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src/x/b/xbob.paper.tpami2013-1.0.0/xbob/paper/tpami2013/scripts/plda_example_iris.py   xbob.paper.tpami2013(Download)
 
  print("Enrolling a class-specific PLDA model given the data...")
  machine = bob.machine.PLDAMachine(pldabase)
  trainer = bob.trainer.PLDATrainer()
  trainer.enrol(machine, data)

src/x/b/xbob.spkrec-1.0.3/xbob/spkrec/tools/IVector.py   xbob.spkrec(Download)
    proj_hdf5file.cd('/plda')
    self.m_plda_base = bob.machine.PLDABase(proj_hdf5file)
    self.m_plda_machine = bob.machine.PLDAMachine(self.m_plda_base)
    self.m_plda_trainer = bob.trainer.PLDATrainer()
 
  def read_plda_model(self, model_file):
    """Reads the model, which in this case is a PLDA-Machine"""
    # read machine and attach base machine
    print ("model: %s" %model_file)
    plda_machine = bob.machine.PLDAMachine(bob.io.HDF5File(str(model_file)), self.m_plda_base)

src/b/o/bob.spear-1.1.2/spear/tools/IVector.py   bob.spear(Download)
    proj_hdf5file.cd('/plda')
    self.m_plda_base = bob.machine.PLDABase(proj_hdf5file)
    self.m_plda_machine = bob.machine.PLDAMachine(self.m_plda_base)
    self.m_plda_trainer = bob.trainer.PLDATrainer()
 
  def read_plda_model(self, model_file):
    """Reads the model, which in this case is a PLDA-Machine"""
    # read machine and attach base machine
    print ("model: %s" %model_file)
    plda_machine = bob.machine.PLDAMachine(bob.io.HDF5File(str(model_file)), self.m_plda_base)

src/f/a/facereclib-1.2.1/facereclib/tools/PLDA.py   facereclib(Download)
    self.m_plda_base = bob.machine.PLDABase(proj_hdf5file)
    #self.m_plda_base = bob.machine.PLDABase(bob.io.HDF5File(projector_file))
    self.m_plda_machine = bob.machine.PLDAMachine(self.m_plda_base)
    self.m_plda_trainer = bob.trainer.PLDATrainer()
 
  def read_model(self, model_file):
    """Reads the model, which in this case is a PLDA-Machine"""
    # read machine and attach base machine
    plda_machine = bob.machine.PLDAMachine(bob.io.HDF5File(model_file), self.m_plda_base)
    return plda_machine

src/f/a/facereclib-HEAD/facereclib/tools/PLDA.py   facereclib(Download)
    self.m_plda_base = bob.machine.PLDABase(proj_hdf5file)
    #self.m_plda_base = bob.machine.PLDABase(bob.io.HDF5File(projector_file))
    self.m_plda_machine = bob.machine.PLDAMachine(self.m_plda_base)
    self.m_plda_trainer = bob.trainer.PLDATrainer()
 
  def read_model(self, model_file):
    """Reads the model, which in this case is a PLDA-Machine"""
    # read machine and attach base machine
    plda_machine = bob.machine.PLDAMachine(bob.io.HDF5File(model_file), self.m_plda_base)
    return plda_machine

src/x/b/xbob.paper.tpami2013-1.0.0/xbob/paper/tpami2013/plda.py   xbob.paper.tpami2013(Download)
def enroll_model(data, pldabase):
  """Enrols a PLDA Machine for a given identity using the provided arrayset
     and trained PLDABase."""
  machine = bob.machine.PLDAMachine(pldabase)
  trainer = bob.trainer.PLDATrainer()
def load_model(plda_model_filename, pldabase):
  if not os.path.exists(plda_model_filename):
    raise RuntimeError("Cannot find PLDAMachine %s" % (plda_model_filename))
  return bob.machine.PLDAMachine(bob.io.HDF5File(plda_model_filename), pldabase)