatternFinder::DrawModel	(	eVision::EDrawAdapter *	graphicContext,
		uint32_t	learntPatternIndex,
		float	zoomX,
		float	zoomY,
		float	panX,
		float	panY ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
learntPatternIndex	Index of the learnt pattern. Defaults to 0.
zoomX	Horizontal zooming factor.
zoomY	Vertical zooming factor. If set to 0, the horizontal zooming factor will be used for isotropic zooming.
panX	Horizontal panning value expressed in pixels. By default, no panning occurs.
panY	Vertical panning value expressed in pixels. By default, no panning occurs.

DrawModel() [11/20]

void eVision::EPatternFinder::DrawModel

(

HDC

graphicContext

)

const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext

Handle to the device context of the destination windows.

Deprecated

Use the overload taking an EDrawAdapter by using an instance of EWindowsDrawAdapter.

Deprecated in version 23.12. Scheduled to be removed in version 27.6.

DrawModel() [12/20]

void eVision::EPatternFinder::DrawModel	(	HDC	graphicContext,
		const eVision::ERGBColor &	color ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
color	The color in which to draw the overlay.

Deprecated

Use the overload taking an EDrawAdapter by using an instance of EWindowsDrawAdapter.

Deprecated in version 23.12. Scheduled to be removed in version 27.6.

DrawModel() [13/20]

void eVision::EPatternFinder::DrawModel	(	HDC	graphicContext,
		const eVision::ERGBColor &	color,
		float	zoomX ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
color	The color in which to draw the overlay.
zoomX	Horizontal zooming factor.

Deprecated

Use the overload taking an EDrawAdapter by using an instance of EWindowsDrawAdapter.

Deprecated in version 23.12. Scheduled to be removed in version 27.6.

DrawModel() [14/20]

void eVision::EPatternFinder::DrawModel	(	HDC	graphicContext,
		const eVision::ERGBColor &	color,
		float	zoomX,
		float	zoomY ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
color	The color in which to draw the overlay.
zoomX	Horizontal zooming factor.
zoomY	Vertical zooming factor. If set to 0, the horizontal zooming factor will be used for isotropic zooming.

Deprecated

Use the overload taking an EDrawAdapter by using an instance of EWindowsDrawAdapter.

Deprecated in version 23.12. Scheduled to be removed in version 27.6.

DrawModel() [15/20]

void eVision::EPatternFinder::DrawModel	(	HDC	graphicContext,
		const eVision::ERGBColor &	color,
		float	zoomX,
		float	zoomY,
		float	panX ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
color	The color in which to draw the overlay.
zoomX	Horizontal zooming factor.
zoomY	Vertical zooming factor. If set to 0, the horizontal zooming factor will be used for isotropic zooming.
panX	Horizontal panning value expressed in pixels. By default, no panning occurs.

Deprecated

Use the overload taking an EDrawAdapter by using an instance of EWindowsDrawAdapter.

Deprecated in version 23.12. Scheduled to be removed in version 27.6.

DrawModel() [16/20]

void eVision::EPatternFinder::DrawModel	(	HDC	graphicContext,
		const eVision::ERGBColor &	color,
		float	zoomX,
		float	zoomY,
		float	panX,
		float	panY ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
color	The color in which to draw the overlay.
zoomX	Horizontal zooming factor.
zoomY	Vertical zooming factor. If set to 0, the horizontal zooming factor will be used for isotropic zooming.
panX	Horizontal panning value expressed in pixels. By default, no panning occurs.
panY	Vertical panning value expressed in pixels. By default, no panning occurs.

Deprecated

Use the overload taking an EDrawAdapter by using an instance of EWindowsDrawAdapter.

Deprecated in version 23.12. Scheduled to be removed in version 27.6.

DrawModel() [17/20]

void eVision::EPatternFinder::DrawModel	(	HDC	graphicContext,
		float	zoomX ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
zoomX	Horizontal zooming factor.

Deprecated

Use the overload taking an EDrawAdapter by using an instance of EWindowsDrawAdapter.

Deprecated in version 23.12. Scheduled to be removed in version 27.6.

DrawModel() [18/20]

void eVision::EPatternFinder::DrawModel	(	HDC	graphicContext,
		float	zoomX,
		float	zoomY ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
zoomX	Horizontal zooming factor.
zoomY	Vertical zooming factor. If set to 0, the horizontal zooming factor will be used for isotropic zooming.

Deprecated

Use the overload taking an EDrawAdapter by using an instance of EWindowsDrawAdapter.

Deprecated in version 23.12. Scheduled to be removed in version 27.6.

DrawModel() [19/20]

void eVision::EPatternFinder::DrawModel	(	HDC	graphicContext,
		float	zoomX,
		float	zoomY,
		float	panX ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
zoomX	Horizontal zooming factor.
zoomY	Vertical zooming factor. If set to 0, the horizontal zooming factor will be used for isotropic zooming.
panX	Horizontal panning value expressed in pixels. By default, no panning occurs.

Deprecated

Use the overload taking an EDrawAdapter by using an instance of EWindowsDrawAdapter.

Deprecated in version 23.12. Scheduled to be removed in version 27.6.

DrawModel() [20/20]

void eVision::EPatternFinder::DrawModel	(	HDC	graphicContext,
		float	zoomX,
		float	zoomY,
		float	panX,
		float	panY ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
zoomX	Horizontal zooming factor.
zoomY	Vertical zooming factor. If set to 0, the horizontal zooming factor will be used for isotropic zooming.
panX	Horizontal panning value expressed in pixels. By default, no panning occurs.
panY	Vertical panning value expressed in pixels. By default, no panning occurs.

Deprecated

Use the overload taking an EDrawAdapter by using an instance of EWindowsDrawAdapter.

Deprecated in version 23.12. Scheduled to be removed in version 27.6.

DrawModelWithCurrentPen() [1/5]

void eVision::EPatternFinder::DrawModelWithCurrentPen

(

HDC

graphicContext

)

const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext

Handle to the device context of the destination windows.

Deprecated

Deprecated in version 23.12. Scheduled to be removed in version 27.6.

