diff --git a/bob/learn/misc/include/bob.learn.misc/BICMachine.h b/bob/learn/misc/include/bob.learn.misc/BICMachine.h
deleted file mode 100644
index 827537bfbadfe3ae385d4615a79d10b2ba3bc354..0000000000000000000000000000000000000000
--- a/bob/learn/misc/include/bob.learn.misc/BICMachine.h
+++ /dev/null
@@ -1,109 +0,0 @@
-/**
- * @date Tue Jun 5 16:54:27 CEST 2012
- * @author Manuel Guenther <Manuel.Guenther@idiap.ch>
- *
- * Copyright (C) Idiap Research Institute, Martigny, Switzerland
- */
-
-
-#ifndef BOB_LEARN_MISC_BICMACHINE_H
-#define BOB_LEARN_MISC_BICMACHINE_H
-
-#include <blitz/array.h>
-#include <bob.io.base/HDF5File.h>
-#include <bob.learn.misc/Machine.h>
-
-namespace bob { namespace learn { namespace misc {
- /**
- * This class computes the Bayesian Intrapersonal/Extrapersonal Classifier (BIC),
- * (see "Beyond Eigenfaces: Probabilistic Matching for Face Recognition" from Moghaddam, Wahid and Pentland)
- * which estimates the posterior probability that the given <b>image difference vector</b>
- * is of the intrapersonal class, i.e., both images stem from the same person.
- *
- * There are two possible implementations of the BIC:
- * <ul>
- * <li> "The Bayesian Intrapersonal/Extrapersonal Classifier" from Teixeira.<br>
- * A full projection of the data is performed. No prior for the classes has to be selected.</li>
- *
- * <li> "Face Detection and Recognition using Maximum Likelihood Classifiers on Gabor Graphs" from Günther and Würtz.<br>
- * Only mean and variance of the difference vectors are calculated. There is no subspace truncation and no priors.</li>
- * </ul>
- * In any of the two implementations, the resulting score (using the forward() method) is a log-likelihood estimate,
- * using Mahalanobis(-like) distance measures.
- *
- */
- class BICMachine: public Machine<blitz::Array<double,1>, double>
- {
- public:
- //! generates an empty BIC machine
- BICMachine(bool use_DFFS = false);
-
- //! Copy constructor
- BICMachine(const BICMachine& other);
-
- //! Assignment Operator
- BICMachine& operator =(const BICMachine &other);
-
- //! Equality operator
- bool operator ==(const BICMachine& other) const;
-
- //! Inequality operator
- bool operator !=(const BICMachine& other) const;
-
- //! Similarity operator
- bool is_similar_to(const BICMachine& other, const double r_epsilon=1e-5, const double a_epsilon=1e-8) const;
-
- //! computes the BIC probability score for the given input difference vector
- void forward_(const blitz::Array<double,1>& input, double& output) const;
-
- //! performs some checks before calling the forward_ method
- void forward (const blitz::Array<double,1>& input, double& output) const;
-
- //! sets the IEC vectors of the given class
- void setIEC(bool clazz, const blitz::Array<double,1>& mean, const blitz::Array<double,1>& variances, bool copy_data = false);
-
- //! sets the BIC projection details of the given class
- void setBIC(bool clazz, const blitz::Array<double,1>& mean, const blitz::Array<double,1>& variances, const blitz::Array<double,2>& projection, const double rho, bool copy_data = false);
-
- //! loads this machine from the given hdf5 file.
- void load (bob::io::base::HDF5File& config);
-
- //! saves this machine to the given hdf5 file.
- void save (bob::io::base::HDF5File& config) const;
-
- //! Use the Distance From Feature Space
- void use_DFFS(bool use_DFFS = true);
-
- //! Use the Distance From Feature Space
- bool use_DFFS() const {return m_use_DFFS;}
-
- private:
-
- //! initializes internal data storages for the given class
- void initialize(bool clazz, int input_length, int projected_length);
-
- //! project data?
- bool m_project_data;
-
- //! mean vectors
- blitz::Array<double, 1> m_mu_I, m_mu_E;
- //! variances (eigenvalues)
- blitz::Array<double, 1> m_lambda_I, m_lambda_E;
-
- ///
- // only required when projection is enabled
- //! add the distance from feature space?
