ximgproc class

Constructors

ximgproc()

Properties

hashCode → int
The hash code for this object.
no setterinherited
runtimeType → Type
A representation of the runtime type of the object.
no setterinherited

Methods

noSuchMethod(Invocation invocation) → dynamic
Invoked when a nonexistent method or property is accessed.
inherited
toString() → String
A string representation of this object.
inherited

Operators

operator ==(Object other) → bool
The equality operator.
inherited

Static Methods

anisotropicDiffusion(InputArray src, double alpha, double K, int niters, {OutputArray? dst}) → Mat
Performs anisotropic diffusion on an image.
anisotropicDiffusionAsync(InputArray src, double alpha, double K, int niters, {OutputArray? dst}) → Future<Mat>
Performs anisotropic diffusion on an image.
edgePreservingFilter(InputArray src, int d, double threshold, {OutputArray? dst}) → Mat
Smoothes an image using the Edge-Preserving filter.
edgePreservingFilterAsync(InputArray src, int d, double threshold, {OutputArray? dst}) → Future<Mat>
Smoothes an image using the Edge-Preserving filter.
findEllipses(InputArray image, {OutputArray? ellipses, double scoreThreshold = 0.7, double reliabilityThreshold = 0.5, double centerDistanceThreshold = 0.05}) → Mat
Finds ellipses fastly in an image using projective invariant pruning.
findEllipsesAsync(InputArray image, {OutputArray? ellipses, double scoreThreshold = 0.7, double reliabilityThreshold = 0.5, double centerDistanceThreshold = 0.05}) → Future<Mat>
Finds ellipses fastly in an image using projective invariant pruning.
niBlackThreshold(InputArray src, double maxValue, int type, int blockSize, double k, {OutputArray? dst, int binarizationMethod = BINARIZATION_NIBLACK, double r = 128}) → Mat
Performs thresholding on input images using Niblack's technique or some of the popular variations it inspired.
niBlackThresholdAsync(InputArray src, double maxValue, int type, int blockSize, double k, {OutputArray? dst, int binarizationMethod = BINARIZATION_NIBLACK, double r = 128}) → Future<Mat>
Performs thresholding on input images using Niblack's technique or some of the popular variations it inspired.
PeiLinNormalization(InputArray I, {OutputArray? T}) → Mat
Calculates an affine transformation that normalize given image using Pei&Lin Normalization.
PeiLinNormalizationAsync(InputArray I, {OutputArray? T}) → Future<Mat>
Calculates an affine transformation that normalize given image using Pei&Lin Normalization.
thinning(InputArray src, {OutputArray? dst, int thinningType = THINNING_ZHANGSUEN}) → Mat
Applies a binary blob thinning operation, to achieve a skeletization of the input image.
thinningAsync(InputArray src, {OutputArray? dst, int thinningType = THINNING_ZHANGSUEN}) → Future<Mat>
Applies a binary blob thinning operation, to achieve a skeletization of the input image.