DrawModelWithCurrentPen() [2/5]

void eVision::EPatternFinder::DrawModelWithCurrentPen	(	HDC	graphicContext,
		float	zoomX ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
zoomX	Horizontal zooming factor.

Deprecated

Deprecated in version 23.12. Scheduled to be removed in version 27.6.

DrawModelWithCurrentPen() [3/5]

void eVision::EPatternFinder::DrawModelWithCurrentPen	(	HDC	graphicContext,
		float	zoomX,
		float	zoomY ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
zoomX	Horizontal zooming factor.
zoomY	Vertical zooming factor. If set to 0, the horizontal zooming factor will be used for isotropic zooming.

Deprecated

Deprecated in version 23.12. Scheduled to be removed in version 27.6.

DrawModelWithCurrentPen() [4/5]

void eVision::EPatternFinder::DrawModelWithCurrentPen	(	HDC	graphicContext,
		float	zoomX,
		float	zoomY,
		float	panX ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
zoomX	Horizontal zooming factor.
zoomY	Vertical zooming factor. If set to 0, the horizontal zooming factor will be used for isotropic zooming.
panX	Horizontal panning value expressed in pixels. By default, no panning occurs.

Deprecated

Deprecated in version 23.12. Scheduled to be removed in version 27.6.

DrawModelWithCurrentPen() [5/5]

void eVision::EPatternFinder::DrawModelWithCurrentPen	(	HDC	graphicContext,
		float	zoomX,
		float	zoomY,
		float	panX,
		float	panY ) const

Draws the model features with an overlay in image coordinates. Image coordinates means that we expect to draw in the parent image of the roi given in EPatternFinder::Learn or EPatternFinder::LearnPatterns.

Parameters

graphicContext	Handle to the device context of the destination windows.
zoomX	Horizontal zooming factor.
zoomY	Vertical zooming factor. If set to 0, the horizontal zooming factor will be used for isotropic zooming.
panX	Horizontal panning value expressed in pixels. By default, no panning occurs.
panY	Vertical panning value expressed in pixels. By default, no panning occurs.

Deprecated

Deprecated in version 23.12. Scheduled to be removed in version 27.6.

Find() [1/4]

std::vector< eVision::EFoundPattern > eVision::EPatternFinder::Find

(

eVision::EROIBW8 *

source

)

Locates a set of possible occurrences of the learned pattern in the supplied search field.

Parameters

source

Image or part of an image in which the learned model has to be searched for.

This method will fail if no pattern has been learned previously. The result is a vector of EFoundPattern objects. EFoundPattern instances can be retrieved by using the Vector<>::operator[] method.

Find() [2/4]

std::vector< eVision::EFoundPattern > eVision::EPatternFinder::Find	(	eVision::EROIBW8 *	source,
		const eVision::EFrame &	frame )

Locates a set of possible occurrences of the learned pattern in the supplied search field.

Parameters

source	Image or part of an image in which the learned model has to be searched for.
frame	Frame of the input image.

This method will fail if no pattern has been learned previously. The result is a vector of EFoundPattern objects. EFoundPattern instances can be retrieved by using the Vector<>::operator[] method.

Find() [3/4]

std::vector< eVision::EFoundPattern > eVision::EPatternFinder::Find	(	eVision::EROIBW8 *	source,
		const eVision::ERegion &	region )

Locates a set of possible occurrences of the learned pattern in the supplied search field.

Parameters

source	Image or part of an image in which the learned model has to be searched for.
region	Region into the ROI where the search is performed.

This method will fail if no pattern has been learned previously. The result is a vector of EFoundPattern objects. EFoundPattern instances can be retrieved by using the Vector<>::operator[] method.

Find() [4/4]

std::vector< eVision::EFoundPattern > eVision::EPatternFinder::Find	(	eVision::EROIBW8 *	source,
		const eVision::ERegion &	region,
		const eVision::EFrame &	frame )

Locates a set of possible occurrences of the learned pattern in the supplied search field.

Parameters

source	Image or part of an image in which the learned model has to be searched for.
region	Region into the ROI where the search is performed.
frame	Frame of the input image.

This method will fail if no pattern has been learned previously. The result is a vector of EFoundPattern objects. EFoundPattern instances can be retrieved by using the Vector<>::operator[] method.

GetAngleBias()

float eVision::EPatternFinder::GetAngleBias

(

)

const

Angle bias, expressed in the current angle unit.

The AngleBias defines the angle offset between the model and the instances. Finding the pattern is performed in range AngleBias +/- EPatternFinder::GetAngleTolerance. This range should not exceed a full turn. Default: 0.0.

GetAngleSearchExtent()

int32_t eVision::EPatternFinder::GetAngleSearchExtent

(

)

const

The angular extension of the search neighborhood. Only odd values are allowed for this parameter. See the EPatternFinder::SetLocalSearchMode property description for further details.

GetAngleTolerance()

float eVision::EPatternFinder::GetAngleTolerance

(

)

const

Angle tolerance, expressed in the current angle unit.

The AngleTolerance defines the angle allowance of the instances around the EPatternFinder::GetAngleBias. Finding the pattern is performed in range EPatternFinder::GetAngleBias +/- AngleTolerance. This range should not exceed a full turn. A NULL tolerance can be set, in which case the angle bias value is assumed. Default: 0.0.

GetComputePerFeaturePointScore()

bool eVision::EPatternFinder::GetComputePerFeaturePointScore

(

)

const

Whether the EPatternFinder should compute a score for each feature point. The scores are then displayed as a Red-Yellow-Green colormap by EFoundPattern::Draw. Note that the scores correspond to the Point-By-Point variants of EPatternFinder::GetContrastMode, so if EPatternFinder::GetContrastMode is not a Point-By-Point variant, EFoundPattern::GetScore isn't exactly the average of the displayed scores for each feature point.

GetContrastMode()

eVision::EFindContrastMode eVision::EPatternFinder::GetContrastMode

(

)

const

Contrast of the instance, as defined in EFindContrastMode.

