curfil::TrainingConfiguration Class Reference

Parameters used for training, most of which are provided by the user. More...

#include <random_tree.h>

Public Member Functions
	TrainingConfiguration (const TrainingConfiguration &other)
	using another object to set the training cofiguration attributes
	TrainingConfiguration (int randomSeed, unsigned int samplesPerImage, unsigned int featureCount, unsigned int minSampleCount, int maxDepth, uint16_t boxRadius, uint16_t regionSize, uint16_t thresholds, int numThreads, int maxImages, int imageCacheSize, unsigned int maxSamplesPerBatch, AccelerationMode accelerationMode, bool useCIELab=true, bool useDepthFilling=false, const std::vector< int > deviceIds=std::vector< int >(1, 0), const std::string subsamplingType="classUniform", const std::vector< std::string > &ignoredColors=std::vector< std::string >(), bool useDepthImages=true, bool horizontalFlipping=false)
	creating a configuration objects with the settings that the user provided
void	setRandomSeed (int randomSeed)
	sets the seed used for RandomSource during training
int	getRandomSeed () const
unsigned int	getSamplesPerImage () const
unsigned int	getFeatureCount () const
unsigned int	getMinSampleCount () const
int	getMaxDepth () const
uint16_t	getBoxRadius () const
uint16_t	getRegionSize () const
uint16_t	getThresholds () const
int	getNumThreads () const
int	getMaxImages () const
int	getImageCacheSize () const
unsigned int	getMaxSamplesPerBatch () const
AccelerationMode	getAccelerationMode () const
void	setAccelerationMode (const AccelerationMode &accelerationMode)
	set the acceleration mode: gpu or cpu
std::string	getAccelerationModeString () const
const std::vector< int > &	getDeviceIds () const
void	setDeviceIds (const std::vector< int > &deviceIds)
	set the deviceId used for training
std::string	getSubsamplingType () const
bool	isUseCIELab () const
bool	isUseDepthFilling () const
bool	isUseDepthImages () const
bool	doHorizontalFlipping () const
const std::vector< std::string > &	getIgnoredColors () const
TrainingConfiguration &	operator= (const TrainingConfiguration &other)
	set its attributes to be equal to another configuration
bool	equals (const TrainingConfiguration &other, bool strict=false) const
bool	operator== (const TrainingConfiguration &other) const
bool	operator!= (const TrainingConfiguration &other) const

Static Public Member Functions
static AccelerationMode	parseAccelerationModeString (const std::string &modeString)

Detailed Description

Parameters used for training, most of which are provided by the user.

Definition at line 159 of file random_tree.h.

Member Function Documentation

bool curfil::TrainingConfiguration::doHorizontalFlipping ( ) const

inline

Returns

whether features should be also horizontally flipped

Definition at line 407 of file random_tree.h.

bool curfil::TrainingConfiguration::equals	(	const TrainingConfiguration &	other,
		bool	strict = false
	)		const

Returns

whether it's equal to another configuration

AccelerationMode curfil::TrainingConfiguration::getAccelerationMode ( ) const

inline

Returns

acceleration mode: gpu, cpu or compare

Definition at line 341 of file random_tree.h.

std::string curfil::TrainingConfiguration::getAccelerationModeString

(

)

const

Returns

acceleration mode as string

uint16_t curfil::TrainingConfiguration::getBoxRadius ( ) const

inline

Returns

the interval from which to sample the offsets of the rectangular regions

Definition at line 292 of file random_tree.h.

const std::vector<int>& curfil::TrainingConfiguration::getDeviceIds ( ) const

inline

Returns

GPU deviceId used for training

Definition at line 365 of file random_tree.h.

unsigned int curfil::TrainingConfiguration::getFeatureCount ( ) const

inline

Returns

number of random feature candidates to sample

Definition at line 271 of file random_tree.h.

const std::vector<std::string>& curfil::TrainingConfiguration::getIgnoredColors ( ) const

inline

Returns

which colors should be ignored when sampling

Definition at line 414 of file random_tree.h.

int curfil::TrainingConfiguration::getImageCacheSize ( ) const

inline

Returns

image cache size on the GPU in Megabytes

Definition at line 327 of file random_tree.h.

int curfil::TrainingConfiguration::getMaxDepth ( ) const

inline

Returns

maximum depth of the tree, training is stopped after that

Definition at line 285 of file random_tree.h.

int curfil::TrainingConfiguration::getMaxImages ( ) const

inline

Returns

number of images to load when training each tree

Definition at line 320 of file random_tree.h.

unsigned int curfil::TrainingConfiguration::getMaxSamplesPerBatch ( ) const

inline

Returns

max number of samples in a batch - depends on the memory and sample size

Definition at line 334 of file random_tree.h.

unsigned int curfil::TrainingConfiguration::getMinSampleCount ( ) const

inline

Returns

minimum number of samples that a node should have to continue splitting

Definition at line 278 of file random_tree.h.

int curfil::TrainingConfiguration::getNumThreads ( ) const

inline

Returns

number of threads used in training

Definition at line 313 of file random_tree.h.

int curfil::TrainingConfiguration::getRandomSeed ( ) const

inline

Returns

the random seed used

Definition at line 257 of file random_tree.h.

uint16_t curfil::TrainingConfiguration::getRegionSize ( ) const

inline

Returns

the interval from which to sample the width and height of the rectangular regions

Definition at line 299 of file random_tree.h.

unsigned int curfil::TrainingConfiguration::getSamplesPerImage ( ) const

inline

Returns

number of pixels to sample per image

Definition at line 264 of file random_tree.h.

std::string curfil::TrainingConfiguration::getSubsamplingType ( ) const

inline

Returns

type of sampling, pixelUniform or classUniform

Definition at line 379 of file random_tree.h.

uint16_t curfil::TrainingConfiguration::getThresholds ( ) const

inline

Returns

number of threshold candidates selected for the evaluation split

Definition at line 306 of file random_tree.h.

bool curfil::TrainingConfiguration::isUseCIELab ( ) const

inline

Returns

whether to convert images to CIELab color space before training

Definition at line 386 of file random_tree.h.

bool curfil::TrainingConfiguration::isUseDepthFilling ( ) const

inline

Returns

whether to do simple depth filling

Definition at line 393 of file random_tree.h.

bool curfil::TrainingConfiguration::isUseDepthImages ( ) const

inline

Returns

whether there are depth images

Definition at line 400 of file random_tree.h.

bool curfil::TrainingConfiguration::operator!= ( const TrainingConfiguration &  other ) const

inline

Returns

whether it's not equal to another configuration

Definition at line 438 of file random_tree.h.

bool curfil::TrainingConfiguration::operator== ( const TrainingConfiguration &  other ) const

inline

Returns

whether it's equal to another configuration, all attributes should match

Definition at line 431 of file random_tree.h.

static AccelerationMode curfil::TrainingConfiguration::parseAccelerationModeString ( const std::string &  modeString )

static

Returns

the acceleration mode from the string representation

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The documentation for this class was generated from the following file:

• src/curfil/random_tree.h