| EMTrainM Method |
Estimate the Gaussian mixture parameters from a samples set.
Namespace:
OpenCvSharp
Assembly:
OpenCvSharp (in OpenCvSharp.dll) Version: 1.0.0
Syntax public virtual bool TrainM(
InputArray samples,
InputArray probs0,
OutputArray logLikelihoods = null,
OutputArray labels = null,
OutputArray probs = null
)
Public Overridable Function TrainM (
samples As InputArray,
probs0 As InputArray,
Optional logLikelihoods As OutputArray = Nothing,
Optional labels As OutputArray = Nothing,
Optional probs As OutputArray = Nothing
) As Boolean
public:
virtual bool TrainM(
InputArray^ samples,
InputArray^ probs0,
OutputArray^ logLikelihoods = nullptr,
OutputArray^ labels = nullptr,
OutputArray^ probs = nullptr
)
abstract TrainM :
samples : InputArray *
probs0 : InputArray *
?logLikelihoods : OutputArray *
?labels : OutputArray *
?probs : OutputArray
(* Defaults:
let _logLikelihoods = defaultArg logLikelihoods null
let _labels = defaultArg labels null
let _probs = defaultArg probs null
*)
-> bool
override TrainM :
samples : InputArray *
probs0 : InputArray *
?logLikelihoods : OutputArray *
?labels : OutputArray *
?probs : OutputArray
(* Defaults:
let _logLikelihoods = defaultArg logLikelihoods null
let _labels = defaultArg labels null
let _probs = defaultArg probs null
*)
-> bool
Parameters
- samples
- Type: OpenCvSharpInputArray
Samples from which the Gaussian mixture model will be estimated. It should be a
one-channel matrix, each row of which is a sample. If the matrix does not have CV_64F type
it will be converted to the inner matrix of such type for the further computing. - probs0
- Type: OpenCvSharpInputArray
the probabilities - logLikelihoods (Optional)
- Type: OpenCvSharpOutputArray
The optional output matrix that contains a likelihood logarithm value for
each sample. It has \f$nsamples \times 1\f$ size and CV_64FC1 type. - labels (Optional)
- Type: OpenCvSharpOutputArray
The optional output "class label" for each sample:
\f$\texttt{labels}_i=\texttt{arg max}_k(p_{i,k}), i=1..N\f$ (indices of the most probable
mixture component for each sample). It has \f$nsamples \times 1\f$ size and CV_32SC1 type. - probs (Optional)
- Type: OpenCvSharpOutputArray
The optional output matrix that contains posterior probabilities of each Gaussian
mixture component given the each sample. It has \f$nsamples \times nclusters\f$ size and CV_64FC1 type.
Return Value
Type:
Boolean[Missing <returns> documentation for "M:OpenCvSharp.EM.TrainM(OpenCvSharp.InputArray,OpenCvSharp.InputArray,OpenCvSharp.OutputArray,OpenCvSharp.OutputArray,OpenCvSharp.OutputArray)"]
See Also