This is a EPatternType::EPatternType_ConsistentEdges pattern type property. It defines the contrast of regions. Contrast can be normal (as in the model), inverse (inverse contrast of the model), or any (same or inverse contrast of the model). Default: EFindContrastMode::EFindContrastMode_Normal.

GetFeaturePoints() [1/2]

std::vector< eVision::EFindFeaturePoint > eVision::EPatternFinder::GetFeaturePoints

(

)

const

The feature points used by the model.

The feature points are expressed with respect to the parent image of the ROI given as input to the EPatternFinder::Learn method.

GetFeaturePoints() [2/2]

std::vector< eVision::EFindFeaturePoint > eVision::EPatternFinder::GetFeaturePoints

(

uint32_t

learntPatternIndex

)

const

The feature points used by the model.

Parameters

learntPatternIndex

Index of the learnt pattern.

The feature points are expressed with respect to the parent image of the ROI given as input to the EPatternFinder::LearnPatterns method.

GetFindExtension()

int32_t eVision::EPatternFinder::GetFindExtension

(

)

const

Extension value, that is the pattern margin size (in pixels) that is allowed to go out of the search field.

When a non-NULL value is attributed to the extension, the detection of instances partially out of the ROI is allowed. The extension value defines how much the ROI is extended. Default: 0.

GetFindTimeOut()

uint64_t eVision::EPatternFinder::GetFindTimeOut

(

)

const

Time-out for the EPatternFinder::Find method.

If the processing time of one of these functions becomes longer than the set time-out, the processing is stopped and an exception is thrown. In that case, the error code of the exception is EError::EError_TimeoutReached.

The time-out is set in microseconds.

This time-out is not a real time-out. The processing is stopped as soon as possible after the time-out has been reached. This means that the time elapsed effectively in the method can be greater than the time-out itself.

GetInterpolate()

bool eVision::EPatternFinder::GetInterpolate

(

)

const

Whether interpolation is performed when searching for a pattern occurrence.

By default, matching is done with a one-pixel precision for all degrees of freedom (translation, rotation and scaling). You can use an additional interpolation process to achieve sub-pixel accuracy. This generally leads to an improvement of the sub-pixel accuracy by a factor larger than 10. This is possible only when the found instances match closely the model. A score higher than 0.99 indicates that the instances are a close match of the model. In other words, the instance is considered to be more accurate when the score is higher. The added computational cost is low. Default: true.

GetLearningDone()

bool eVision::EPatternFinder::GetLearningDone

(

)

const

Indicates whether a pattern has already been learned.

GetLearningHasRegion()

bool eVision::EPatternFinder::GetLearningHasRegion

(

)

const

Indicates whether a ERegion was used alongside the learned pattern. Returns false if no learning was performed.

GetLearnTimeOut()

uint64_t eVision::EPatternFinder::GetLearnTimeOut

(

)

const

Time-out for the EPatternFinder::Learn and EPatternFinder::LearnPatterns methods.

If the processing time of one of these functions becomes longer than the set time-out, the processing is stopped and an exception is thrown. In that case, the error code of the exception is EError::EError_TimeoutReached.

The time-out is set in microseconds.

This time-out is not a real time-out. The processing is stopped as soon as possible after the time-out has been reached. This means that the time elapsed effectively in the method can be greater than the time-out itself.

GetLightBalance()

float eVision::EPatternFinder::GetLightBalance

(

)

const

Light balance, between [-1.0, 1.0].

In the EPatternType::EPatternType_ConsistentEdges and EPatternType::EPatternType_ThinStructure modes, the LightBalance property governs the selection of the feature points while learning the model. It drives which edge points are eligible as feature points in the model, by defining a criterion for ignoring those edge points that are not sharp enough. As a consequence, this property will influence the spatial distribution of the feature points. In the aforementioned operating modes, the feature points are the places in the image that exhibit a strong variation in the gray level signal. Mathematically, these places are those at which the magnitude of the gradient is significant. The LightBalance property defines the way the latter threshold on the magnitude of the gradient is computed, through a careful analysis of the dynamics of gradient. The more the LightBalance tends to -1, the more tolerant will be the threshold, and the more edge points will be considered as candidates for becoming feature points. Conversely, as the LightBalance property becomes close to 1, only the points with a high gradient magnitude are taken into consideration. In other words, a small LightBalance defines a loose criterion for defining what an edge point is, whereas a great value implies a conservative criterion. By default, this property is fixed to 0.0. This is an appropriate value for most images which are encountered in industrial machine vision. The LightBalance is automatically set to 0.0 after a learning process. Once the LightBalance is changed, a new learning process has to be done to take the new value into account. An efficient way to see the effect of changing this property is to use the EPatternFinder::DrawModel method.

GetLocalSearchMode()

eVision::ELocalSearchMode eVision::EPatternFinder::GetLocalSearchMode

(

)

const

Sets the local search mode.

In the multi-stage approach of EasyFind, pattern occurrence candidates are at first found at the coarsest stage. Then, at each of the following stages, their position and score are refined until the last and finest one. This refining is achieved by searching for better candidates in the neighborhood of each of the ones found in the previous stage. The local search mode allows the user to set the extent of this neighborhood. By default, the local search mode is set to ELocalSearchMode::ELocalSearchMode_Basic.

GetMaxFeaturePoints()

uint32_t eVision::EPatternFinder::GetMaxFeaturePoints

(

)

const

Maximum number of feature points at the fine stage.

Default: 1024. Reserved use.

GetMaximumOverlapping()

float eVision::EPatternFinder::GetMaximumOverlapping

(

)

const

Deprecated

Use EPatternFinder::GetMaxOverlap instead.

Deprecated in version 26.6. Scheduled to be removed in version 27.6.

GetMaxInitialCandidates()

uint32_t eVision::EPatternFinder::GetMaxInitialCandidates

(

)

const

Maximum number of initial candidates.

During the search for matching patterns, EasyFind considers a set of candidates that it progressively refines. The maximum number of initial candidates must be greater or equal than the number of instances to be found (see EPatternFinder::GetMaxInstances). A large number of initial candidates can help finding difficult or partial match but at the cost of increasing processing time. A small number can help speeding up the find process. By default, the value for maximum number of initial candidates is 0, indicating that the value is chosen internally.

