OpenCV for Unity 2.6.5
Enox Software / Please refer to OpenCV official document ( http://docs.opencv.org/4.10.0/index.html ) for the details of the argument of the method.
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Public Member Functions | |
float | getInitialStepSize () |
float | getMarginRegularization () |
int | getMarginType () |
float | getShift () |
float | getStepDecreasingPower () |
int | getSvmsgdType () |
TermCriteria | getTermCriteria () |
double double double epsilon | getTermCriteriaAsValueTuple () |
Vec3d | getTermCriteriaAsVec3d () |
Mat | getWeights () |
void | setInitialStepSize (float InitialStepSize) |
void | setMarginRegularization (float marginRegularization) |
void | setMarginType (int marginType) |
void | setOptimalParameters () |
Function sets optimal parameters values for chosen SVM SGD model. | |
void | setOptimalParameters (int svmsgdType) |
Function sets optimal parameters values for chosen SVM SGD model. | |
void | setOptimalParameters (int svmsgdType, int marginType) |
Function sets optimal parameters values for chosen SVM SGD model. | |
void | setStepDecreasingPower (float stepDecreasingPower) |
void | setSvmsgdType (int svmsgdType) |
void | setTermCriteria (in Vec3d val) |
void | setTermCriteria (in(double type, double maxCount, double epsilon) val) |
void | setTermCriteria (TermCriteria val) |
Public Member Functions inherited from OpenCVForUnity.MlModule.StatModel | |
float | calcError (TrainData data, bool test, Mat resp) |
Computes error on the training or test dataset. | |
override bool | empty () |
Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. | |
int | getVarCount () |
Returns the number of variables in training samples. | |
bool | isClassifier () |
Returns true if the model is classifier. | |
bool | isTrained () |
Returns true if the model is trained. | |
virtual float | predict (Mat samples) |
Predicts response(s) for the provided sample(s) | |
virtual float | predict (Mat samples, Mat results) |
Predicts response(s) for the provided sample(s) | |
virtual float | predict (Mat samples, Mat results, int flags) |
Predicts response(s) for the provided sample(s) | |
bool | train (Mat samples, int layout, Mat responses) |
Trains the statistical model. | |
bool | train (TrainData trainData) |
Trains the statistical model. | |
bool | train (TrainData trainData, int flags) |
Trains the statistical model. | |
Public Member Functions inherited from OpenCVForUnity.CoreModule.Algorithm | |
virtual void | clear () |
Clears the algorithm state. | |
virtual string | getDefaultName () |
IntPtr | getNativeObjAddr () |
void | save (string filename) |
Public Member Functions inherited from OpenCVForUnity.DisposableObject | |
void | Dispose () |
void | ThrowIfDisposed () |
Static Public Member Functions | |
static new SVMSGD | __fromPtr__ (IntPtr addr) |
static SVMSGD | create () |
Creates empty model. Use StatModel.train to train the model. Since SVMSGD has several parameters, you may want to find the best parameters for your problem or use setOptimalParameters() to set some default parameters. | |
static SVMSGD | load (string filepath) |
Loads and creates a serialized SVMSGD from a file. | |
static SVMSGD | load (string filepath, string nodeName) |
Loads and creates a serialized SVMSGD from a file. | |
Static Public Member Functions inherited from OpenCVForUnity.MlModule.StatModel | |
static new StatModel | __fromPtr__ (IntPtr addr) |
Static Public Member Functions inherited from OpenCVForUnity.CoreModule.Algorithm | |
static Algorithm | __fromPtr__ (IntPtr addr) |
Static Public Member Functions inherited from OpenCVForUnity.DisposableObject | |
static IntPtr | ThrowIfNullIntPtr (IntPtr ptr) |
Public Attributes | |
double double | maxCount |
double | type |
Static Public Attributes | |
const int | ASGD = 1 |
const int | HARD_MARGIN = 1 |
const int | SGD = 0 |
const int | SOFT_MARGIN = 0 |
Static Public Attributes inherited from OpenCVForUnity.MlModule.StatModel | |
const int | COMPRESSED_INPUT = 2 |
const int | PREPROCESSED_INPUT = 4 |
const int | RAW_OUTPUT = 1 |
const int | UPDATE_MODEL = 1 |
Protected Member Functions | |
override void | Dispose (bool disposing) |
Protected Member Functions inherited from OpenCVForUnity.MlModule.StatModel | |
Protected Member Functions inherited from OpenCVForUnity.CoreModule.Algorithm | |
Protected Member Functions inherited from OpenCVForUnity.DisposableOpenCVObject | |
DisposableOpenCVObject () | |
DisposableOpenCVObject (bool isEnabledDispose) | |
DisposableOpenCVObject (IntPtr ptr) | |
DisposableOpenCVObject (IntPtr ptr, bool isEnabledDispose) | |
Protected Member Functions inherited from OpenCVForUnity.DisposableObject | |
DisposableObject () | |
DisposableObject (bool isEnabledDispose) | |
Additional Inherited Members | |
Package Functions inherited from OpenCVForUnity.MlModule.StatModel | |
Package Functions inherited from OpenCVForUnity.CoreModule.Algorithm | |
Package Attributes inherited from OpenCVForUnity.DisposableOpenCVObject | |
Properties inherited from OpenCVForUnity.DisposableObject | |
bool | IsDisposed [get, protected set] |
bool | IsEnabledDispose [get, set] |
*************************************************************************************\ Stochastic Gradient Descent SVM Classifier * ***************************************************************************************
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Creates empty model. Use StatModel.train to train the model. Since SVMSGD has several parameters, you may want to find the best parameters for your problem or use setOptimalParameters() to set some default parameters.
