Name
find_planar_uncalib_deformable_modelT_find_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModel — Find the best matches of a planar projective invariant deformable model
in an image.
find_planar_uncalib_deformable_model(Image : : ModelID, AngleStart, AngleExtent, ScaleRMin, ScaleRMax, ScaleCMin, ScaleCMax, MinScore, NumMatches, MaxOverlap, NumLevels, Greediness, ParamName, ParamValue : HomMat2D, Score)
Herror T_find_planar_uncalib_deformable_model(const Hobject Image, const Htuple ModelID, const Htuple AngleStart, const Htuple AngleExtent, const Htuple ScaleRMin, const Htuple ScaleRMax, const Htuple ScaleCMin, const Htuple ScaleCMax, const Htuple MinScore, const Htuple NumMatches, const Htuple MaxOverlap, const Htuple NumLevels, const Htuple Greediness, const Htuple ParamName, const Htuple ParamValue, Htuple* HomMat2D, Htuple* Score)
Herror find_planar_uncalib_deformable_model(Hobject Image, const HTuple& ModelID, const HTuple& AngleStart, const HTuple& AngleExtent, const HTuple& ScaleRMin, const HTuple& ScaleRMax, const HTuple& ScaleCMin, const HTuple& ScaleCMax, const HTuple& MinScore, const HTuple& NumMatches, const HTuple& MaxOverlap, const HTuple& NumLevels, const HTuple& Greediness, const HTuple& ParamName, const HTuple& ParamValue, HTuple* HomMat2D, HTuple* Score)
HTuple HImage::FindPlanarUncalibDeformableModel(const HDeformableModel& ModelID, const HTuple& AngleStart, const HTuple& AngleExtent, const HTuple& ScaleRMin, const HTuple& ScaleRMax, const HTuple& ScaleCMin, const HTuple& ScaleCMax, const HTuple& MinScore, const HTuple& NumMatches, const HTuple& MaxOverlap, const HTuple& NumLevels, const HTuple& Greediness, const HTuple& ParamName, const HTuple& ParamValue, HTuple* Score) const
HTuple HDeformableModel::FindPlanarUncalibDeformableModel(const HImage& Image, const HTuple& AngleStart, const HTuple& AngleExtent, const HTuple& ScaleRMin, const HTuple& ScaleRMax, const HTuple& ScaleCMin, const HTuple& ScaleCMax, const HTuple& MinScore, const HTuple& NumMatches, const HTuple& MaxOverlap, const HTuple& NumLevels, const HTuple& Greediness, const HTuple& ParamName, const HTuple& ParamValue, HTuple* Score) const
void FindPlanarUncalibDeformableModel(const HObject& Image, const HTuple& ModelID, const HTuple& AngleStart, const HTuple& AngleExtent, const HTuple& ScaleRMin, const HTuple& ScaleRMax, const HTuple& ScaleCMin, const HTuple& ScaleCMax, const HTuple& MinScore, const HTuple& NumMatches, const HTuple& MaxOverlap, const HTuple& NumLevels, const HTuple& Greediness, const HTuple& ParamName, const HTuple& ParamValue, HTuple* HomMat2D, HTuple* Score)
HHomMat2DArray HDeformableModel::FindPlanarUncalibDeformableModel(const HImage& Image, double AngleStart, double AngleExtent, double ScaleRMin, double ScaleRMax, double ScaleCMin, double ScaleCMax, double MinScore, Hlong NumMatches, double MaxOverlap, const HTuple& NumLevels, double Greediness, const HTuple& ParamName, const HTuple& ParamValue, HTuple* Score) const
HHomMat2D HDeformableModel::FindPlanarUncalibDeformableModel(const HImage& Image, double AngleStart, double AngleExtent, double ScaleRMin, double ScaleRMax, double ScaleCMin, double ScaleCMax, double MinScore, Hlong NumMatches, double MaxOverlap, Hlong NumLevels, double Greediness, const HTuple& ParamName, const HTuple& ParamValue, HTuple* Score) const
HHomMat2DArray HImage::FindPlanarUncalibDeformableModel(const HDeformableModel& ModelID, double AngleStart, double AngleExtent, double ScaleRMin, double ScaleRMax, double ScaleCMin, double ScaleCMax, double MinScore, Hlong NumMatches, double MaxOverlap, const HTuple& NumLevels, double Greediness, const HTuple& ParamName, const HTuple& ParamValue, HTuple* Score) const