GetMaxInstances()

uint32_t eVision::EPatternFinder::GetMaxInstances

(

)

const

Maximum number of instances to be found.

Default: 1.

GetMaxOverlap()

float eVision::EPatternFinder::GetMaxOverlap

(

)

const

Overlapping tolerance.

0.0 means all found patterns must be disconnected, 1.0 means they can fully overlap. Default: 1.0.

GetMinFeaturePoints()

uint32_t eVision::EPatternFinder::GetMinFeaturePoints

(

)

const

Minimum number of feature points at the coarse stage.

Default: 8. Reserved use.

GetMinScore()

float eVision::EPatternFinder::GetMinScore

(

)

const

Minimum score of found instances, between [-1.0, 1.0].

Instances with a score under the MinScore will not be returned.

GetNumLearnedPatterns()

uint32_t eVision::EPatternFinder::GetNumLearnedPatterns

(

)

const

Indicates the number of patterns learnt. 0 is returned if no learning was performed.

GetPatternType()

eVision::EPatternType eVision::EPatternFinder::GetPatternType

(

)

const

Pattern type, as defined in EPatternType.

This property informs the EPatternFinder::EPatternFinder of the general nature of the model to be learned. Default: EPatternType::EPatternType_ConsistentEdges.

GetPivot()

eVision::EPoint eVision::EPatternFinder::GetPivot

(

)

const

Reference point in the model.

The coordinates of the reference point are relative to the upper left corner of the model. The location of an instance (Coordinates (X,Y)) is the location of its reference point defined in the model. By default, the pivot is a EPoint set to the pattern center. EPoint is a structure that contains two x and y float values.

GetReductionMode()

eVision::EReductionMode eVision::EPatternFinder::GetReductionMode

(

)

const

The reduction mode that is to be used when learning the model (automatic or manual), as defined in EReductionMode.

Specifies whether the best-guess method should be used to assert the level of reduction that will be used when learning the model. If this property is set to EReductionMode::EReductionMode_Manual, it is up to the user to provide a suitable reduction strength. This value is only used when learning the model. Default: EReductionMode::EReductionMode_Auto, which means that the best-guess algorithm is used by default.

GetReductionStrength()

float eVision::EPatternFinder::GetReductionStrength

(

)

const

The reduction strength that is to be used when learning the model, between 0 and 1.

Specifies the reduction strength for learning the model (encoded as a percentage). Its precise semantics depends on the reduction mode (see the EPatternFinder::GetReductionMode property):

• In the automatic reduction mode, its value is undefined until a model is learned. When a model is learned (i.e. after a call to EPatternFinder::Learn), the value of this property can be read, in which case it reflects the reduction strength that has been automatically chosen by the best-guess algorithm.
• In the manual reduction mode, this property must be set by the user and is kept constant throughout the entire lifetime of the object. The new value of the property is only used at the following call to EPatternFinder::Learn. This value only has an effect when learning the model. Default: The default value depends on the value of the EPatternFinder::GetReductionMode property. Allowed values: Floating-point number in the interval [0..1]. When multiple patterns are learned and reduction mode is automatic, the reduction strength corresponding to the first pattern is returned.

GetScaleBias()

float eVision::EPatternFinder::GetScaleBias

(

)

const

Scale bias, expressed in units (not in percent).

The ScaleBias defines the scale factor between the model and the instances. Finding the pattern is performed in range ScaleBias +/- ScaleTolerance. This range should not exceed [0.5..2.5] (50% to 250% scaling). Default: 1.0 (100%).

GetScaleSearchExtent()

int32_t eVision::EPatternFinder::GetScaleSearchExtent

(

)

const

The scaling extension of the search neighborhood. Only odd values are allowed for this parameter. See the EPatternFinder::SetLocalSearchMode property description for further details.

GetScaleTolerance()

float eVision::EPatternFinder::GetScaleTolerance

(

)

const

Scale tolerance, expressed in units (not in percent).

The ScaleTolerance defines the scale allowance of the instances around the EPatternFinder::GetScaleBias. Finding the pattern is performed in range EPatternFinder::GetScaleBias +/- ScaleTolerance. This range should not exceed [0.5..2] (50 % to 200 % scaling). A NULL tolerance can be set, in which case the scale bias value is assumed. Default: 0.0.

GetThinStructureMode()

eVision::EThinStructureMode eVision::EPatternFinder::GetThinStructureMode

(

)

const

Mode for EPatternType::EPatternType_ThinStructure, as defined in EThinStructureMode.

EThinStructureMode informs EasyFind if thin elements in the model are darker or brighter than regions. Default: EThinStructureMode::EThinStructureMode_Auto, which detects the best mode between dark or bright.

GetXSearchExtent()

int32_t eVision::EPatternFinder::GetXSearchExtent

(

)

const

The X-axis extension of the search neighborhood. Only odd values are allowed for this parameter. See the EPatternFinder::SetLocalSearchMode property description for further details.

GetYSearchExtent()

int32_t eVision::EPatternFinder::GetYSearchExtent

(

)

const

The Y-axis extension of the search neighborhood. Only odd values are allowed for this parameter. See the EPatternFinder::SetLocalSearchMode property description for further details.

Learn() [1/6]

void eVision::EPatternFinder::Learn

(

const eVision::EROIBW8 *

pattern

)

Learns a given pattern and stores it in the EPatternFinder::EPatternFinder object.

Parameters

pattern

Model to be learned (ROI).

Learning another pattern erases the information stored for the first one. A "don't care area" can be set as argument, allowing to mask and not take into account certain parts of the pattern while learning. The "don't care area" mask should have the same size as the pattern or as its eventual parent image. The mask should be a bi-level image with pixel - values of '0' for ignored areas and '255' otherwise.

Learn() [2/6]

void eVision::EPatternFinder::Learn	(	const eVision::EROIBW8 *	pattern,
		const eVision::EFrame &	frame )

Learns a given pattern and stores it in the EPatternFinder::EPatternFinder object.

