Specifies the parameters for the MultiBoxLossParameter. More...

Inheritance diagram for MyCaffe.param.ssd.MultiBoxLossParameter:

Public Types
enum	LocLossType { L2 , SMOOTH_L1 }
	Defines the localization loss types. More...

enum	ConfLossType { SOFTMAX , LOGISTIC }
	Defines the confidence loss types. More...

enum	MatchType { BIPARTITE , PER_PREDICTION }
	Defines the matching method used during training. More...

enum	MiningType { NONE , MAX_NEGATIVE , HARD_EXAMPLE }
	Defines the mining type used during training. More...

Public Types inherited from MyCaffe.param.LayerParameterBase
enum	LABEL_TYPE { NONE , SINGLE , MULTIPLE , ONLY_ONE }
	Defines the label type. More...

Public Member Functions
	MultiBoxLossParameter ()
	The constructor. More...

override object	Load (BinaryReader br, bool bNewInstance=true)
	Load the parameter from a binary reader. More...

override void	Copy (LayerParameterBase src)
	Copy on parameter to another. More...

override LayerParameterBase	Clone ()
	Creates a new copy of this instance of the parameter. More...

override RawProto	ToProto (string strName)
	Convert the parameter into a RawProto. More...

Public Member Functions inherited from MyCaffe.param.LayerParameterBase
	LayerParameterBase ()
	Constructor for the parameter. More...

virtual string	PrepareRunModelInputs ()
	This method gives derivative classes a chance specify model inputs required by the run model. More...

virtual void	PrepareRunModel (LayerParameter p)
	This method gives derivative classes a chance to prepare the layer for a run-model. More...

void	Save (BinaryWriter bw)
	Save this parameter to a binary writer. More...

Public Member Functions inherited from MyCaffe.basecode.BaseParameter
	BaseParameter ()
	Constructor for the parameter. More...

virtual bool	Compare (BaseParameter p)
	Compare this parameter to another parameter. More...

Static Public Member Functions
static LocLossType	LocLossTypeFromString (string str)
	Convert a string into a LocLossType. More...

static ConfLossType	ConfLossTypeFromString (string str)
	Convert a string into a ConfLossType. More...

static MatchType	MatchTypeFromString (string str)
	Convert a string into a MatchType. More...

static MiningType	MiningTypeFromString (string str)
	Convert a string into a MiningType. More...

static MultiBoxLossParameter	FromProto (RawProto rp)
	Parses the parameter from a RawProto. More...

Static Public Member Functions inherited from MyCaffe.basecode.BaseParameter
static double	ParseDouble (string strVal)
	Parse double values using the US culture if the decimal separator = '.', then using the native culture, and if then lastly trying the US culture to handle prototypes containing '.' as the separator, yet parsed in a culture that does not use '.' as a decimal. More...

static bool	TryParse (string strVal, out double df)
	Parse double values using the US culture if the decimal separator = '.', then using the native culture, and if then lastly trying the US culture to handle prototypes containing '.' as the separator, yet parsed in a culture that does not use '.' as a decimal. More...

static float	ParseFloat (string strVal)
	Parse float values using the US culture if the decimal separator = '.', then using the native culture, and if then lastly trying the US culture to handle prototypes containing '.' as the separator, yet parsed in a culture that does not use '.' as a decimal. More...

static bool	TryParse (string strVal, out float f)
	Parse doufloatble values using the US culture if the decimal separator = '.', then using the native culture, and if then lastly trying the US culture to handle prototypes containing '.' as the separator, yet parsed in a culture that does not use '.' as a decimal. More...

Properties
LocLossType	loc_loss_type `[getset]`
	Get/set the localization loss type (default = SMOOTH_L1). More...

ConfLossType	conf_loss_type `[getset]`
	Get/set the confidence loss type (default = SOFTMAX). More...

float	loc_weight `[getset]`
	Get/set the weight for the localization loss (default = 1.0). More...

uint	num_classes `[getset]`
	Get/set the number of classes to be predicted - required! More...

bool	share_location `[getset]`
	Get/sets whether or not the bounding box is shared among different classes (default = true). More...

MatchType	match_type `[getset]`
	Get/set the matching method used during training (default = PER_PREDICTION). More...

float	overlap_threshold `[getset]`
	Get/set the overlap threshold (default = 0.5). More...

uint	background_label_id `[getset]`
	Get/set the background label id. More...

bool	use_difficult_gt `[getset]`
	Get/set whether or not to consider the difficult ground truth (defalt = true). More...

bool?	do_neg_mining `[getset]`
	DEPRECIATED: Get/set whether or not to perform negative mining (default = false). More...

float	neg_pos_ratio `[getset]`
	Get/set the negative/positive ratio (default = 3.0). More...

float	neg_overlap `[getset]`
	Get/set the negative overlap upperbound for the unmatched predictions (default = 0.5). More...