HHomMat2D HImage::FindPlanarUncalibDeformableModel(const HDeformableModel& ModelID, double AngleStart, double AngleExtent, double ScaleRMin, double ScaleRMax, double ScaleCMin, double ScaleCMax, double MinScore, Hlong NumMatches, double MaxOverlap, Hlong NumLevels, double Greediness, const HTuple& ParamName, const HTuple& ParamValue, HTuple* Score) const
void HOperatorSetX.FindPlanarUncalibDeformableModel(
[in] IHUntypedObjectX* Image, [in] VARIANT ModelID, [in] VARIANT AngleStart, [in] VARIANT AngleExtent, [in] VARIANT ScaleRMin, [in] VARIANT ScaleRMax, [in] VARIANT ScaleCMin, [in] VARIANT ScaleCMax, [in] VARIANT MinScore, [in] VARIANT NumMatches, [in] VARIANT MaxOverlap, [in] VARIANT NumLevels, [in] VARIANT Greediness, [in] VARIANT ParamName, [in] VARIANT ParamValue, [out] VARIANT* HomMat2d, [out] VARIANT* Score)
IHHomMat2DX* HDeformableModelX.FindPlanarUncalibDeformableModel(
[in] IHImageX* Image, [in] double AngleStart, [in] double AngleExtent, [in] double ScaleRMin, [in] double ScaleRMax, [in] double ScaleCMin, [in] double ScaleCMax, [in] double MinScore, [in] Hlong NumMatches, [in] double MaxOverlap, [in] VARIANT NumLevels, [in] double Greediness, [in] VARIANT ParamName, [in] VARIANT ParamValue, [out] VARIANT* Score)
IHHomMat2DX* HImageX.FindPlanarUncalibDeformableModel(
[in] IHDeformableModelX* ModelID, [in] double AngleStart, [in] double AngleExtent, [in] double ScaleRMin, [in] double ScaleRMax, [in] double ScaleCMin, [in] double ScaleCMax, [in] double MinScore, [in] Hlong NumMatches, [in] double MaxOverlap, [in] VARIANT NumLevels, [in] double Greediness, [in] VARIANT ParamName, [in] VARIANT ParamValue, [out] VARIANT* Score)
static void HOperatorSet.FindPlanarUncalibDeformableModel(HObject image, HTuple modelID, HTuple angleStart, HTuple angleExtent, HTuple scaleRMin, HTuple scaleRMax, HTuple scaleCMin, HTuple scaleCMax, HTuple minScore, HTuple numMatches, HTuple maxOverlap, HTuple numLevels, HTuple greediness, HTuple paramName, HTuple paramValue, out HTuple homMat2D, out HTuple score)
HHomMat2D[] HDeformableModel.FindPlanarUncalibDeformableModel(HImage image, double angleStart, double angleExtent, double scaleRMin, double scaleRMax, double scaleCMin, double scaleCMax, double minScore, int numMatches, double maxOverlap, HTuple numLevels, double greediness, HTuple paramName, HTuple paramValue, out HTuple score)
HHomMat2D HDeformableModel.FindPlanarUncalibDeformableModel(HImage image, double angleStart, double angleExtent, double scaleRMin, double scaleRMax, double scaleCMin, double scaleCMax, double minScore, int numMatches, double maxOverlap, int numLevels, double greediness, HTuple paramName, HTuple paramValue, out HTuple score)
HHomMat2D[] HImage.FindPlanarUncalibDeformableModel(HDeformableModel modelID, double angleStart, double angleExtent, double scaleRMin, double scaleRMax, double scaleCMin, double scaleCMax, double minScore, int numMatches, double maxOverlap, HTuple numLevels, double greediness, HTuple paramName, HTuple paramValue, out HTuple score)
HHomMat2D HImage.FindPlanarUncalibDeformableModel(HDeformableModel modelID, double angleStart, double angleExtent, double scaleRMin, double scaleRMax, double scaleCMin, double scaleCMax, double minScore, int numMatches, double maxOverlap, int numLevels, double greediness, HTuple paramName, HTuple paramValue, out HTuple score)
The operator find_planar_uncalib_deformable_modelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModel finds the best
NumMatchesNumMatchesNumMatchesNumMatchesNumMatchesnumMatches instances of the perspectively distorted deformable
model ModelIDModelIDModelIDModelIDModelIDmodelID in the input image ImageImageImageImageImageimage. The
model must have been created previously by calling
create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModel or
read_deformable_modelread_deformable_modelReadDeformableModelread_deformable_modelReadDeformableModelReadDeformableModel.