- bool m_use_DFFS;
- //! projection matrices (PCA)
- blitz::Array<double, 2> m_Phi_I, m_Phi_E;
- //! averaged eigenvalues to calculate DFFS
- double m_rho_I, m_rho_E;
- //! temporary storage
- mutable blitz::Array<double, 1> m_diff_I, m_diff_E;
- mutable blitz::Array<double, 1> m_proj_I, m_proj_E;
-
- };
-
-} } } // namespaces
-
-#endif // BOB_LEARN_MISC_BICMACHINE_H
diff --git a/bob/learn/misc/include/bob.learn.misc/BICTrainer.h b/bob/learn/misc/include/bob.learn.misc/BICTrainer.h
deleted file mode 100644
index 3f8dabf3701a8d0e9f5b3bbb69af140ba7fb3497..0000000000000000000000000000000000000000
--- a/bob/learn/misc/include/bob.learn.misc/BICTrainer.h
+++ /dev/null
@@ -1,41 +0,0 @@
-/**
- * @date Wed Jun 6 10:29:09 CEST 2012
- * @author Manuel Guenther <Manuel.Guenther@idiap.ch>
- *
- * Copyright (C) Idiap Research Institute, Martigny, Switzerland
- */
-
-#ifndef BOB_LEARN_MISC_BICTRAINER_H
-#define BOB_LEARN_MISC_BICTRAINER_H
-
-#include <bob.learn.misc/BICMachine.h>
-
-namespace bob { namespace learn { namespace misc {
-
- class BICTrainer {
- public:
- //! initializes a BICTrainer to train IEC (without subspace estimation)
- BICTrainer() : m_M_I(0), m_M_E(0) {}
- //! initializes a BICTrainer to train BIC (including subspace truncation)
- BICTrainer(int intra_dim, int extra_dim) : m_M_I(intra_dim), m_M_E(extra_dim) {}
-
- //! trains the intrapersonal and extrapersonal classes of the given BICMachine
- void train(bob::learn::misc::BICMachine& machine, const blitz::Array<double,2>& intra_differences, const blitz::Array<double,2>& extra_differences) const {
- train_single(false, machine, intra_differences);
- train_single(true, machine, extra_differences);
- }
-
- //! trains the intrapersonal or the extrapersonal class of the given BICMachine
- void train_single(bool clazz, bob::learn::misc::BICMachine& machine, const blitz::Array<double,2>& differences) const;
-
- private:
-
- //! dimensions of the intrapersonal and extrapersonal subspace;
- //! zero if training IEC.
- int m_M_I, m_M_E;
- };
-
-} } } // namespaces
-
-
-#endif // BOB_LEARN_MISC_BICTRAINER_H
diff --git a/bob/learn/misc/old/bic.cc b/bob/learn/misc/old/bic.cc
deleted file mode 100644
index 52a1e991c1e36ce66776028e91c602e8ffebd54c..0000000000000000000000000000000000000000
--- a/bob/learn/misc/old/bic.cc
+++ /dev/null
@@ -1,139 +0,0 @@
-/**
- * @author Manuel Guenther <Manuel.Guenther@idiap.ch>
- * @date Wed Jun 6 10:29:09 CEST 2012
- *
- * Copyright (C) 2011-2014 Idiap Research Institute, Martigny, Switzerland
- */
-
-#include <bob.blitz/capi.h>
-#include <bob.blitz/cleanup.h>
-#include <bob.io.base/api.h>
-
-#include "ndarray.h"
-#include <bob.learn.misc/BICMachine.h>
-
-static double bic_call_(const bob::learn::misc::BICMachine& machine, bob::python::const_ndarray input){
- double o;
- machine.forward_(input.bz<double,1>(), o);
- return o;
-}
-
-static double bic_call(const bob::learn::misc::BICMachine& machine, bob::python::const_ndarray input){
- double o;
- machine.forward(input.bz<double,1>(), o);
- return o;
-}
-
-static void bic_load(bob::learn::misc::BICMachine& machine, boost::python::object file){
- if (!PyBobIoHDF5File_Check(file.ptr())) PYTHON_ERROR(TypeError, "Would have expected a bob.io.base.HDF5File");
- PyBobIoHDF5FileObject* hdf5 = (PyBobIoHDF5FileObject*) file.ptr();
- machine.load(*hdf5->f);
-}
-
-static void bic_save(const bob::learn::misc::BICMachine& machine, boost::python::object file){
- if (!PyBobIoHDF5File_Check(file.ptr())) PYTHON_ERROR(TypeError, "Would have expected a bob.io.base.HDF5File");
- PyBobIoHDF5FileObject* hdf5 = (PyBobIoHDF5FileObject*) file.ptr();
- machine.save(*hdf5->f);
-}
-
-
-void bind_machine_bic(){
-
- // bind BICMachine
- boost::python::class_<bob::learn::misc::BICMachine, boost::shared_ptr<bob::learn::misc::BICMachine> > (
- "BICMachine",
- "This machine is designed to classify image differences to be either intrapersonal or extrapersonal. "
- "There are two possible implementations of the BIC:\n"
- "\n"
- "* 'The Bayesian Intrapersonal/Extrapersonal Classifier' from Teixeira [1]_. "
- " A full projection of the data is performed. No prior for the classes has to be selected.\n"
- "* 'Face Detection and Recognition using Maximum Likelihood Classifiers on Gabor Graphs' from Guenther and Wuertz [2]_."