PriorBoxParameter.CodeType	code_type `[getset]`
	Get/set the coding method for the bounding box. More...

bool	encode_variance_in_target `[getset]`
	Get/set whether or not to encode the variance of the prior box in the loc loss target instead of in the bbox (default = false). More...

bool	map_object_to_agnostic `[getset]`
	Get/set whether or not to map all object classes to an agnostic class (default = false). This is useful when learning objectness detector. More...

bool	ignore_cross_boundary_bbox `[getset]`
	Get/set whether or not to ignore cross boundary bbox during matching (default = false). The cross boundary bbox is a bbox who is outside of the image region. More...

bool	bp_inside `[getset]`
	Get/set whether or not to only backpropagate on corners which are inside of the image region when encode type is CORNER or CORNER_SIZE (default = false). More...

MiningType	mining_type `[getset]`
	Get/set the mining type used during training (default = MAX_NEGATIVE). More...

NonMaximumSuppressionParameter	nms_param `[getset]`
	Get/set the parameters used for the non maximum suppression during hard example training. More...

int	sample_size `[getset]`
	Get/set the number of samples (default = 64). More...

bool	use_prior_for_nms `[getset]`
	Get/set whether or not to use the prior bbox for nms. More...

bool	use_prior_for_matching `[getset]`
	Get/set whether or not to use prior for matching. More...

bool	use_gpu `[getset]`
	Use the GPU version of the algorithm. More...

Detailed Description

Specifies the parameters for the MultiBoxLossParameter.

See also: SSD: Single Shot MultiBox Detector by Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg, 2016.; GitHub: SSD: Single Shot MultiBox Detector, by weiliu89/caffe, 2016; Training Region-based Object Detectors with Online Hard Example Mining by Abhinav Shrivastava, Abhinav Gupta, Ross Girshick, 2016.

Definition at line 22 of file MultiBoxLossParameter.cs.

Member Enumeration Documentation

◆ ConfLossType

enum MyCaffe.param.ssd.MultiBoxLossParameter.ConfLossType

Defines the confidence loss types.

Enumerator
SOFTMAX	Specifies to use softmax.
LOGISTIC	Specifies to use logistic.

Definition at line 86 of file MultiBoxLossParameter.cs.

◆ LocLossType

enum MyCaffe.param.ssd.MultiBoxLossParameter.LocLossType

Defines the localization loss types.

Enumerator
L2	Specifies to use L2 loss.
SMOOTH_L1	Specifies to use smooth L1 loss.

Definition at line 51 of file MultiBoxLossParameter.cs.

◆ MatchType

enum MyCaffe.param.ssd.MultiBoxLossParameter.MatchType

Defines the matching method used during training.

Enumerator
BIPARTITE	Specifies to use Bi-Partite.
PER_PREDICTION	Specifies to use per-prediction matching.

Definition at line 121 of file MultiBoxLossParameter.cs.

◆ MiningType

enum MyCaffe.param.ssd.MultiBoxLossParameter.MiningType

Defines the mining type used during training.

Enumerator

NONE

Use all negatives.

MAX_NEGATIVE

Select negatives based on the score.

HARD_EXAMPLE

Select hard examples based on Shrivastava et. al. method.

See also: Training Region-based Object Detectors with Online Hard Example Mining by Abhinav Shrivastava, Abhinav Gupta, Ross Girshick, 2016.

Definition at line 157 of file MultiBoxLossParameter.cs.

Constructor & Destructor Documentation

◆ MultiBoxLossParameter()

MyCaffe.param.ssd.MultiBoxLossParameter.MultiBoxLossParameter ( )

The constructor.

Definition at line 203 of file MultiBoxLossParameter.cs.

Member Function Documentation

◆ Clone()

override LayerParameterBase MyCaffe.param.ssd.MultiBoxLossParameter.Clone ( )

virtual

Creates a new copy of this instance of the parameter.

Returns: A new instance of this parameter is returned.

Implements MyCaffe.param.LayerParameterBase.

Definition at line 495 of file MultiBoxLossParameter.cs.

◆ ConfLossTypeFromString()

static ConfLossType MyCaffe.param.ssd.MultiBoxLossParameter.ConfLossTypeFromString ( string str )

static

Convert a string into a ConfLossType.

Parameters

str	Specifies the string.

Returns: The associated ConfLossType is returned.

Definition at line 103 of file MultiBoxLossParameter.cs.

◆ Copy()

override void MyCaffe.param.ssd.MultiBoxLossParameter.Copy ( LayerParameterBase src )

virtual

Copy on parameter to another.

Parameters

src	Specifies the parameter to copy.

Implements MyCaffe.param.LayerParameterBase.

Definition at line 462 of file MultiBoxLossParameter.cs.

