bob.machine.GMMMachine.set_variance_thresholds

All Samples(31) | Call(31) | Derive(0) | Import(0)

src/a/n/antispoofing.verification.gmm-1.0.2/antispoofing/verification/gmm/__init__.py antispoofing.verification.gmm(Download)

  gmm.variances = variances
  gmm.weights = weights
  gmm.set_variance_thresholds(variance_threshold)
 
  # Trains the GMM

      raise RuntimeError, "Cannot find UBM %s" % (ubm_filename)
  ubm = bob.machine.GMMMachine(bob.io.HDF5File(ubm_filename))    
  ubm.set_variance_thresholds(variance_threshold)
 
  # Creates the trainer

  # Creates a GMM from the UBM
  gmm = bob.machine.GMMMachine(ubm)
  gmm.set_variance_thresholds(variance_threshold)
 
  # Trains the GMM

src/x/b/xbob.thesis.elshafey2014-0.0.1a0/xbob/thesis/elshafey2014/tools/ParaUBMGMM.py xbob.thesis.elshafey2014(Download)

      gmm_machine.variances = variances
      gmm_machine.weights = weights
      gmm_machine.set_variance_thresholds(self.m_tool.m_variance_threshold)
 
      utils.ensure_dir(os.path.dirname(output_file))

src/f/a/facereclib-1.2.1/facereclib/tools/ParallelUBMGMM.py facereclib(Download)

      gmm_machine.variances = variances
      gmm_machine.weights = weights
      gmm_machine.set_variance_thresholds(self.m_tool.m_variance_threshold)
 
      utils.ensure_dir(os.path.dirname(output_file))

src/x/b/xbob.spkrec-1.0.3/xbob/spkrec/script/ParallelUBMGMM.py xbob.spkrec(Download)

      gmm_machine.variances = variances
      gmm_machine.weights = weights
      gmm_machine.set_variance_thresholds(self.m_tool.m_variance_threshold)
 
      utils.ensure_dir(os.path.dirname(output_file))

src/f/a/facereclib-HEAD/facereclib/tools/ParallelUBMGMM.py facereclib(Download)

      gmm_machine.variances = variances
      gmm_machine.weights = weights
      gmm_machine.set_variance_thresholds(self.m_tool.m_variance_threshold)
 
      utils.ensure_dir(os.path.dirname(output_file))

src/b/o/bob.spear-1.1.2/spear/script/ParallelUBMGMM.py bob.spear(Download)

      gmm_machine.variances = variances
      gmm_machine.weights = weights
      gmm_machine.set_variance_thresholds(self.m_tool.m_variance_threshold)
 
      utils.ensure_dir(os.path.dirname(output_file))

src/f/a/facereclib-1.2.1/facereclib/tools/UBMGMM.py facereclib(Download)

    self.m_ubm.variances = variances
    self.m_ubm.weights = weights
    self.m_ubm.set_variance_thresholds(self.m_variance_threshold)
 
    # Trains the GMM

  def load_projector(self, projector_file):
    """Reads the UBM model from file"""
    # read UBM
    self.m_ubm = bob.machine.GMMMachine(bob.io.HDF5File(projector_file))
    self.m_ubm.set_variance_thresholds(self.m_variance_threshold)

  def _enroll_using_array(self, array):
    utils.debug(" .... Enrolling with %d feature vectors" % array.shape[0])
 
    gmm = bob.machine.GMMMachine(self.m_ubm)
    gmm.set_variance_thresholds(self.m_variance_threshold)

src/x/b/xbob.spkrec-1.0.3/xbob/spkrec/preprocessing/Energy.py xbob.spkrec(Download)

    m_ubm.variances = variances
    m_ubm.weights = weights
    m_ubm.set_variance_thresholds(0.0005)
 
    trainer = bob.trainer.ML_GMMTrainer(True, True, True)

src/x/b/xbob.thesis.elshafey2014-0.0.1a0/xbob/thesis/elshafey2014/tools/JFA.py xbob.thesis.elshafey2014(Download)

  def _load_projector_gmm_resolved(self, gmm_filename):
    self.m_ubm = bob.machine.GMMMachine(bob.io.HDF5File(gmm_filename))
    self.m_ubm.set_variance_thresholds(self.m_variance_threshold)
    # Initializes GMMStats object
    self.m_gmm_stats = bob.machine.GMMStats(self.m_ubm.dim_c, self.m_ubm.dim_d)

    # read UBM
    self.m_ubm = bob.machine.GMMMachine(hdf5file)
    self.m_ubm.set_variance_thresholds(self.m_variance_threshold)
    # Initializes GMMStats object
    self.m_gmm_stats = bob.machine.GMMStats(self.m_ubm.dim_c, self.m_ubm.dim_d)

src/x/b/xbob.thesis.elshafey2014-0.0.1a0/xbob/thesis/elshafey2014/tools/IVector.py xbob.thesis.elshafey2014(Download)

  def _load_projector_gmm_resolved(self, gmm_filename):
    self.m_ubm = bob.machine.GMMMachine(bob.io.HDF5File(gmm_filename))
    self.m_ubm.set_variance_thresholds(self.m_variance_threshold)
    # Initializes GMMStats object
    self.m_gmm_stats = bob.machine.GMMStats(self.m_ubm.dim_c, self.m_ubm.dim_d)

    # read UBM
    self.m_ubm = bob.machine.GMMMachine(hdf5file)
    self.m_ubm.set_variance_thresholds(self.m_variance_threshold)
    # Initializes GMMStats object
    self.m_gmm_stats = bob.machine.GMMStats(self.m_ubm.dim_c, self.m_ubm.dim_d)

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