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src/x/b/xbob.thesis.elshafey2014-0.0.1a0/xbob/thesis/elshafey2014/utils/miris.py   xbob.thesis.elshafey2014(Download)
  ubm.acc_statistics(sample, gs)
  ux = numpy.zeros((4,), numpy.float64)
  isvmachine.estimate_ux(gs, ux)
 
  figure = mpl.figure()

src/m/a/maskattack.study-1.0.0/maskattack/study/analyze/isv.py   maskattack.study(Download)
      array_isv = numpy.ndarray(shape=(ubm.dim_c*ubm.dim_d,), dtype=numpy.float64)
      isv_machine = bob.machine.ISVMachine(isvbase)
      isv_machine.estimate_ux(array[i][j], array_isv)
      list.append(array_isv)
    array_proj.append(list)

src/x/b/xbob.spkrec-1.0.3/xbob/spkrec/tools/ISV.py   xbob.spkrec(Download)
 
    model = bob.machine.ISVMachine(self.m_isvbase)
    model.estimate_ux(projected_ubm, projected_isv)
    #
    return [projected_ubm, projected_isv]

src/b/o/bob.spear-1.1.2/spear/tools/ISV.py   bob.spear(Download)
 
    model = bob.machine.ISVMachine(self.m_isvbase)
    model.estimate_ux(projected_ubm, projected_isv)
    #
    return [projected_ubm, projected_isv]

src/f/a/facereclib-1.2.1/facereclib/tools/ISV.py   facereclib(Download)
  def _project_isv(self, projected_ubm):
    projected_isv = numpy.ndarray(shape=(self.m_ubm.dim_c*self.m_ubm.dim_d,), dtype=numpy.float64)
    model = bob.machine.ISVMachine(self.m_isvbase)
    model.estimate_ux(projected_ubm, projected_isv)
    return projected_isv

src/f/a/facereclib-HEAD/facereclib/tools/ISV.py   facereclib(Download)
  def _project_isv(self, projected_ubm):
    projected_isv = numpy.ndarray(shape=(self.m_ubm.dim_c*self.m_ubm.dim_d,), dtype=numpy.float64)
    model = bob.machine.ISVMachine(self.m_isvbase)
    model.estimate_ux(projected_ubm, projected_isv)
    return projected_isv