Calibrator Class Reference

Layered calibration class for puzzle surveillance system. More...

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	predict (self)
	Generate prediction of expected measurement. 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 Detectors
def	loadFrom (fPtr)

Public Attributes
	depth
	glove
	phase
	workspace
Public Attributes inherited from Detectors
	depth
	glove
	imGlove
	First, perform any specified pre-processing. More...
	imPuzzle
	mask
	workspace

Additional Inherited Members
Static Public Member Functions inherited from Detectors
def	buildFromCfg (theConfig)
	Instantiate from stored configuration file (YAML). More...
def	calibrate2config (theStream, outFile)
def	load (inFile)

Detailed Description

Layered calibration class for puzzle surveillance system.

A calibration scheme for the entire process with saving to YAML and HDF5 files.

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 Detectors.

Member Function Documentation

adapt()

def adapt

(

self

)

Adapt the layer detection models.

This part is tricky as there may be dependencies across the layers in terms of what should be updated and what should not be. Applying simple filtering to establish what pixels should adapt and which ones shouldn't.

Reimplemented from Detectors.

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 Detectors.

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 Detectors.

emptyDebug()

def emptyDebug

(

self

)

Reimplemented from Detectors.

emptyState()

def emptyState

(

self

)

Get and empty state to recover its basic structure.

Parameters

[out]

estate

The empty state.

Reimplemented from Detectors.

getDebug()

def getDebug

(

self

)

Reimplemented from Detectors.

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 Detectors.

info()

def info

(

self

)

Reimplemented from Detectors.

measure()

def measure	(		self,
			I
	)

Apply detection to the source image pass.

Parameters

[in]

I

An RGB-D image (structure/dataclass).

Reimplemented from Detectors.

predict()

def predict

(

self

)

Generate prediction of expected measurement.

The detectors are mostly going to be static models, which means that prediction does nothing. Just in case though, the prediction methods are called for them.

Reimplemented from Detectors.

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 Detectors.

saveConfig()

def saveConfig	(		self,
			outFile
	)

saveTo()

def saveTo	(		self,
			fPtr
	)

Save the instantiated Detector to given HDF5 file.

The save process saves the necessary information to re-instantiate a Detectors class object.

Parameters

[in]

fPtr

An HDF5 file point.

Reimplemented from Detectors.

Member Data Documentation

depth

depth

glove

glove

phase

phase

workspace

workspace

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

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