Parameters

pattern	Model to be learned (ROI).
frame	Reference frame of the learned image

Learning another pattern erases the information stored for the first one. A "don't care area" can be set as argument, allowing to mask and not take into account certain parts of the pattern while learning. The "don't care area" mask should have the same size as the pattern or as its eventual parent image. The mask should be a bi-level image with pixel - values of '0' for ignored areas and '255' otherwise.

Learn() [3/6]

void eVision::EPatternFinder::Learn	(	const eVision::EROIBW8 *	pattern,
		const eVision::ERegion &	region )

Learns a given pattern and stores it in the EPatternFinder::EPatternFinder object.

Parameters

pattern	Model to be learned (ROI).
region	Region into the ROI where the learning is performed

Learning another pattern erases the information stored for the first one. A "don't care area" can be set as argument, allowing to mask and not take into account certain parts of the pattern while learning. The "don't care area" mask should have the same size as the pattern or as its eventual parent image. The mask should be a bi-level image with pixel - values of '0' for ignored areas and '255' otherwise.

Learn() [4/6]

void eVision::EPatternFinder::Learn	(	const eVision::EROIBW8 *	pattern,
		const eVision::ERegion &	region,
		const eVision::EFrame &	frame )

Learns a given pattern and stores it in the EPatternFinder::EPatternFinder object.

Parameters

pattern	Model to be learned (ROI).
region	Region into the ROI where the learning is performed
frame	Reference frame of the learned image

Learning another pattern erases the information stored for the first one. A "don't care area" can be set as argument, allowing to mask and not take into account certain parts of the pattern while learning. The "don't care area" mask should have the same size as the pattern or as its eventual parent image. The mask should be a bi-level image with pixel - values of '0' for ignored areas and '255' otherwise.

Learn() [5/6]

void eVision::EPatternFinder::Learn	(	const eVision::EROIBW8 *	pattern,
		eVision::EROIBW8 *	dontCare )

Learns a given pattern and stores it in the EPatternFinder::EPatternFinder object.

Parameters

pattern	Model to be learned (ROI).
dontCare	"Don't care" area mask (ROI).

Learning another pattern erases the information stored for the first one. A "don't care area" can be set as argument, allowing to mask and not take into account certain parts of the pattern while learning. The "don't care area" mask should have the same size as the pattern or as its eventual parent image. The mask should be a bi-level image with pixel - values of '0' for ignored areas and '255' otherwise.

Deprecated

Use the overload taking an ERegion instead.

Deprecated in version 25.2. Scheduled to be removed in version 27.6.

Learn() [6/6]

void eVision::EPatternFinder::Learn

(

eVision::EVectorModel &

model

)

Learns a given pattern and stores it in the EPatternFinder::EPatternFinder object.

Parameters

model

EVectorModel to be learned.

Learning another pattern erases the information stored for the first one. A "don't care area" can be set as argument, allowing to mask and not take into account certain parts of the pattern while learning. The "don't care area" mask should have the same size as the pattern or as its eventual parent image. The mask should be a bi-level image with pixel - values of '0' for ignored areas and '255' otherwise.

LearnPatterns() [1/12]

void eVision::EPatternFinder::LearnPatterns

(

const std::vector< eVision::EImageBW8 > &

patterns

)

Learns multiple (at least two) patterns.

Parameters

patterns

Vector of models to be learned (ROI).

Learning multiple patterns is useful when your object presents slight variations: shape deformation, lighting, perspective,... Each pattern is Learned and Found independently and only the best patterns are kept. The options of the EPatternFinder are used for all of the patterns. We recommend setting a EPatternFinder::GetMaxOverlap when using this feature.

LearnPatterns() [2/12]

void eVision::EPatternFinder::LearnPatterns	(	const std::vector< eVision::EImageBW8 > &	patterns,
		const eVision::EFrame &	frame )

Learns multiple (at least two) patterns.

Parameters

patterns	Vector of models to be learned (ROI).
frame	Reference frame of the learned image

Learning multiple patterns is useful when your object presents slight variations: shape deformation, lighting, perspective,... Each pattern is Learned and Found independently and only the best patterns are kept. The options of the EPatternFinder are used for all of the patterns. We recommend setting a EPatternFinder::GetMaxOverlap when using this feature.

LearnPatterns() [3/12]

void eVision::EPatternFinder::LearnPatterns	(	const std::vector< eVision::EImageBW8 > &	patterns,
		const std::vector< eVision::ERegion > &	regions )

Learns multiple (at least two) patterns.

Parameters

patterns	Vector of models to be learned (ROI).
regions	Vector of regions into the ROI where the learning is performed

Learning multiple patterns is useful when your object presents slight variations: shape deformation, lighting, perspective,... Each pattern is Learned and Found independently and only the best patterns are kept. The options of the EPatternFinder are used for all of the patterns. We recommend setting a EPatternFinder::GetMaxOverlap when using this feature.

LearnPatterns() [4/12]

void eVision::EPatternFinder::LearnPatterns	(	const std::vector< eVision::EImageBW8 > &	patterns,
		const std::vector< eVision::ERegion > &	regions,
		const eVision::EFrame &	frame )

Learns multiple (at least two) patterns.

Parameters

patterns	Vector of models to be learned (ROI).
regions	Vector of regions into the ROI where the learning is performed
frame	Reference frame of the learned image

Learning multiple patterns is useful when your object presents slight variations: shape deformation, lighting, perspective,... Each pattern is Learned and Found independently and only the best patterns are kept. The options of the EPatternFinder are used for all of the patterns. We recommend setting a EPatternFinder::GetMaxOverlap when using this feature.

LearnPatterns() [5/12]

void eVision::EPatternFinder::LearnPatterns

(

const std::vector< eVision::EROIBW8 * > &

patterns

)

Learns multiple (at least two) patterns.

Parameters

patterns

Vector of models to be learned (ROI).

Learning multiple patterns is useful when your object presents slight variations: shape deformation, lighting, perspective,... Each pattern is Learned and Found independently and only the best patterns are kept. The options of the EPatternFinder are used for all of the patterns. We recommend setting a EPatternFinder::GetMaxOverlap when using this feature.

