Direct Graphical Models
v.1.5.1
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OpenCV Random Forest training class. More...
#include <TrainNodeCvRF.h>
Public Member Functions | |
CTrainNodeCvRF (byte nStates, word nFeatures, TrainNodeCvRFParams params=TRAIN_NODE_CV_RF_PARAMS_DEFAULT) | |
Constructor. More... | |
CTrainNodeCvRF (byte nStates, word nFeatures, int maxSamples) | |
Constructor. More... | |
~CTrainNodeCvRF (void) | |
void | reset (void) |
Resets class variables. More... | |
void | save (const std::string &path, const std::string &name=std::string(), short idx=-1) const |
Saves the training data. More... | |
void | load (const std::string &path, const std::string &name=std::string(), short idx=-1) |
Loads the training data. More... | |
void | addFeatureVec (const Mat &featureVector, byte gt) |
Adds new feature vector. More... | |
void | train (bool doClean=false) |
Random model training. More... | |
Mat | getFeatureImportance (void) const |
Returns the feature importance vector. More... | |
Public Member Functions inherited from DirectGraphicalModels::CTrainNode | |
CTrainNode (byte nStates, word nFeatures) | |
Constructor. More... | |
virtual | ~CTrainNode (void) |
void | addFeatureVec (const Mat &featureVectors, const Mat >) |
Adds a block of new feature vectors. More... | |
void | addFeatureVec (const vec_mat_t &featureVectors, const Mat >) |
Adds a block of new feature vectors. More... | |
Mat | getNodePotentials (const Mat &featureVector, float weight=1.0f) const |
Returns the node potential, based on the feature vector. More... | |
Public Member Functions inherited from DirectGraphicalModels::ITrain | |
ITrain (byte nStates, word nFeatures) | |
Constructor. More... | |
virtual | ~ITrain (void) |
word | getNumFeatures (void) const |
Returns number of features. More... | |
Public Member Functions inherited from DirectGraphicalModels::CBaseRandomModel | |
CBaseRandomModel (byte nStates) | |
Constructor. More... | |
virtual | ~CBaseRandomModel (void) |
byte | getNumStates (void) const |
Returns number of features. More... | |
Protected Member Functions | |
void | saveFile (FILE *pFile) const |
Saves the random model into the file. More... | |
void | loadFile (FILE *pFile) |
Loads the random model from the file. More... | |
void | calculateNodePotentials (const Mat &featureVector, Mat &potential, Mat &mask) const |
Calculates the node potential, based on the feature vector. More... | |
Protected Member Functions inherited from DirectGraphicalModels::CBaseRandomModel | |
std::string | generateFileName (const std::string &path, const std::string &name, short idx) const |
Generates name of the data file for storing random model parameters. More... | |
Protected Attributes | |
Ptr< CRForest > | m_pRF |
Random Forest. More... | |
Protected Attributes inherited from DirectGraphicalModels::ITrain | |
word | m_nFeatures |
The number of features (length of the feature vector) More... | |
Protected Attributes inherited from DirectGraphicalModels::CBaseRandomModel | |
byte | m_nStates |
The number of states (classes) More... | |
OpenCV Random Forest training class.
Definition at line 49 of file TrainNodeCvRF.h.
DirectGraphicalModels::CTrainNodeCvRF::CTrainNodeCvRF | ( | byte | nStates, |
word | nFeatures, | ||
TrainNodeCvRFParams | params = TRAIN_NODE_CV_RF_PARAMS_DEFAULT |
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) |
Constructor.
nStates | Number of states (classes) |
nFeatures | Number of features |
params | Random Forest parameters (Ref. TrainNodeCvRFParams) |
Definition at line 10 of file TrainNodeCvRF.cpp.
DirectGraphicalModels::CTrainNodeCvRF::CTrainNodeCvRF | ( | byte | nStates, |
word | nFeatures, | ||
int | maxSamples | ||
) |
Constructor.
nStates | Number of states (classes) |
nFeatures | Number of features |
maxSamples | Maximum number of samples to be used in training.