◆ FromProto()

static MultiBoxLossParameter MyCaffe.param.ssd.MultiBoxLossParameter.FromProto ( RawProto rp )

static

Parses the parameter from a RawProto.

Parameters

rp	Specifies the RawProto to parse.

Returns: A new instance of the parameter is returned.

Definition at line 543 of file MultiBoxLossParameter.cs.

◆ Load()

override object MyCaffe.param.ssd.MultiBoxLossParameter.Load	(	BinaryReader	br,
		bool	bNewInstance = `true`
	)

virtual

Load the parameter from a binary reader.

Parameters

br	Specifies the binary reader.
bNewInstance	When true a new instance is created (the default), otherwise the existing instance is loaded from the binary reader.

Returns: Returns an instance of the parameter.

Implements MyCaffe.param.LayerParameterBase.

Definition at line 447 of file MultiBoxLossParameter.cs.

◆ LocLossTypeFromString()

static LocLossType MyCaffe.param.ssd.MultiBoxLossParameter.LocLossTypeFromString ( string str )

static

Convert a string into a LocLossType.

Parameters

str	Specifies the string.

Returns: The associated LocLossType is returned.

Definition at line 68 of file MultiBoxLossParameter.cs.

◆ MatchTypeFromString()

static MatchType MyCaffe.param.ssd.MultiBoxLossParameter.MatchTypeFromString ( string str )

static

Convert a string into a MatchType.

Parameters

str	Specifies the string.

Returns: The associated MatchType is returned.

Definition at line 138 of file MultiBoxLossParameter.cs.

◆ MiningTypeFromString()

static MiningType MyCaffe.param.ssd.MultiBoxLossParameter.MiningTypeFromString ( string str )

static

Convert a string into a MiningType.

Parameters

str	Specifies the string.

Returns: The associated MiningType is returned.

Definition at line 181 of file MultiBoxLossParameter.cs.

◆ ToProto()

override RawProto MyCaffe.param.ssd.MultiBoxLossParameter.ToProto ( string strName )

virtual

Convert the parameter into a RawProto.

Parameters

strName Specifies the name to associate with the RawProto.

Returns: The new RawProto is returned.

Implements MyCaffe.basecode.BaseParameter.

Definition at line 507 of file MultiBoxLossParameter.cs.

Property Documentation

◆ background_label_id

uint MyCaffe.param.ssd.MultiBoxLossParameter.background_label_id

getset

Get/set the background label id.

Definition at line 281 of file MultiBoxLossParameter.cs.

◆ bp_inside

bool MyCaffe.param.ssd.MultiBoxLossParameter.bp_inside

getset

Get/set whether or not to only backpropagate on corners which are inside of the image region when encode type is CORNER or CORNER_SIZE (default = false).

Definition at line 375 of file MultiBoxLossParameter.cs.

◆ code_type

PriorBoxParameter.CodeType MyCaffe.param.ssd.MultiBoxLossParameter.code_type

getset

Get/set the coding method for the bounding box.

Definition at line 334 of file MultiBoxLossParameter.cs.

◆ conf_loss_type

ConfLossType MyCaffe.param.ssd.MultiBoxLossParameter.conf_loss_type

getset

Get/set the confidence loss type (default = SOFTMAX).

Definition at line 221 of file MultiBoxLossParameter.cs.

◆ do_neg_mining

bool? MyCaffe.param.ssd.MultiBoxLossParameter.do_neg_mining

getset

DEPRECIATED: Get/set whether or not to perform negative mining (default = false).

DEPRECIATED: using 'mining_type' instead.

Definition at line 304 of file MultiBoxLossParameter.cs.

◆ encode_variance_in_target

bool MyCaffe.param.ssd.MultiBoxLossParameter.encode_variance_in_target

getset

Get/set whether or not to encode the variance of the prior box in the loc loss target instead of in the bbox (default = false).

Definition at line 344 of file MultiBoxLossParameter.cs.

◆ ignore_cross_boundary_bbox

bool MyCaffe.param.ssd.MultiBoxLossParameter.ignore_cross_boundary_bbox

getset

Get/set whether or not to ignore cross boundary bbox during matching (default = false). The cross boundary bbox is a bbox who is outside of the image region.

Definition at line 365 of file MultiBoxLossParameter.cs.

◆ loc_loss_type

LocLossType MyCaffe.param.ssd.MultiBoxLossParameter.loc_loss_type

getset

Get/set the localization loss type (default = SMOOTH_L1).

Definition at line 211 of file MultiBoxLossParameter.cs.

◆ loc_weight

float MyCaffe.param.ssd.MultiBoxLossParameter.loc_weight

getset

Get/set the weight for the localization loss (default = 1.0).

Definition at line 231 of file MultiBoxLossParameter.cs.