LearnPatterns() [6/12]

void eVision::EPatternFinder::LearnPatterns	(	const std::vector< eVision::EROIBW8 * > &	patterns,
		const eVision::EFrame &	frame )

Learns multiple (at least two) patterns.

Parameters

patterns	Vector of models to be learned (ROI).
frame	Reference frame of the learned image

Learning multiple patterns is useful when your object presents slight variations: shape deformation, lighting, perspective,... Each pattern is Learned and Found independently and only the best patterns are kept. The options of the EPatternFinder are used for all of the patterns. We recommend setting a EPatternFinder::GetMaxOverlap when using this feature.

LearnPatterns() [7/12]

void eVision::EPatternFinder::LearnPatterns	(	const std::vector< eVision::EROIBW8 * > &	patterns,
		const std::vector< eVision::ERegion * > &	regions )

Learns multiple (at least two) patterns.

Parameters

patterns	Vector of models to be learned (ROI).
regions	Vector of regions into the ROI where the learning is performed

Learning multiple patterns is useful when your object presents slight variations: shape deformation, lighting, perspective,... Each pattern is Learned and Found independently and only the best patterns are kept. The options of the EPatternFinder are used for all of the patterns. We recommend setting a EPatternFinder::GetMaxOverlap when using this feature.

LearnPatterns() [8/12]

void eVision::EPatternFinder::LearnPatterns	(	const std::vector< eVision::EROIBW8 * > &	patterns,
		const std::vector< eVision::ERegion * > &	regions,
		const eVision::EFrame &	frame )

Learns multiple (at least two) patterns.

Parameters

patterns	Vector of models to be learned (ROI).
regions	Vector of regions into the ROI where the learning is performed
frame	Reference frame of the learned image

Learning multiple patterns is useful when your object presents slight variations: shape deformation, lighting, perspective,... Each pattern is Learned and Found independently and only the best patterns are kept. The options of the EPatternFinder are used for all of the patterns. We recommend setting a EPatternFinder::GetMaxOverlap when using this feature.

LearnPatterns() [9/12]

void eVision::EPatternFinder::LearnPatterns

(

const std::vector< eVision::EROIBW8 > &

patterns

)

Learns multiple (at least two) patterns.

Parameters

patterns

Vector of models to be learned (ROI).

Learning multiple patterns is useful when your object presents slight variations: shape deformation, lighting, perspective,... Each pattern is Learned and Found independently and only the best patterns are kept. The options of the EPatternFinder are used for all of the patterns. We recommend setting a EPatternFinder::GetMaxOverlap when using this feature.

LearnPatterns() [10/12]

void eVision::EPatternFinder::LearnPatterns	(	const std::vector< eVision::EROIBW8 > &	patterns,
		const eVision::EFrame &	frame )

Learns multiple (at least two) patterns.

Parameters

patterns	Vector of models to be learned (ROI).
frame	Reference frame of the learned image

Learning multiple patterns is useful when your object presents slight variations: shape deformation, lighting, perspective,... Each pattern is Learned and Found independently and only the best patterns are kept. The options of the EPatternFinder are used for all of the patterns. We recommend setting a EPatternFinder::GetMaxOverlap when using this feature.

LearnPatterns() [11/12]

void eVision::EPatternFinder::LearnPatterns	(	const std::vector< eVision::EROIBW8 > &	patterns,
		const std::vector< eVision::ERegion > &	regions )

Learns multiple (at least two) patterns.

Parameters

patterns	Vector of models to be learned (ROI).
regions	Vector of regions into the ROI where the learning is performed

Learning multiple patterns is useful when your object presents slight variations: shape deformation, lighting, perspective,... Each pattern is Learned and Found independently and only the best patterns are kept. The options of the EPatternFinder are used for all of the patterns. We recommend setting a EPatternFinder::GetMaxOverlap when using this feature.

LearnPatterns() [12/12]

void eVision::EPatternFinder::LearnPatterns	(	const std::vector< eVision::EROIBW8 > &	patterns,
		const std::vector< eVision::ERegion > &	regions,
		const eVision::EFrame &	frame )

Learns multiple (at least two) patterns.

Parameters

patterns	Vector of models to be learned (ROI).
regions	Vector of regions into the ROI where the learning is performed
frame	Reference frame of the learned image

Learning multiple patterns is useful when your object presents slight variations: shape deformation, lighting, perspective,... Each pattern is Learned and Found independently and only the best patterns are kept. The options of the EPatternFinder are used for all of the patterns. We recommend setting a EPatternFinder::GetMaxOverlap when using this feature.

Load() [1/2]

void eVision::EPatternFinder::Load

(

const std::string &

path

)

Loads an EPatternFinder.The given EPatternFinder must have been created for reading.

Parameters

path	The file path.

Load() [2/2]

void eVision::EPatternFinder::Load

(

eVision::ESerializer *

serializer

)

Loads an EPatternFinder.The given EPatternFinder must have been created for reading.

Parameters

serializer

Pointer to the ESerializer created for reading.

operator=()

eVision::EPatternFinder & eVision::EPatternFinder::operator=

(

const eVision::EPatternFinder &

other

)

Assignment operator.

Parameters

other

The other EPatternFinder that we will copy into this one.

Save() [1/2]

void eVision::EPatternFinder::Save

(

const std::string &

path

)

Loads an EPatternFinder.The given EPatternFinder must have been created for writing.

Parameters

path	The file path.

Save() [2/2]

void eVision::EPatternFinder::Save

(

eVision::ESerializer *

serializer

)

Loads an EPatternFinder.The given EPatternFinder must have been created for writing.

Parameters

serializer

Pointer to the ESerializer created for writing.

SetAngleBias()

void eVision::EPatternFinder::SetAngleBias

(

float

angleBias

)

Angle bias, expressed in the current angle unit.

The AngleBias defines the angle offset between the model and the instances. Finding the pattern is performed in range AngleBias +/- EPatternFinder::GetAngleTolerance. This range should not exceed a full turn. Default: 0.0.

