IVALab Python Libraries
Collection of code for computer vision and robotics with specific API.
Public Member Functions | Static Public Member Functions | Public Attributes | List of all members
Detector Class Reference
Inheritance diagram for Detector:
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Collaboration diagram for Detector:
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Public Member Functions

def __init__ (self, detCfg=None, detInst=None, processors=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 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...
 
def process (self, I)
 Apply entire predict to adapt process to source image. More...
 
def saveTo (self, fPtr)
 Save the instantiated Detector to given HDF5 file. More...
 

Static Public Member Functions

def buildFromCfg (theConfig)
 Instantiate from stored configuration file (YAML). More...
 
def calibrate2config (theStream, outFile, initModel=None)
 

Public Attributes

 config
 
 depth
 
 hand
 
 imHand
 
 mask
 

Constructor & Destructor Documentation

◆ __init__()

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

Constructor for layered puzzle scene detector.

Parameters
[in]detCfgDetector configuration.
[in]detInstDetection instances for layer(s).
[in]processorsImage processors for layer(s).

Reimplemented in Calibrator.

Member Function Documentation

◆ adapt()

def adapt (   self)

Adapt the layer detection models.

Does nothing. There may nto be enough information to know how to proceed.

Reimplemented in Calibrator.

◆ buildFromCfg()

def buildFromCfg (   theConfig)
static

Instantiate from stored configuration file (YAML).

◆ calibrate2config()

def calibrate2config (   theStream,
  outFile,
  initModel = None 
)
static

◆ 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 in Calibrator.

◆ 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]ISource RGB-D image (structure/dataclass).

Reimplemented in Calibrator.

◆ emptyDebug()

def emptyDebug (   self)

Reimplemented in Calibrator.

◆ emptyState()

def emptyState (   self)

Get and empty state to recover its basic structure.

Parameters
[out]estateThe empty state.

Reimplemented in Calibrator.

◆ getDebug()

def getDebug (   self)

Reimplemented in Calibrator.

◆ getState()

def getState (   self)

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

Parameters
[out]stateThe detector state for each layer, by layer.

Reimplemented in Calibrator.

◆ info()

def info (   self)

Reimplemented in Calibrator.

◆ load()

def load (   inFile)

◆ loadFrom()

def loadFrom (   fPtr)

◆ measure()

def measure (   self,
  I,
  M = None 
)

Apply detection to the source image pass.

Parameters
[in]IAn RGB-D image (structure/dataclass).
[in]MOptional mask indicate candidate hand regions (true) but with presumption that there may false positives.

◆ 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.

◆ process()

def process (   self,
  I 
)

Apply entire predict to adapt process to source image.

Parameters
[in]ISource RGB-D image (structure/dataclass).

Reimplemented in Calibrator.

◆ 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]fPtrAn HDF5 file point.

Reimplemented in Calibrator.

Member Data Documentation

◆ config

config

◆ depth

depth

◆ hand

hand

◆ imHand

imHand

◆ mask

mask

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