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Definition at line 16 of file TrainNodeCvRF.cpp.
DirectGraphicalModels::CTrainNodeCvRF::~CTrainNodeCvRF | ( | void | ) |
Definition at line 44 of file TrainNodeCvRF.cpp.
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virtual |
Adds new feature vector.
Used to add a featureVector, corresponding to the ground-truth state (class) gt for training
featureVector | Multi-dimensinal point: Mat(size: nFeatures x 1; type: CV_8UC1) |
gt | Corresponding ground-truth state (class) |
Implements DirectGraphicalModels::CTrainNode.
Definition at line 66 of file TrainNodeCvRF.cpp.
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protectedvirtual |
Calculates the node potential, based on the feature vector.
This function calculates the potentials of the node, described with the sample featureVector, being in each state (belonging to each class). These potentials are united in the node potential vector:
\[nodePot[nStates] = f(\textbf{f}[nFeatures]).\]
Functions \( f \) must be implemented in derived classes.
[in] | featureVector | Multi-dimensinal point \(\textbf{f}\): Mat(size: nFeatures x 1; type: CV_{XX}C1) |
[in,out] | potential | Node potentials: Mat(size: nStates x 1; type: CV_32FC1). This parameter should be preinitialized and set to value 0. |
[in,out] | mask | Relevant Node potentials: Mat(size: nStates x 1; type: CV_8UC1). This parameter should be preinitialized and set to value 1 (all potentials are relevant). |
Implements DirectGraphicalModels::CTrainNode.
Definition at line 122 of file TrainNodeCvRF.cpp.
Mat DirectGraphicalModels::CTrainNodeCvRF::getFeatureImportance | ( | void | ) | const |
Returns the feature importance vector.
The method returns the feature importance vector, computed at the training stage when TrainNodeCvRFParams::calc_var_importance is set to true.
NULL | : Empty Mat() on error (TrainNodeCvRFParams::calc_var_importance flag is not set) |
feature_importance | : Mat(size: 1 x nFeatures; type: CV_32FC1) |
Definition at line 117 of file TrainNodeCvRF.cpp.
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virtual |
Loads the training data.
Allows to re-use the class. Loads data to the file: "<path><name>_<idx>.dat".
path | Path to the folder, containing the data file. |
name | Name of data file. If empty, will be generated automatically from the class name. |
idx | Index of the data file. Negative value means no index. |
Reimplemented from DirectGraphicalModels::CBaseRandomModel.
Definition at line 60 of file TrainNodeCvRF.cpp.
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inlineprotectedvirtual |
Loads the random model from the file.
Allows to re-use the class.
pFile | Pointer to the file, opened for reading. |
Implements DirectGraphicalModels::CBaseRandomModel.
Definition at line 88 of file TrainNodeCvRF.h.
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virtual |
Resets class variables.
Allows to re-use the class.
Implements DirectGraphicalModels::CBaseRandomModel.
Definition at line 47 of file TrainNodeCvRF.cpp.
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virtual |
Saves the training data.
Allows to re-use the class. Stores data to the file: "<path><name>_<idx>.dat".
path | Path to the destination folder. |
name | Name of data file. If empty, will be generated automatically from the class name. |
idx | Index of the destination file. Negative value means no index. |
Reimplemented from DirectGraphicalModels::CBaseRandomModel.
Definition at line 54 of file TrainNodeCvRF.cpp.
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inlineprotectedvirtual |
Saves the random model into the file.
Allows to re-use the class.
pFile | Pointer to the file, opened for writing. |
Implements DirectGraphicalModels::CBaseRandomModel.
Definition at line 87 of file TrainNodeCvRF.h.
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virtual |
Random model training.
Auxilary function for training - some derived classes may use this function inbetween training and classification phases
doClean | Flag indicating if the memory, keeping the trining data should be released after training |
Reimplemented from DirectGraphicalModels::CTrainNode.
Definition at line 82 of file TrainNodeCvRF.cpp.
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protected |
Random Forest.
Definition at line 93 of file TrainNodeCvRF.h.