- " Only mean and variance of the difference vectors are calculated. There is no subspace truncation and no priors.\n"
- "\n"
- "What kind of machine is used is dependent on the way, this class is trained via the BICTrainer.\n"
- "\n"
- ".. [1] Marcio Luis Teixeira. The Bayesian intrapersonal/extrapersonal classifier. Colorado State University, 2003.\n"
- ".. [2] Manuel Guenther and Rolf P. Wuertz. Face detection and recognition using maximum likelihood classifiers on Gabor graphs. International Journal of Pattern Recognition and Artificial Intelligence, 23(3):433-461, 2009.",
- boost::python::init<bool>(
- (boost::python::arg("self"), boost::python::arg("use_dffs") = false),
- "Initializes an empty BICMachine. The optional boolean parameter specifies whether to use the DFFS in the BIC implementation. \n\n.. warning :: Use this flag with care, the default value 'False' is usually the best choice!"
- )
- )
-
- .def(
- boost::python::init<const bob::learn::misc::BICMachine&>(
- (boost::python::arg("self"), boost::python::arg("other")),
- "Constructs one BICMachine from another one by doing a deep copy."
- )
- )
-
- .def(
- boost::python::self == boost::python::self
- )
-
- .def(
- "is_similar_to",
- &bob::learn::misc::BICMachine::is_similar_to,
- (boost::python::arg("self"), boost::python::arg("other"), boost::python::arg("r_epsilon") = 1e-5, boost::python::arg("a_epsilon") = 1e-8),
- "Compares this BICMachine with the 'other' one to be approximately the same."
- )
-
- .def(
- "load",
- &bic_load,
- (boost::python::arg("self"), boost::python::arg("file")),
- "Loads the configuration parameters from an hdf5 file."
- )
-
- .def(
- "save",
- &bic_save,
- (boost::python::arg("self"), boost::python::arg("file")),
- "Saves the configuration parameters to an hdf5 file."
- )
-
- .def(
- "__call__",
- &bic_call,
- (
- boost::python::arg("self"),
- boost::python::arg("input")
- ),
- "Computes the BIC or IEC score for the given input vector, which results of a comparison of two (facial) images. "
- "The resulting value is returned as a single float value. "
- "The score itself is the log-likelihood score of the given input vector belonging to the intrapersonal class. "
- "No sanity checks of input and output are performed."
- )
-
- .def(
- "forward_",
- &bic_call_,
- (
- boost::python::arg("self"),
- boost::python::arg("input")
- ),
- "Computes the BIC or IEC score for the given input vector, which results of a comparison of two (facial) images. "
- "The score itself is the log-likelihood score of the given input vector belonging to the intrapersonal class. "
- "No sanity checks of input are performed."
- )
-
- .def(
- "forward",
- &bic_call,
- (
- boost::python::arg("self"),
- boost::python::arg("input")
- ),
- "Computes the BIC or IEC score for the given input vector, which results of a comparison of two (facial) images. "
- "The score itself is the log-likelihood score of the given input vector belonging to the intrapersonal class. "
- "Sanity checks of input shape are performed."
- )
-
- .add_property(
- "use_dffs",
- // cast overloaded function with the same name to its type...
- static_cast<bool (bob::learn::misc::BICMachine::*)() const>(&bob::learn::misc::BICMachine::use_DFFS),
- static_cast<void (bob::learn::misc::BICMachine::*)(bool)>(&bob::learn::misc::BICMachine::use_DFFS),
- "Should the Distance From Feature Space (DFFS) measure be added during scoring? \n\n.. warning :: Only set this flag to True if the number of intrapersonal and extrapersonal training pairs is approximately equal. Otherwise, weird thing may happen!"
