MLtoolkit

Functions
int	_CRml (mmachine m)
	Create a new neural network Prototype: fun [Chn I F] ObjMl.
int	_DSml (mmachine m)
	destroy a neural network Prototype: fun [ObjMl] I
int	_MlAddDetectionData (mmachine m)
	Get a label for the input Prototype: fun [ObjMl [[F F F] r1]] I.
int	_MlAddTrainingData (mmachine m)
	Add data to learn to the format <input, label> Prototype: fun [ObjMl [[F F F] r1] S] I.
int	_MlTrain (mmachine m)
	Launch the training of the nn Prototype: fun [ObjMl] I.
int	_MlSaveData (mmachine m)
	Save the settings of a trained neural network Prototype: fun [ObjMl W] I.
int	_MlLoadData (mmachine m)
	Load an already trained file neural network AND the used parameters (high level) Prototype: fun [ObjMl P] I.
int	_MlGetCategories (mmachine m)
	Get the ML loaded categories Prototype: fun [ObjMl] [S r1].
int	_CBMlTrainingFinished (mmachine m)
	Set a CB function linked to the finished training signal Prototype: fun [ObjMl fun [ObjMl u0] u1 u0] ObjMl.
int	_CBMlDetect (mmachine m)
	Set a CB function linked to detection signal Prototype: fun [ObjMl fun [ObjMl u0 S] u1 u0] ObjMl.

Detailed Description

Scol functions for Neural network

Function Documentation

_CBMlDetect()

int _CBMlDetect

(

mmachine

m

)

Set a CB function linked to detection signal Prototype: fun [ObjMl fun [ObjMl u0 S] u1 u0] ObjMl.

Returns

I : return the same ObjMl

Definition at line 425 of file MlToolkit.cpp.

_CBMlTrainingFinished()

int _CBMlTrainingFinished

(

mmachine

m

)

Set a CB function linked to the finished training signal Prototype: fun [ObjMl fun [ObjMl u0] u1 u0] ObjMl.

Returns

I : return the same ObjMl

Definition at line 404 of file MlToolkit.cpp.

_CRml()

int _CRml

(

mmachine

m

)

Create a new neural network Prototype: fun [Chn I F] ObjMl.

Parameters

Chn	Scol channel
I	: Mode, 0 for pose detection, 1 for motion detection
I	: Input number
F	: sensibility

Returns

I : return new ObjMl on success or NIL otherwise

Definition at line 63 of file MlToolkit.cpp.

_DSml()

int _DSml

(

mmachine

m

)

destroy a neural network Prototype: fun [ObjMl] I

Parameters

ObjMl

: the ML object

Returns

I : return 0 if success or NIL otherwise

Definition at line 117 of file MlToolkit.cpp.

_MlAddDetectionData()

int _MlAddDetectionData

(

mmachine

m

)

Get a label for the input Prototype: fun [ObjMl [[F F F] r1]] I.

Parameters

ObjMl	: the ML object
[[F	F F] r1] : list of tuple data

Returns

I : return 0 if success or NIL otherwise

Definition at line 148 of file MlToolkit.cpp.

_MlAddTrainingData()

int _MlAddTrainingData

(

mmachine

m

)

Add data to learn to the format <input, label> Prototype: fun [ObjMl [[F F F] r1] S] I.

Parameters

ObjMl	: the ML object
[[F	F F] r1] : list of tuple data
S	: the category name for the data

Returns

I : return 0 if success or NIL otherwise

Definition at line 197 of file MlToolkit.cpp.

_MlGetCategories()

int _MlGetCategories

(

mmachine

m

)

Get the ML loaded categories Prototype: fun [ObjMl] [S r1].

Parameters

ObjMl

: the ML object

Returns

I : return 0 if success or NIL otherwise

Definition at line 353 of file MlToolkit.cpp.

_MlLoadData()

int _MlLoadData

(

mmachine

m

)

Load an already trained file neural network AND the used parameters (high level) Prototype: fun [ObjMl P] I.

Parameters

ObjMl	: the ML object
P	: the ML data file

Returns

I : return 0 if success or NIL otherwise

Definition at line 320 of file MlToolkit.cpp.

_MlSaveData()

int _MlSaveData

(

mmachine

m

)

Save the settings of a trained neural network Prototype: fun [ObjMl W] I.

Parameters

ObjMl	: the ML object
W	: file to write

Returns

I : return 0 if success or NIL otherwise

Definition at line 278 of file MlToolkit.cpp.

_MlTrain()

int _MlTrain

(

mmachine

m

)

Launch the training of the nn Prototype: fun [ObjMl] I.

Parameters

ObjMl

: the ML object

Returns

I : return 0 if success or NIL otherwise

Definition at line 247 of file MlToolkit.cpp.