SetAngleSearchExtent()

void eVision::EPatternFinder::SetAngleSearchExtent

(

int32_t

extent

)

The angular extension of the search neighborhood. Only odd values are allowed for this parameter. See the EPatternFinder::SetLocalSearchMode property description for further details.

SetAngleTolerance()

void eVision::EPatternFinder::SetAngleTolerance

(

float

angleTolerance

)

Angle tolerance, expressed in the current angle unit.

The AngleTolerance defines the angle allowance of the instances around the EPatternFinder::GetAngleBias. Finding the pattern is performed in range EPatternFinder::GetAngleBias +/- AngleTolerance. This range should not exceed a full turn. A NULL tolerance can be set, in which case the angle bias value is assumed. Default: 0.0.

SetComputePerFeaturePointScore()

void eVision::EPatternFinder::SetComputePerFeaturePointScore

(

bool

compute

)

Whether the EPatternFinder should compute a score for each feature point. The scores are then displayed as a Red-Yellow-Green colormap by EFoundPattern::Draw. Note that the scores correspond to the Point-By-Point variants of EPatternFinder::GetContrastMode, so if EPatternFinder::GetContrastMode is not a Point-By-Point variant, EFoundPattern::GetScore isn't exactly the average of the displayed scores for each feature point.

SetContrastMode()

void eVision::EPatternFinder::SetContrastMode

(

eVision::EFindContrastMode

eContrastMode

)

Contrast of the instance, as defined in EFindContrastMode.

This is a EPatternType::EPatternType_ConsistentEdges pattern type property. It defines the contrast of regions. Contrast can be normal (as in the model), inverse (inverse contrast of the model), or any (same or inverse contrast of the model). Default: EFindContrastMode::EFindContrastMode_Normal.

SetFindExtension()

void eVision::EPatternFinder::SetFindExtension

(

int32_t

extension

)

Extension value, that is the pattern margin size (in pixels) that is allowed to go out of the search field.

When a non-NULL value is attributed to the extension, the detection of instances partially out of the ROI is allowed. The extension value defines how much the ROI is extended. Default: 0.

SetFindTimeOut()

void eVision::EPatternFinder::SetFindTimeOut

(

uint64_t

value

)

Time-out for the EPatternFinder::Find method.

If the processing time of one of these functions becomes longer than the set time-out, the processing is stopped and an exception is thrown. In that case, the error code of the exception is EError::EError_TimeoutReached.

The time-out is set in microseconds.

This time-out is not a real time-out. The processing is stopped as soon as possible after the time-out has been reached. This means that the time elapsed effectively in the method can be greater than the time-out itself.

SetInterpolate()

void eVision::EPatternFinder::SetInterpolate

(

bool

interpolate

)

Whether interpolation is performed when searching for a pattern occurrence.

By default, matching is done with a one-pixel precision for all degrees of freedom (translation, rotation and scaling). You can use an additional interpolation process to achieve sub-pixel accuracy. This generally leads to an improvement of the sub-pixel accuracy by a factor larger than 10. This is possible only when the found instances match closely the model. A score higher than 0.99 indicates that the instances are a close match of the model. In other words, the instance is considered to be more accurate when the score is higher. The added computational cost is low. Default: true.

SetLearnTimeOut()

void eVision::EPatternFinder::SetLearnTimeOut

(

uint64_t

value

)

Time-out for the EPatternFinder::Learn and EPatternFinder::LearnPatterns methods.

If the processing time of one of these functions becomes longer than the set time-out, the processing is stopped and an exception is thrown. In that case, the error code of the exception is EError::EError_TimeoutReached.

The time-out is set in microseconds.

This time-out is not a real time-out. The processing is stopped as soon as possible after the time-out has been reached. This means that the time elapsed effectively in the method can be greater than the time-out itself.

SetLightBalance()

void eVision::EPatternFinder::SetLightBalance

(

float

lightBalance

)

Light balance, between [-1.0, 1.0].

In the EPatternType::EPatternType_ConsistentEdges and EPatternType::EPatternType_ThinStructure modes, the LightBalance property governs the selection of the feature points while learning the model. It drives which edge points are eligible as feature points in the model, by defining a criterion for ignoring those edge points that are not sharp enough. As a consequence, this property will influence the spatial distribution of the feature points. In the aforementioned operating modes, the feature points are the places in the image that exhibit a strong variation in the gray level signal. Mathematically, these places are those at which the magnitude of the gradient is significant. The LightBalance property defines the way the latter threshold on the magnitude of the gradient is computed, through a careful analysis of the dynamics of gradient. The more the LightBalance tends to -1, the more tolerant will be the threshold, and the more edge points will be considered as candidates for becoming feature points. Conversely, as the LightBalance property becomes close to 1, only the points with a high gradient magnitude are taken into consideration. In other words, a small LightBalance defines a loose criterion for defining what an edge point is, whereas a great value implies a conservative criterion. By default, this property is fixed to 0.0. This is an appropriate value for most images which are encountered in industrial machine vision. The LightBalance is automatically set to 0.0 after a learning process. Once the LightBalance is changed, a new learning process has to be done to take the new value into account. An efficient way to see the effect of changing this property is to use the EPatternFinder::DrawModel method.

SetLocalSearchMode()

void eVision::EPatternFinder::SetLocalSearchMode

(

eVision::ELocalSearchMode

eLocalSearchMode

)

Sets the local search mode.

In the multi-stage approach of EasyFind, pattern occurrence candidates are at first found at the coarsest stage. Then, at each of the following stages, their position and score are refined until the last and finest one. This refining is achieved by searching for better candidates in the neighborhood of each of the ones found in the previous stage. The local search mode allows the user to set the extent of this neighborhood. By default, the local search mode is set to ELocalSearchMode::ELocalSearchMode_Basic.

SetMaxFeaturePoints()

void eVision::EPatternFinder::SetMaxFeaturePoints

(

uint32_t

maxFeaturePoints

)

Maximum number of feature points at the fine stage.

Default: 1024. Reserved use.

SetMaximumOverlapping()

void eVision::EPatternFinder::SetMaximumOverlapping

(

float

maximumOverlapping

)

Deprecated

Use EPatternFinder::GetMaxOverlap instead.

