Calibrator Class Reference

Inheritance diagram for Calibrator:

Collaboration diagram for Calibrator:

Public Member Functions
def	__init__ (self, detCfg=None, processors=None, detModel=None)
	Constructor for layered puzzle scene detector. More...
def	adapt (self)
	Adapt the layer detection models. More...
def	correct (self)
	Apply correction process to the individual detectors. More...
def	detect (self, I)
	Apply predict, measure, correct process to source image. More...
def	emptyDebug (self)
def	emptyState (self)
	Get and empty state to recover its basic structure. More...
def	getDebug (self)
def	getState (self)
	Get the complete detector state, which involves the states of the individual layer detectors. More...
def	info (self)
def	measure (self, I)
	Apply detection to the source image pass. More...
def	process (self, I)
	Apply entire predict to adapt process to source image. More...
def	saveConfig (self, outFile)
def	saveTo (self, fPtr)
	Save the instantiated Detector to given HDF5 file. More...
Public Member Functions inherited from Detector
def	load (inFile)
def	loadFrom (fPtr)
def	measure (self, I, M=None)
	Apply detection to the source image pass. More...
def	predict (self)
	Generate prediction of expected measurement. More...

Public Attributes
	depth
	hand
	phase
Public Attributes inherited from Detector
	config
	depth
	hand
	imHand
	mask

Additional Inherited Members
Static Public Member Functions inherited from Detector
def	buildFromCfg (theConfig)
	Instantiate from stored configuration file (YAML). More...
def	calibrate2config (theStream, outFile, initModel=None)

Constructor & Destructor Documentation

__init__()

def __init__	(		self,
			detCfg = None,
			processors = None,
			detModel = None
	)

Constructor for layered puzzle scene detector.

Parameters

[in]	detCfg	Detector configuration.
[in]	processors	Image processors for the different layers.
[in]	detModel	Detection models for the different layers.

Reimplemented from Detector.

Member Function Documentation

adapt()

def adapt

(

self

)

Adapt the layer detection models.

Doing nothing. Need to review.

Todo:

Figure out proper approach here.

Reimplemented from Detector.

correct()

def correct

(

self

)

Apply correction process to the individual detectors.

Apply naive correction on a per detector basis. As a layered system, there might be interdependencies that would impact the correction step. Ignoring that for now since it does not immediately come to mind what needs to be done.

Reimplemented from Detector.

detect()

def detect	(		self,
			I
	)

Apply predict, measure, correct process to source image.

Running detect alone elects not to adapt or update the underlying models. The static model is presumed to be sufficient and applied to the RGBD stream.

Parameters

[in]

I

Source RGB-D image (structure/dataclass).

Reimplemented from Detector.

emptyDebug()

def emptyDebug

(

self

)

Reimplemented from Detector.

emptyState()

def emptyState

(

self

)

Get and empty state to recover its basic structure.

Parameters

[out]

estate

The empty state.

Reimplemented from Detector.

getDebug()

def getDebug

(

self

)

Reimplemented from Detector.

getState()

def getState

(

self

)

Get the complete detector state, which involves the states of the individual layer detectors.

Parameters

[out]

state

The detector state for each layer, by layer.

Reimplemented from Detector.

info()

def info

(

self

)

Reimplemented from Detector.

measure()

def measure	(		self,
			I
	)

Apply detection to the source image pass.

Parameters

[in]

I

An RGB-D image (structure/dataclass).

process()

def process	(		self,
			I
	)

Apply entire predict to adapt process to source image.

Parameters

[in]

I

Source RGB-D image (structure/dataclass).

Reimplemented from Detector.

saveConfig()

def saveConfig	(		self,
			outFile
	)

saveTo()

def saveTo	(		self,
			fPtr
	)

Save the instantiated Detector to given HDF5 file.

The save to function writes the necessary information to re-instantiate a Detectors class object to the passed HDF5 file pointer/instance.

Parameters

[in]

fPtr

An HDF5 file point.

Reimplemented from Detector.

Member Data Documentation

depth

depth

hand

hand

phase

phase

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

• /home/pvela/python/surveillance/Surveillance/layers/HoveringHand.py