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Reimplemented from OpenCVForUnity.MlModule.StatModel.
float OpenCVForUnity.MlModule.SVMSGD.getInitialStepSize | ( | ) |
float OpenCVForUnity.MlModule.SVMSGD.getMarginRegularization | ( | ) |
int OpenCVForUnity.MlModule.SVMSGD.getMarginType | ( | ) |
float OpenCVForUnity.MlModule.SVMSGD.getShift | ( | ) |
float OpenCVForUnity.MlModule.SVMSGD.getStepDecreasingPower | ( | ) |
int OpenCVForUnity.MlModule.SVMSGD.getSvmsgdType | ( | ) |
TermCriteria OpenCVForUnity.MlModule.SVMSGD.getTermCriteria | ( | ) |
double double double epsilon OpenCVForUnity.MlModule.SVMSGD.getTermCriteriaAsValueTuple | ( | ) |
Vec3d OpenCVForUnity.MlModule.SVMSGD.getTermCriteriaAsVec3d | ( | ) |
Mat OpenCVForUnity.MlModule.SVMSGD.getWeights | ( | ) |
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Loads and creates a serialized SVMSGD from a file.
Use SVMSGD.save to serialize and store an SVMSGD to disk. Load the SVMSGD from this file again, by calling this function with the path to the file. Optionally specify the node for the file containing the classifier
filepath | path to serialized SVMSGD |
nodeName | name of node containing the classifier |
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Loads and creates a serialized SVMSGD from a file.
Use SVMSGD.save to serialize and store an SVMSGD to disk. Load the SVMSGD from this file again, by calling this function with the path to the file. Optionally specify the node for the file containing the classifier
filepath | path to serialized SVMSGD |
nodeName | name of node containing the classifier |
void OpenCVForUnity.MlModule.SVMSGD.setInitialStepSize | ( | float | InitialStepSize | ) |
void OpenCVForUnity.MlModule.SVMSGD.setMarginRegularization | ( | float | marginRegularization | ) |
void OpenCVForUnity.MlModule.SVMSGD.setMarginType | ( | int | marginType | ) |
void OpenCVForUnity.MlModule.SVMSGD.setOptimalParameters | ( | ) |
void OpenCVForUnity.MlModule.SVMSGD.setOptimalParameters | ( | int | svmsgdType | ) |
void OpenCVForUnity.MlModule.SVMSGD.setOptimalParameters | ( | int | svmsgdType, |
int | marginType ) |
void OpenCVForUnity.MlModule.SVMSGD.setStepDecreasingPower | ( | float | stepDecreasingPower | ) |
void OpenCVForUnity.MlModule.SVMSGD.setSvmsgdType | ( | int | svmsgdType | ) |
void OpenCVForUnity.MlModule.SVMSGD.setTermCriteria | ( | in Vec3d | val | ) |
void OpenCVForUnity.MlModule.SVMSGD.setTermCriteria | ( | in(double type, double maxCount, double epsilon) | val | ) |
void OpenCVForUnity.MlModule.SVMSGD.setTermCriteria | ( | TermCriteria | val | ) |
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double double OpenCVForUnity.MlModule.SVMSGD.maxCount |
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double OpenCVForUnity.MlModule.SVMSGD.type |