The projective transformation (homographies) that encode the position of the
found instances of the model are returned in HomMat2DHomMat2DHomMat2DHomMat2DHomMat2DhomMat2D. In case that
multiple objects are found, the different homographies are concatenated. A
single homography can easily be extracted by tuple_select_range(HomMat2D,Index*9,(Index+1)*9-1,
SelectedHomMat2D). The different detection results are sorted in decreasing
order of ScoreScoreScoreScoreScorescore.
The row and column coordinates are
the coordinates of the origin of the deformable model in the search image,
which can be found by calling
projective_trans_pixel(HomMat2D,0,0,Row,Column). By default, the
origin is the center of gravity of the domain (region) of the image that was
used to create the deformable model with
create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModel. A different origin
can be set with set_deformable_model_originset_deformable_model_originSetDeformableModelOriginset_deformable_model_originSetDeformableModelOriginSetDeformableModelOrigin.
For visualization purposes, the model contours that are extracted by
get_deformable_model_contoursget_deformable_model_contoursGetDeformableModelContoursget_deformable_model_contoursGetDeformableModelContoursGetDeformableModelContours can be projected to the
found location given HomMat2DHomMat2DHomMat2DHomMat2DHomMat2DhomMat2D with
projective_trans_contour_xldprojective_trans_contour_xldProjectiveTransContourXldprojective_trans_contour_xldProjectiveTransContourXldProjectiveTransContourXld.
Additionally, the score of each found instance is returned in ScoreScoreScoreScoreScorescore.
The score is a number between 0 and 1, which is an approximate measure of how
much of the model is visible in the image. If, for example, half of the
model is occluded, the score cannot exceed 0.5.
The domain of the image ImageImageImageImageImageimage determines the search space
for the reference point of the model, i.e., for the center of
gravity of the domain (region) of the image that was used to create
the deformable model with create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModel.
A different origin set with set_deformable_model_originset_deformable_model_originSetDeformableModelOriginset_deformable_model_originSetDeformableModelOriginSetDeformableModelOrigin is not taken
into account. The model is searched within those points of the domain of
the image, in which the model lies completely within the image.
This means that the model will not be found if it extends beyond the
borders of the image, even if it would achieve a score greater than
MinScoreMinScoreMinScoreMinScoreMinScoreminScore (see below). This behavior can be changed with
set_system('border_shape_models','true'), which will cause
models that extend beyond the image border to be found if they
achieve a score greater than MinScoreMinScoreMinScoreMinScoreMinScoreminScore. Here, points lying
outside the image are regarded as being occluded, i.e., they lower
the score. It should be noted that the runtime of the search will
increase in this mode.
The range parameters AngleStartAngleStartAngleStartAngleStartAngleStartangleStart, AngleExtentAngleExtentAngleExtentAngleExtentAngleExtentangleExtent,
ScaleRMinScaleRMinScaleRMinScaleRMinScaleRMinscaleRMin, ScaleRMaxScaleRMaxScaleRMaxScaleRMaxScaleRMaxscaleRMax, ScaleCMinScaleCMinScaleCMinScaleCMinScaleCMinscaleCMin and
ScaleCMaxScaleCMaxScaleCMaxScaleCMaxScaleCMaxscaleCMax are used to specify a basic range of up to an anisotropic
transformation that is exhaustively searched on the top level of the image
pyramid. The operator find_planar_uncalib_deformable_modelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModel finds
objects outside this range, e.g., even when the object is perspectively
distorted. Hence, the range parameters are a kind of suggestion for the
search algorithm, and starting from there a certain bigger range can be
detected that depends on the pyramid levels that are used, but also on the
model/image content. Often, it is not necessary to use an anisotropic
scaling to find the object. In these cases, ScaleCMinScaleCMinScaleCMinScaleCMinScaleCMinscaleCMin and
ScaleCMaxScaleCMaxScaleCMaxScaleCMaxScaleCMaxscaleCMax should be set to 1. The search is then performed
with isotropic scaling only, which is much faster.
