* **keypoints** Collection of keypoints detected in an input images. keypoints[i] is a set of keypoints detected in an images[i].
:param keypoints:Collection of keypoints detected in input images. ``keypoints[i]`` is a set of keypoints detected in ``images[i]`` .
* **masks** Masks for each input image specifying where to look for keypoints (optional). masks[i] is a mask for images[i].
Each element of ``masks`` vector must be a char matrix with non-zero values in the region of interest.
:param masks:Masks for each input image specifying where to look for keypoints (optional). ``masks[i]`` is a mask for ``images[i]`` . Each element of the ``masks`` vector must be a char matrix with non-zero values in the region of interest.
Adapts a detector to detect points over multiple levels of a Gaussian pyramid. Useful for detectors that are not inherently scaled. ::
Class adapting a detector to detect points over multiple levels of a Gaussian pyramid. Consider using this class for detectors that are not inherently scaled. ::
class PyramidAdaptedFeatureDetector : public FeatureDetector
{
@ -397,7 +394,7 @@ DynamicAdaptedFeatureDetector
..c:type:: DynamicAdaptedFeatureDetector
An adaptively adjusting detector that iteratively detects until the desired number of features are found. ::
Adaptively adjusting detector that iteratively detects features until the desired number is found ::
class DynamicAdaptedFeatureDetector: public FeatureDetector
..c:function:: DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector( const Ptr<AdjusterAdapter>\& adjaster, int min_features, int max_features, int max_iters )
DynamicAdaptedFeatureDetector constructor.
``DynamicAdaptedFeatureDetector`` constructor
:param adjaster:An :func:`AdjusterAdapter` that will do the detection and parameter
adjustment
:param adjaster::func:`AdjusterAdapter` that detects features and adjusts parameters.??parameter formatting is broken here
:param min_features:This minimum desired number features.
:param min_features:Minimum desired number features.
:param max_features:The maximum desired number of features.
:param max_features:Maximum desired number of features.
:param max_iters:The maximum number of times to try to adjust the feature detector parameters. For the :func:`FastAdjuster` this number can be high,
but with Star or Surf, many iterations can get time consuming. At each iteration the detector is rerun, so keep this in mind when choosing this value.
:param max_iters:Maximum number of times to try adjusting the feature detector parameters. For :func:`FastAdjuster` , this number can be high, but with ``Star`` or ``Surf`` , many iterations can be time-comsuming. At each iteration the detector is rerun.
..index:: AdjusterAdapter
@ -461,7 +457,7 @@ AdjusterAdapter
..c:type:: AdjusterAdapter
A feature detector parameter adjuster interface, this is used by the :func:`DynamicAdaptedFeatureDetector` and is a wrapper for :func:`FeatureDetecto` r that allow them to be adjusted after a detection. ::
Class providing an interface for adjusting parameters of a feature detector. This interface is used by :func:`DynamicAdaptedFeatureDetector` . It is a wrapper for :func:`FeatureDetector` that enables adjusting parameters after detection.?? ::
class AdjusterAdapter: public FeatureDetector
{
@ -474,7 +470,9 @@ AdjusterAdapter
See
:func:`FastAdjuster`,:func:`StarAdjuster`,:func:`SurfAdjuster` for concrete implementations.
:func:`FastAdjuster`,
:func:`StarAdjuster`,
:func:`SurfAdjuster` for concrete implementations.
..index:: AdjusterAdapter::tooFew
@ -483,13 +481,13 @@ AdjusterAdapter::tooFew
---------------------------
..c:function:: virtual void tooFew(int min, int n_detected) = 0
Too few features were detected so, adjust the detector parameters accordingly - so that the next detection detects more features.
Adjusts the detector parameters to detect more features.
:param min:This minimum desired number features.
:param min:Minimum desired number of features.
:param n_detected:The actual number detected last run.
:param n_detected:Number of features detected during the latest run.
An example implementation of this is ::
Example: ::
void FastAdjuster::tooFew(int min, int n_detected)
{
@ -503,13 +501,13 @@ AdjusterAdapter::tooMany
----------------------------
..c:function:: virtual void tooMany(int max, int n_detected) = 0
Too many features were detected so, adjust the detector parameters accordingly - so that the next detection detects less features.
Adjusts the detector parameters detect less features.
:param max:This maximum desired number features.
:param max:Maximum desired number of features.
:param n_detected:The actual number detected last run.
:param n_detected:Number of features detected during the latest run.
An example implementation of this is ::
Example: ::
void FastAdjuster::tooMany(int min, int n_detected)
{
@ -523,7 +521,9 @@ AdjusterAdapter::good
-------------------------
..c:function:: virtual bool good() const = 0
Are params maxed out or still valid? Returns false if the parameters can't be adjusted any more. An example implementation of this is ::
Returns false if the detector parameters cannot be adjusted any more.