◆ map_object_to_agnostic

bool MyCaffe.param.ssd.MultiBoxLossParameter.map_object_to_agnostic

getset

Get/set whether or not to map all object classes to an agnostic class (default = false). This is useful when learning objectness detector.

Definition at line 354 of file MultiBoxLossParameter.cs.

◆ match_type

MatchType MyCaffe.param.ssd.MultiBoxLossParameter.match_type

getset

Get/set the matching method used during training (default = PER_PREDICTION).

Definition at line 261 of file MultiBoxLossParameter.cs.

◆ mining_type

MiningType MyCaffe.param.ssd.MultiBoxLossParameter.mining_type

getset

Get/set the mining type used during training (default = MAX_NEGATIVE).

Definition at line 385 of file MultiBoxLossParameter.cs.

◆ neg_overlap

float MyCaffe.param.ssd.MultiBoxLossParameter.neg_overlap

getset

Get/set the negative overlap upperbound for the unmatched predictions (default = 0.5).

Definition at line 324 of file MultiBoxLossParameter.cs.

◆ neg_pos_ratio

float MyCaffe.param.ssd.MultiBoxLossParameter.neg_pos_ratio

getset

Get/set the negative/positive ratio (default = 3.0).

Definition at line 314 of file MultiBoxLossParameter.cs.

◆ nms_param

NonMaximumSuppressionParameter MyCaffe.param.ssd.MultiBoxLossParameter.nms_param

getset

Get/set the parameters used for the non maximum suppression during hard example training.

Definition at line 395 of file MultiBoxLossParameter.cs.

◆ num_classes

uint MyCaffe.param.ssd.MultiBoxLossParameter.num_classes

getset

Get/set the number of classes to be predicted - required!

Definition at line 241 of file MultiBoxLossParameter.cs.

◆ overlap_threshold

float MyCaffe.param.ssd.MultiBoxLossParameter.overlap_threshold

getset

Get/set the overlap threshold (default = 0.5).

Definition at line 271 of file MultiBoxLossParameter.cs.

◆ sample_size

int MyCaffe.param.ssd.MultiBoxLossParameter.sample_size

getset

Get/set the number of samples (default = 64).

Definition at line 405 of file MultiBoxLossParameter.cs.

◆ share_location

bool MyCaffe.param.ssd.MultiBoxLossParameter.share_location

getset

Get/sets whether or not the bounding box is shared among different classes (default = true).

Definition at line 251 of file MultiBoxLossParameter.cs.

◆ use_difficult_gt

bool MyCaffe.param.ssd.MultiBoxLossParameter.use_difficult_gt

getset

Get/set whether or not to consider the difficult ground truth (defalt = true).

Definition at line 291 of file MultiBoxLossParameter.cs.

◆ use_gpu

bool MyCaffe.param.ssd.MultiBoxLossParameter.use_gpu

getset

Use the GPU version of the algorithm.

Definition at line 435 of file MultiBoxLossParameter.cs.

◆ use_prior_for_matching

bool MyCaffe.param.ssd.MultiBoxLossParameter.use_prior_for_matching

getset

Get/set whether or not to use prior for matching.

Definition at line 425 of file MultiBoxLossParameter.cs.

◆ use_prior_for_nms

bool MyCaffe.param.ssd.MultiBoxLossParameter.use_prior_for_nms

getset

Get/set whether or not to use the prior bbox for nms.

Definition at line 415 of file MultiBoxLossParameter.cs.

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

C:/Data/Data/SS_Projects/Intelligence/GitHub/MyCaffe/MyCaffe/param.ssd/MultiBoxLossParameter.cs

Public Types

Public Member Functions

Static Public Member Functions

Properties

Detailed Description

Member Enumeration Documentation

◆ ConfLossType

◆ LocLossType

◆ MatchType

◆ MiningType

Constructor & Destructor Documentation

◆ MultiBoxLossParameter()

Member Function Documentation

◆ Clone()

◆ ConfLossTypeFromString()

◆ Copy()

◆ FromProto()

◆ Load()

◆ LocLossTypeFromString()

◆ MatchTypeFromString()

◆ MiningTypeFromString()

◆ ToProto()

Property Documentation

◆ background_label_id

◆ bp_inside

◆ code_type

◆ conf_loss_type

◆ do_neg_mining

◆ encode_variance_in_target

◆ ignore_cross_boundary_bbox

◆ loc_loss_type

◆ loc_weight

◆ map_object_to_agnostic

◆ match_type

◆ mining_type

◆ neg_overlap

◆ neg_pos_ratio

◆ nms_param

◆ num_classes

◆ overlap_threshold

◆ sample_size

◆ share_location

◆ use_difficult_gt

◆ use_gpu

◆ use_prior_for_matching

◆ use_prior_for_nms