Deprecated in version 26.6. Scheduled to be removed in version 27.6.

SetMaxInitialCandidates()

void eVision::EPatternFinder::SetMaxInitialCandidates

(

uint32_t

maxCandidate

)

Maximum number of initial candidates.

Parameters

maxCandidate

The maximum number of initial candidates (default is 0).

During the search for matching patterns, EasyFind considers a set of candidates that it progressively refines. The maximum number of initial candidates must be greater or equal than the number of instances to be found (see EPatternFinder::GetMaxInstances). A large number of initial candidates can help finding difficult or partial match but at the cost of increasing processing time. A small number can help speeding up the find process. By default, the value for maximum number of initial candidates is 0, indicating that the value is chosen internally.

SetMaxInstances()

void eVision::EPatternFinder::SetMaxInstances

(

uint32_t

maxInstances

)

Maximum number of instances to be found.

Default: 1.

SetMaxOverlap()

void eVision::EPatternFinder::SetMaxOverlap

(

float

maxOverlap

)

Overlapping tolerance.

0.0 means all found patterns must be disconnected, 1.0 means they can fully overlap. Default: 1.0.

SetMinFeaturePoints()

void eVision::EPatternFinder::SetMinFeaturePoints

(

uint32_t

minFeaturePoints

)

Minimum number of feature points at the coarse stage.

Default: 8. Reserved use.

SetMinScore()

void eVision::EPatternFinder::SetMinScore

(

float

minScore

)

Minimum score of found instances, between [-1.0, 1.0].

Instances with a score under the MinScore will not be returned.

SetPatternType()

void eVision::EPatternFinder::SetPatternType

(

eVision::EPatternType

patternType

)

Pattern type, as defined in EPatternType.

This property informs the EPatternFinder::EPatternFinder of the general nature of the model to be learned. Default: EPatternType::EPatternType_ConsistentEdges.

SetPivot()

void eVision::EPatternFinder::SetPivot

(

const eVision::EPoint &

pivot

)

Reference point in the model.

The coordinates of the reference point are relative to the upper left corner of the model. The location of an instance (Coordinates (X,Y)) is the location of its reference point defined in the model. By default, the pivot is a EPoint set to the pattern center. EPoint is a structure that contains two x and y float values.

SetReductionMode()

void eVision::EPatternFinder::SetReductionMode

(

eVision::EReductionMode

eReductionMode

)

The reduction mode that is to be used when learning the model (automatic or manual), as defined in EReductionMode.

Specifies whether the best-guess method should be used to assert the level of reduction that will be used when learning the model. If this property is set to EReductionMode::EReductionMode_Manual, it is up to the user to provide a suitable reduction strength. This value is only used when learning the model. Default: EReductionMode::EReductionMode_Auto, which means that the best-guess algorithm is used by default.

SetReductionStrength()

void eVision::EPatternFinder::SetReductionStrength

(

float

reductionStrength

)

The reduction strength that is to be used when learning the model, between 0 and 1.

Specifies the reduction strength for learning the model (encoded as a percentage). Its precise semantics depends on the reduction mode (see the EPatternFinder::GetReductionMode property):

• In the automatic reduction mode, its value is undefined until a model is learned. When a model is learned (i.e. after a call to EPatternFinder::Learn), the value of this property can be read, in which case it reflects the reduction strength that has been automatically chosen by the best-guess algorithm.
• In the manual reduction mode, this property must be set by the user and is kept constant throughout the entire lifetime of the object. The new value of the property is only used at the following call to EPatternFinder::Learn. This value only has an effect when learning the model. Default: The default value depends on the value of the EPatternFinder::GetReductionMode property. Allowed values: Floating-point number in the interval [0..1]. When multiple patterns are learned and reduction mode is automatic, the reduction strength corresponding to the first pattern is returned.

SetScaleBias()

void eVision::EPatternFinder::SetScaleBias

(

float

scaleBias

)

Scale bias, expressed in units (not in percent).

The ScaleBias defines the scale factor between the model and the instances. Finding the pattern is performed in range ScaleBias +/- ScaleTolerance. This range should not exceed [0.5..2.5] (50% to 250% scaling). Default: 1.0 (100%).

SetScaleSearchExtent()

void eVision::EPatternFinder::SetScaleSearchExtent

(

int32_t

extent

)

The scaling extension of the search neighborhood. Only odd values are allowed for this parameter. See the EPatternFinder::SetLocalSearchMode property description for further details.

SetScaleTolerance()

void eVision::EPatternFinder::SetScaleTolerance

(

float

scaleTolerance

)

Scale tolerance, expressed in units (not in percent).

The ScaleTolerance defines the scale allowance of the instances around the EPatternFinder::GetScaleBias. Finding the pattern is performed in range EPatternFinder::GetScaleBias +/- ScaleTolerance. This range should not exceed [0.5..2] (50 % to 200 % scaling). A NULL tolerance can be set, in which case the scale bias value is assumed. Default: 0.0.

SetThinStructureMode()

void eVision::EPatternFinder::SetThinStructureMode

(

eVision::EThinStructureMode

thinStructureMode

)

Mode for EPatternType::EPatternType_ThinStructure, as defined in EThinStructureMode.

EThinStructureMode informs EasyFind if thin elements in the model are darker or brighter than regions. Default: EThinStructureMode::EThinStructureMode_Auto, which detects the best mode between dark or bright.

SetXSearchExtent()

void eVision::EPatternFinder::SetXSearchExtent

(

int32_t

extent

)

The X-axis extension of the search neighborhood. Only odd values are allowed for this parameter. See the EPatternFinder::SetLocalSearchMode property description for further details.

SetYSearchExtent()

void eVision::EPatternFinder::SetYSearchExtent

(

int32_t

extent

)

The Y-axis extension of the search neighborhood. Only odd values are allowed for this parameter. See the EPatternFinder::SetLocalSearchMode property description for further details.

Member Data Documentation

wrappedClass_

CppWrapperInternal::WrappedClass eVision::EPatternFinder::wrappedClass_