IVALab Python Libraries
Collection of code for computer vision and robotics with specific API.
Classes | Functions
Surveillance.layers.Glove Namespace Reference

Detector, track pointer, and perceiver classes for glove tracking. More...

Classes

class  Calibrator
 
class  CfgGloveDetector
 Configuration instance for glove tracking perceiver. More...
 
class  Detector
 
class  DetectorState
 
class  InstGloveDetector
 Class for collecting visual processing methods needed by the PuzzleScene scene interpreter. More...
 
class  InstGlovePerceiver
 Class for collecting visual processing methods needed by the PuzzleScene perceiver. More...
 
class  Perceiver
 
class  TrackPointer
 

Functions

def __init__ (self, perCfg=None, perInst=None)
 
def adapt (self)
 
def correct (self)
 
def detect (self)
 
def emptyDebug (self)
 
def emptyState (self)
 
def getDebugState (self)
 
def getState (self)
 
def measure (self, I)
 
def predict (self)
 
def process (self, I)
 

Detailed Description

Detector, track pointer, and perceiver classes for glove tracking.

Follows the structure of the Puzzle Scene perceiver, which packages everything into one file since python has individual import facilities, and placing in one uniform location simplifies things.

Code here is copied from the Puzzle Scene glove tracker classes. The reason that they were all mashed together in Puzzle Scene is to take advantage of common image processing and not separate things such that efforts to reduce repeated computation make the data passing too complex. Changes should be mirrored across these two files.

What should be contained in this file would be:

  1. Glove layer detector from RGBD input.
  2. Glove trackpointer based on layered detector output.
  3. Perceiver that combines detector + trackpointer.
  4. A calibration scheme for the entire process with saving to YAML and HDF5 files.

This single file replaces/supercedes the existing human_seg file in this directory (and by extension possibly others, like base_fg).

Function Documentation

◆ __init__()

def Surveillance.layers.Glove.__init__ (   self,
  perCfg = None,
  perInst = None 
)

◆ adapt()

def Surveillance.layers.Glove.adapt (   self)

◆ correct()

def Surveillance.layers.Glove.correct (   self)

◆ detect()

def Surveillance.layers.Glove.detect (   self)

◆ emptyDebug()

def Surveillance.layers.Glove.emptyDebug (   self)

◆ emptyState()

def Surveillance.layers.Glove.emptyState (   self)

◆ getDebugState()

def Surveillance.layers.Glove.getDebugState (   self)

◆ getState()

def Surveillance.layers.Glove.getState (   self)

◆ measure()

def Surveillance.layers.Glove.measure (   self,
  I 
)

◆ predict()

def Surveillance.layers.Glove.predict (   self)

◆ process()

def Surveillance.layers.Glove.process (   self,
  I 
)