The parameter MinScoreMinScoreMinScoreMinScoreMinScoreminScore determines what score a potential
match must at least have to be regarded as an instance of the model
in the image. The larger MinScoreMinScoreMinScoreMinScoreMinScoreminScore is chosen, the faster
the search is. If the model can be expected never to be occluded in
the images, MinScoreMinScoreMinScoreMinScoreMinScoreminScore may be set as high as 0.8 or even 0.9.
The maximum number of instances to be found can be determined with
NumMatchesNumMatchesNumMatchesNumMatchesNumMatchesnumMatches. If more than NumMatchesNumMatchesNumMatchesNumMatchesNumMatchesnumMatches instances
with a score greater than MinScoreMinScoreMinScoreMinScoreMinScoreminScore are found in the image,
only the best NumMatchesNumMatchesNumMatchesNumMatchesNumMatchesnumMatches instances are returned. If fewer
than NumMatchesNumMatchesNumMatchesNumMatchesNumMatchesnumMatches are found, only that number is returned,
i.e., the parameter MinScoreMinScoreMinScoreMinScoreMinScoreminScore takes precedence over
NumMatchesNumMatchesNumMatchesNumMatchesNumMatchesnumMatches. If all model instances exceeding
MinScoreMinScoreMinScoreMinScoreMinScoreminScore in the image should be found, NumMatchesNumMatchesNumMatchesNumMatchesNumMatchesnumMatches
must be set to 0.
In rare cases, NumMatchesNumMatchesNumMatchesNumMatchesNumMatchesnumMatches must be set to a
higher value than the required number of matches. This is
the case if, for instance, a small MinScoreMinScoreMinScoreMinScoreMinScoreminScore is set.
If the model exhibits symmetries it may happen that multiple
instances with similar positions but different rotations are found
in the image. The parameter MaxOverlapMaxOverlapMaxOverlapMaxOverlapMaxOverlapmaxOverlap determines by what
fraction (i.e., a number between 0 and 1) two instances may at most
overlap in order to consider them as different instances, and hence
to be returned separately. If two instances overlap each other by
more than MaxOverlapMaxOverlapMaxOverlapMaxOverlapMaxOverlapmaxOverlap only the best instance is returned.
The calculation of the overlap is based on the smallest enclosing
rectangle of arbitrary orientation (see smallest_rectangle2)
of the found instances. If MaxOverlapMaxOverlapMaxOverlapMaxOverlapMaxOverlapmaxOverlap=0, the found
instances may not overlap at all, while for MaxOverlapMaxOverlapMaxOverlapMaxOverlapMaxOverlapmaxOverlap=1
all instances are returned.
With the generic parameters ParamNameParamNameParamNameParamNameParamNameparamName and ParamValueParamValueParamValueParamValueParamValueparamValue it is
possible to adjust parameters that typically do not have to be set by the
user. By default the pose is extracted with high subpixel accuracy
('least_squares_very_high'"least_squares_very_high""least_squares_very_high""least_squares_very_high""least_squares_very_high""least_squares_very_high") through a least-squares
adjustment, i.e., by minimizing the distances of the model points to
their corresponding image points. However, if no high accuracy is required
by an application, the subpixel precise extraction can be reduced or
switched off as it increases the processing time. Here,
'sub_pixel' must be passed in ParamNameParamNameParamNameParamNameParamNameparamName and 'none'"none""none""none""none""none",
'least_squares'"least_squares""least_squares""least_squares""least_squares""least_squares", 'least_squares_high'"least_squares_high""least_squares_high""least_squares_high""least_squares_high""least_squares_high" for
ParamValueParamValueParamValueParamValueParamValueparamValue. A further use of ParamNameParamNameParamNameParamNameParamNameparamName and
ParamValueParamValueParamValueParamValueParamValueparamValue is to override the discretization steps of the search
space 'angle_step', 'scale_r_step' and 'scale_c_step' that have been defined
when the model was created in create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModel.