Example: ::
bool FastAdjuster::good() const
{
@ -538,7 +538,7 @@ FastAdjuster
..c:type:: FastAdjuster
:func:`AdjusterAdapter` for the :func:`FastFeatureDetector`. This will basically decrement or increment the threshhold by 1 ::
:func:`AdjusterAdapter` for :func:`FastFeatureDetector`. This class decrements or increments the threshhold by 1.?? ::
class FastAdjuster FastAdjuster: public AdjusterAdapter
{
@ -554,7 +554,7 @@ StarAdjuster
..c:type:: StarAdjuster
:func:`AdjusterAdapter` for the:func:`StarFeatureDetector` . This adjusts the responseThreshhold of StarFeatureDetector. ::
:func:`AdjusterAdapter` for :func:`StarFeatureDetector` . This class adjusts the ``responseThreshhold`` of ``StarFeatureDetector``. ::
class StarAdjuster: public AdjusterAdapter
{
@ -569,7 +569,7 @@ SurfAdjuster
..c:type:: SurfAdjuster
:func:`AdjusterAdapter` for the:func:`SurfFeatureDetector` . This adjusts the hessianThreshold of SurfFeatureDetector. ::
:func:`AdjusterAdapter` for :func:`SurfFeatureDetector` . This class adjusts the ``hessianThreshold`` of ``SurfFeatureDetector``. ::
class SurfAdjuster: public SurfAdjuster
{
@ -583,7 +583,7 @@ FeatureDetector
---------------
..c:type:: FeatureDetector
Abstract base class for 2D image feature detectors. ::
Abstract base class for 2D image feature detectors ::
Adapts a detector to detect points over multiple levels of a Gaussian pyramid. Useful for detectors that are not inherently scaled. ::
Class adapting a detector to detect points over multiple levels of a Gaussian pyramid. Consider using this class for detectors that are not inherently scaled. ::
class PyramidAdaptedFeatureDetector : public FeatureDetector
{
@ -881,7 +880,7 @@ DynamicAdaptedFeatureDetector
..c:type:: DynamicAdaptedFeatureDetector
An adaptively adjusting detector that iteratively detects until the desired number of features are found. ::
Adaptively adjusting detector that iteratively detects features until the desired number is found. ::
class DynamicAdaptedFeatureDetector: public FeatureDetector
..c:function:: DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector( const Ptr<AdjusterAdapter>\& adjaster, int min_features, int max_features, int max_iters )
:param adjaster:An :func:`AdjusterAdapter` that will do the detection and parameter
adjustment
:param adjaster::func:`AdjusterAdapter` that detects features and adjusts parameters.??formatting issue again
:param min_features:This minimum desired number features.
:param min_features:Minimum desired number features.
:param max_features:The maximum desired number of features.
:param max_features:Maximum desired number of features.
:param max_iters:The maximum number of times to try to adjust the feature detector parameters. For the :func:`FastAdjuster` this number can be high,
but with Star or Surf, many iterations can get time consuming. At each iteration the detector is rerun, so keep this in mind when choosing this value.
:param max_iters:Maximum number of times to try adjusting the feature detector parameters. For :func:`FastAdjuster` , this number can be high, but with ``Star`` or ``Surf`` , many iterations can be time-consuming. At each iteration the detector is rerun.
..index:: AdjusterAdapter
@ -945,7 +942,7 @@ AdjusterAdapter
..c:type:: AdjusterAdapter
A feature detector parameter adjuster interface, this is used by the :func:`DynamicAdaptedFeatureDetector` and is a wrapper for :func:`FeatureDetecto` r that allow them to be adjusted after a detection. ::
Class providing an interface for adjusting parameters of a feature detector. This interface is used by :func:`DynamicAdaptedFeatureDetector` . It is a wrapper for :func:`FeatureDetector` that enables adjusting parameters after detection. ::
class AdjusterAdapter: public FeatureDetector
{
@ -957,7 +954,9 @@ AdjusterAdapter
};
See
:func:`FastAdjuster`,:func:`StarAdjuster`,:func:`SurfAdjuster` for concrete implementations.
:func:`FastAdjuster`,
:func:`StarAdjuster`,
:func:`SurfAdjuster` for concrete implementations.
..index:: AdjusterAdapter::tooFew
@ -965,13 +964,13 @@ AdjusterAdapter::tooFew
---------------------------
..c:function:: virtual void tooFew(int min, int n_detected) = 0
Too few features were detected so, adjust the detector parameters accordingly - so that the next detection detects more features.
Adjusts the detector parameters to detect more features.
:param min:This minimum desired number features.
:param min:Minimum desired number of features.
:param n_detected:The actual number detected last run.
:param n_detected:Number of features detected during the latest run.
An example implementation of this is ::
Example: ::
void FastAdjuster::tooFew(int min, int n_detected)
Elena Fedotova
14 years ago