- );
-}
diff --git a/bob/learn/misc/old/bic_trainer.cc b/bob/learn/misc/old/bic_trainer.cc
deleted file mode 100644
index 7de6156ae7c367d09028375acbfba5e4d0a36ba3..0000000000000000000000000000000000000000
--- a/bob/learn/misc/old/bic_trainer.cc
+++ /dev/null
@@ -1,57 +0,0 @@
-/**
- * @file trainer/python/bic.cc
- * @date Wed Jun 6 10:29:09 CEST 2012
- * @author Manuel Guenther <Manuel.Guenther@idiap.ch>
- *
- * Copyright (C) 2011-2013 Idiap Research Institute, Martigny, Switzerland
- */
-
-#include "ndarray.h"
-#include <bob.learn.misc/BICTrainer.h>
-
-void py_train(const bob::learn::misc::BICTrainer& t,
- bob::learn::misc::BICMachine& m, bob::python::const_ndarray intra_differences,
- bob::python::const_ndarray extra_differences)
-{
- t.train(m, intra_differences.bz<double,2>(),
- extra_differences.bz<double,2>());
-}
-
-
-
-void bind_trainer_bic(){
-
- boost::python::class_<bob::learn::misc::BICTrainer, boost::shared_ptr<bob::learn::misc::BICTrainer> > (
- "BICTrainer",
- "A Trainer for a BICMachine. It trains either a BIC model (including projection matrix and eigenvalues), "
- "or an IEC model (containing mean and variance only). See :py:class:`bob.machine.BICMachine` for more details.",
- boost::python::init<int,int>(
- (
- boost::python::arg("self"),
- boost::python::arg("intra_dim"),
- boost::python::arg("extra_dim")
- ),
- "Initializes the BICTrainer to train a BIC model with the given resulting dimensions of the intraperonal and extrapersonal subspaces."
- )
- )
-
- .def(
- boost::python::init<>(
- (boost::python::arg("self")),
- "Initializes the BICTrainer to train a IEC model."
- )
- )
-
- .def(
- "train",
- &py_train,
- (
- boost::python::arg("self"),
- boost::python::arg("machine"),
- boost::python::arg("intra_differences"),
- boost::python::arg("extra_differences")
- ),
- "Trains the given machine (should be of type :py:class:`bob.machine.BICMachine`) to classify intrapersonal image differences vs. extrapersonal ones. "
- "The given difference vectors might be the result of any image comparison function, e.g., the pixel difference of the images."
- );
-}
diff --git a/bob/learn/misc/old/main.cc b/bob/learn/misc/old/main.cc
index 16f7f9ba565063a449f54451489bb4ba88282e53..f09c85a9925e7dfed70ff397e3e9d06d2eb669e9 100644
--- a/bob/learn/misc/old/main.cc
+++ b/bob/learn/misc/old/main.cc
@@ -25,7 +25,6 @@ void bind_core_bz_numpy();
/** machine bindings **/
void bind_machine_base();
-void bind_machine_bic();
void bind_machine_gaussian();
void bind_machine_gmm();
void bind_machine_kmeans();
@@ -44,7 +43,6 @@ void bind_trainer_ivector();
void bind_trainer_plda();
void bind_trainer_wiener();
void bind_trainer_empca();
-void bind_trainer_bic();
BOOST_PYTHON_MODULE(_old_library) {
@@ -77,7 +75,6 @@ BOOST_PYTHON_MODULE(_old_library) {
/** machine bindings **/
bind_machine_base();
- bind_machine_bic();
bind_machine_gaussian();
bind_machine_gmm();
bind_machine_kmeans();
@@ -96,6 +93,5 @@ BOOST_PYTHON_MODULE(_old_library) {
bind_trainer_plda();
bind_trainer_wiener();
bind_trainer_empca();
- bind_trainer_bic();
}
diff --git a/bob/learn/misc/test_bic.py b/bob/learn/misc/test_bic.py
deleted file mode 100644
index d0cdff3dc98bacd94d5be07604a4158841dc0f85..0000000000000000000000000000000000000000
--- a/bob/learn/misc/test_bic.py
+++ /dev/null
@@ -1,96 +0,0 @@
-#!/usr/bin/env python
-# vim: set fileencoding=utf-8 :
-# Manuel Guenther <Manuel.Guenther@idiap.ch>
-# Thu Jun 14 14:45:06 CEST 2012
-#
-# Copyright (C) 2011-2014 Idiap Research Institute, Martigny, Switzerland
-
-"""Test BIC trainer and machine
-"""
-
-import numpy
-import nose.tools
-from . import BICMachine, BICTrainer
-
-eps = 1e-5
-
-def equals(x, y, epsilon):
- return (abs(x - y) < epsilon).all()
-
-def training_data():
- data = numpy.array([
- (10., 4., 6., 8., 2.),
- (8., 2., 4., 6., 0.),
- (12., 6., 8., 10., 4.),
- (11., 3., 7., 7., 3.),
- (9., 5., 5., 9., 1.)], dtype='float64')
-
- return data, -1. * data
-
-def eval_data(which):
- eval_data = numpy.ndarray((5,), dtype=numpy.float64)
- if which == 0:
- eval_data.fill(0.)