As described in create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModel the
deformable matching algorithm searches exhaustively a basic set of
parameters that are specified with AngleStartAngleStartAngleStartAngleStartAngleStartangleStart,AngleExtentAngleExtentAngleExtentAngleExtentAngleExtentangleExtent,
ScaleRMinScaleRMinScaleRMinScaleRMinScaleRMinscaleRMin,ScaleRMaxScaleRMaxScaleRMaxScaleRMaxScaleRMaxscaleRMax,ScaleCMinScaleCMinScaleCMinScaleCMinScaleCMinscaleCMin and
ScaleCMaxScaleCMaxScaleCMaxScaleCMaxScaleCMaxscaleCMax. However, to allow a detection even when the object is
imaged under perspective distortion, an additional transformation is
estimated. This additional transformation transforms the model from the
original search range to a bigger perspectively distorted one.
By allowing perspective distortions, the risk of false positives is also
increased. One possible use of the parameter ParamNameParamNameParamNameParamNameParamNameparamName is to help
discarding false positives that occur, if for instance a small score was
specified in MinScoreMinScoreMinScoreMinScoreMinScoreminScore and the image contains significant clutter
with similar shape as the model.
To restrict arbitrary perspective matches from occuring, the values
'max_angle_distortion'"max_angle_distortion""max_angle_distortion""max_angle_distortion""max_angle_distortion""max_angle_distortion" and 'max_aniso_scale_distortion'"max_aniso_scale_distortion""max_aniso_scale_distortion""max_aniso_scale_distortion""max_aniso_scale_distortion""max_aniso_scale_distortion" can
be used in ParamNameParamNameParamNameParamNameParamNameparamName.
With 'max_angle_distortion'"max_angle_distortion""max_angle_distortion""max_angle_distortion""max_angle_distortion""max_angle_distortion" the maximal tolerated angular distortion
can be restricted (from the default value 0.0, where arbitrary distortion is
allowed, to pi where no distortion is allowed).
This parameter tests, if the angle of 90 degree at the corners of the
axis-aligned rectangle around the model points is changed by more than the
corresponding ParamValueParamValueParamValueParamValueParamValueparamValue for the found instance of the model.
Note that this parameter helps to restrict both affine (a shear mapping) and
perspective parts of the transformation.
As an example, with 'max_angle_distortion'"max_angle_distortion""max_angle_distortion""max_angle_distortion""max_angle_distortion""max_angle_distortion" a square-like model can
be prevented to match with a parallelogram or an arbitrary trapezium.
With the parameter 'max_aniso_scale_distortion'"max_aniso_scale_distortion""max_aniso_scale_distortion""max_aniso_scale_distortion""max_aniso_scale_distortion""max_aniso_scale_distortion" the ratio of
anisotropic scaling can be restricted (the smaller scale factor divided by
the bigger scale factor).
The value of this parameter ranges from the default value 0.0, where
arbitrary distortion is allowed, to 1.0, where no distortion is allowed.
One typical use for this parameter is to restrict for instance a square-like
model to deform to a rectangular model.
The number of pyramid levels used during the search is determined
with NumLevelsNumLevelsNumLevelsNumLevelsNumLevelsnumLevels. If necessary, the number of levels is
clipped to the range given when the deformable model was created with
create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModel. If NumLevelsNumLevelsNumLevelsNumLevelsNumLevelsnumLevels is set
to 0, the number of pyramid levels specified in
create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModel is used.
The parameter GreedinessGreedinessGreedinessGreedinessGreedinessgreediness determines how “greedily” the
search should be carried out. If GreedinessGreedinessGreedinessGreedinessGreedinessgreediness=0, a safe
search heuristic is used, which finds the model if it is
visible in the image and within the detection range of the algorithm.
However, the search will be relatively time consuming in this case. If
GreedinessGreedinessGreedinessGreedinessGreedinessgreediness=1, an unsafe search heuristic is used, which may cause
the model not to be found in rare cases, even though it is visible in the
image. For GreedinessGreedinessGreedinessGreedinessGreedinessgreediness=1, the maximum search speed is achieved.
In almost all cases, the deformable model will be found for
GreedinessGreedinessGreedinessGreedinessGreedinessgreediness=0.9.
- Multithreading type: reentrant (runs in parallel with non-exclusive operators).
- Multithreading scope: global (may be called from any thread).
- Automatically parallelized on internal data level.