- elif which == 1:
- eval_data.fill(10.)
-
- return eval_data
-
-def test_IEC():
- # Tests the IEC training of the BICTrainer
- intra_data, extra_data = training_data()
-
- # train BIC machine
- machine = BICMachine()
- trainer = BICTrainer()
-
- # train machine with intrapersonal data only
- trainer.train(machine, intra_data, intra_data)
- # => every result should be zero
- assert abs(machine(eval_data(0))) < eps
- assert abs(machine(eval_data(1))) < eps
-
- # re-train the machine with intra- and extrapersonal data
- trainer.train(machine, intra_data, extra_data)
- # now, only the input vector 0 should give log-likelihood 0
- assert abs(machine(eval_data(0))) < eps
- # while a positive vector should give a positive result
- assert machine(eval_data(1)) > 0.
-
-@nose.tools.raises(RuntimeError)
-def test_raises():
-
- # Tests the BIC training of the BICTrainer
- intra_data, extra_data = training_data()
-
- # train BIC machine
- trainer = BICTrainer(2,2)
-
- # The data are chosen such that the third eigenvalue is zero.
- # Hence, calculating rho (i.e., using the Distance From Feature Space) is impossible
- machine = BICMachine(True)
- trainer.train(machine, intra_data, intra_data)
-
-def test_BIC():
- # Tests the BIC training of the BICTrainer
- intra_data, extra_data = training_data()
-
- # train BIC machine
- trainer = BICTrainer(2,2)
-
- # So, now without rho...
- machine = BICMachine(False)
-
- # First, train the machine with intrapersonal data only
- trainer.train(machine, intra_data, intra_data)
-
- # => every result should be zero
- assert abs(machine(eval_data(0))) < eps
- assert abs(machine(eval_data(1))) < eps
-
- # re-train the machine with intra- and extrapersonal data
- trainer.train(machine, intra_data, extra_data)
- # now, only the input vector 0 should give log-likelihood 0
- assert abs(machine(eval_data(0))) < eps
- # while a positive vector should give a positive result
- assert machine(eval_data(1)) > 0.
diff --git a/setup.py b/setup.py
index e58f32365c6ff1865ec26df02e028c641652d6d8..d3426aad12b22368b7a22159726f51294cd3da38 100644
--- a/setup.py
+++ b/setup.py
@@ -54,7 +54,6 @@ setup(
Library("bob.learn.misc.bob_learn_misc",
[
- "bob/learn/misc/cpp/BICMachine.cpp",
"bob/learn/misc/cpp/Gaussian.cpp",
"bob/learn/misc/cpp/GMMMachine.cpp",
"bob/learn/misc/cpp/GMMStats.cpp",
@@ -66,7 +65,6 @@ setup(
"bob/learn/misc/cpp/WienerMachine.cpp",
"bob/learn/misc/cpp/ZTNorm.cpp",
- "bob/learn/misc/cpp/BICTrainer.cpp",
"bob/learn/misc/cpp/EMPCATrainer.cpp",
"bob/learn/misc/cpp/GMMTrainer.cpp",
"bob/learn/misc/cpp/IVectorTrainer.cpp",
@@ -104,8 +102,6 @@ setup(
Extension("bob.learn.misc._old_library",
[
- "bob/learn/misc/old/bic.cc",
- "bob/learn/misc/old/bic_trainer.cc",
"bob/learn/misc/old/empca_trainer.cc",
"bob/learn/misc/old/gaussian.cc",
"bob/learn/misc/old/gmm.cc",