Input image in which the model should be found.
Smallest rotation of the model.
Default value: -0.39
Suggested values: -3.14, -1.57, -0.78, -0.39, -0.20, 0.0
Extent of the rotation angles.
Default value: 0.78
Suggested values: 6.29, 3.14, 1.57, 0.78, 0.39, 0.0
Restriction: AngleExtent >= 0
Minimum scale of the model in row direction.
Default value: 1.0
Suggested values: 0.5, 0.6, 0.7, 0.8, 0.9, 1.0
Restriction: ScaleRMin > 0
Maximum scale of the model in row direction.
Default value: 1.0
Suggested values: 1.0, 1.1, 1.2, 1.3, 1.4, 1.5
Restriction: ScaleRMax >= ScaleRMin
Minimum scale of the model in column direction.
Default value: 1.0
Suggested values: 0.5, 0.6, 0.7, 0.8, 0.9, 1.0
Restriction: ScaleCMin > 0
Maximum scale of the model in column direction.
Default value: 1.0
Suggested values: 1.0, 1.1, 1.2, 1.3, 1.4, 1.5
Restriction: ScaleCMax >= ScaleCMin
Minumum score of the instances of the model to
be found.
Default value: 0.5
Suggested values: 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0
Typical range of values: 0
≤
MinScore
MinScore
MinScore
MinScore
MinScore
minScore
≤
1
Minimum increment: 0.01
Recommended increment: 0.05
Number of instances of the model to be found
(or 0 for all matches).
Default value: 1
Suggested values: 0, 1, 2, 3, 4, 5, 10, 20
Maximum overlap of the instances of the model
to be found.
Default value: 1.0
Suggested values: 0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0
Typical range of values: 0
≤
MaxOverlap
MaxOverlap
MaxOverlap
MaxOverlap
MaxOverlap
maxOverlap
≤
1
Minimum increment: 0.01
Recommended increment: 0.05
Number of pyramid levels used in the matching
(and lowest pyramid level to use if
|NumLevelsNumLevelsNumLevelsNumLevelsNumLevelsnumLevels| = 2).
Default value: 0
List of values: 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
“Greediness” of the search heuristic (0: safe
but slow; 1: fast but matches may be missed).
Default value: 0.9
Suggested values: 0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0
Typical range of values: 0
≤
Greediness
Greediness
Greediness
Greediness
Greediness
greediness
≤
1
Minimum increment: 0.01
Recommended increment: 0.05
The general parameter names.
Default value: []
List of values: [], 'angle_step'"angle_step""angle_step""angle_step""angle_step""angle_step", 'max_angle_distortion'"max_angle_distortion""max_angle_distortion""max_angle_distortion""max_angle_distortion""max_angle_distortion", 'max_aniso_scale_distortion'"max_aniso_scale_distortion""max_aniso_scale_distortion""max_aniso_scale_distortion""max_aniso_scale_distortion""max_aniso_scale_distortion", 'scale_c_step'"scale_c_step""scale_c_step""scale_c_step""scale_c_step""scale_c_step", 'scale_r_step'"scale_r_step""scale_r_step""scale_r_step""scale_r_step""scale_r_step", 'subpixel'"subpixel""subpixel""subpixel""subpixel""subpixel"
Values of the general parameters.
Default value: []
List of values: [], 'least_squares'"least_squares""least_squares""least_squares""least_squares""least_squares", 'least_squares_high'"least_squares_high""least_squares_high""least_squares_high""least_squares_high""least_squares_high", 'least_squares_very_high'"least_squares_very_high""least_squares_very_high""least_squares_very_high""least_squares_very_high""least_squares_very_high", 'none'"none""none""none""none""none"
Homographies between model and found instances.
Score of the found instances of the model.
If the parameters are valid, the operator
find_planar_uncalib_deformable_modelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModel returns the value 2 (H_MSG_TRUE). If
necessary an exception is raised.
create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModel,
read_deformable_modelread_deformable_modelReadDeformableModelread_deformable_modelReadDeformableModelReadDeformableModel
find_planar_calib_deformable_modelfind_planar_calib_deformable_modelFindPlanarCalibDeformableModelfind_planar_calib_deformable_modelFindPlanarCalibDeformableModelFindPlanarCalibDeformableModel
Matching