From 04eeae4f69e8ee62e224d1f077d9c70b884e138d Mon Sep 17 00:00:00 2001
From: Tiago Freitas Pereira <tiagofrepereira@gmail.com>
Date: Thu, 3 May 2018 11:10:58 +0200
Subject: [PATCH] Archiving csu issue #29
Removed unused references
---
bob/bio/face/script/baselines.py | 8 --------
doc/baselines.rst | 19 -------------------
doc/extra-intersphinx.txt | 1 -
doc/index.rst | 1 -
doc/links.rst | 2 --
doc/references.rst | 2 --
6 files changed, 33 deletions(-)
diff --git a/bob/bio/face/script/baselines.py b/bob/bio/face/script/baselines.py
index 0b721913..b6f2a471 100755
--- a/bob/bio/face/script/baselines.py
+++ b/bob/bio/face/script/baselines.py
@@ -35,14 +35,6 @@ try:
except:
print("Could not load the GMM-based algorithms. Did you specify bob.bio.gmm in your config file?")
-try:
- # try if the CSU extension is enabled
- bob.bio.base.load_resource('lrpca', 'algorithm')
- bob.bio.base.load_resource('lda-ir', 'algorithm')
- all_algorithms += ['lrpca', 'lda-ir']
-except:
- print("Could not load the algorithms from the CSU resources. Did you specify bob.bio.csu in your config file?")
-
def command_line_arguments(command_line_parameters):
"""Defines the command line parameters that are accepted."""
diff --git a/doc/baselines.rst b/doc/baselines.rst
index 3f60912f..6df5fdbe 100644
--- a/doc/baselines.rst
+++ b/doc/baselines.rst
@@ -125,25 +125,6 @@ Further algorithms are available, when the :ref:`bob.bio.gmm <bob.bio.gmm>` pack
.. note::
The ``ivector`` algorithm needs a lot of training data and fails on small databases such as the `AT&T database`_.
-
-Additionally, the following algorithms can be executed, when the :ref:`bob.bio.csu <bob.bio.csu>` package is installed.
-
-* ``lrpca``: In Local Region PCA [PBD11]_, the face is sub-divided into local regions and a PCA is performed for each local region.
-
- - preprocessor : :py:class:`bob.bio.csu.preprocessor.LRPCA`
- - feature : :py:class:`bob.bio.csu.extractor.LRPCA`
- - algorithm : :py:class:`bob.bio.csu.algorithm.LRPCA`
-
-* ``lda-ir``: The LDA-IR (a.k.a. CohortLDA [LBP12]_) extracts color information from images after, and computes a PCA+LDA projection on two color layers.
-
- - preprocessor : :py:class:`bob.bio.csu.preprocessor.LDAIR`
- - feature : :py:class:`bob.bio.csu.extractor.LDAIR`
- - algorithm : :py:class:`bob.bio.csu.algorithm.LDAIR`
-
-.. note::
- The ``lrpca`` and ``lda-ir`` algorithms require hand-labeled eye locations.
- Therefore, they can not be run on the default ``atnt`` database.
-
.. _bob.bio.base.baseline_results:
Baseline Results
diff --git a/doc/extra-intersphinx.txt b/doc/extra-intersphinx.txt
index c82f95f8..bf1097eb 100644
--- a/doc/extra-intersphinx.txt
+++ b/doc/extra-intersphinx.txt
@@ -6,7 +6,6 @@ bob.ip.gabor
bob.ip.base
bob.bio.gmm
bob.bio.video
-bob.bio.csu
bob.bio.spear
bob.db.lfw
bob.ip.facedetect
diff --git a/doc/index.rst b/doc/index.rst
index 361114f3..7a6cb686 100644
--- a/doc/index.rst
+++ b/doc/index.rst
@@ -21,7 +21,6 @@ Additionally, a set of baseline algorithms are defined, which integrate well wit
* :ref:`bob.bio.gmm <bob.bio.gmm>` defines algorithms based on Gaussian mixture models
* :ref:`bob.bio.video <bob.bio.video>` uses face recognition algorithms in video frames
-* :ref:`bob.bio.csu <bob.bio.csu>` provides wrapper classes of the `CSU Face Recognition Resources <http://www.cs.colostate.edu/facerec>`_ (only Python 2.7 compatible)
For more detailed information about the structure of the ``bob.bio`` packages, please refer to the documentation of :ref:`bob.bio.base <bob.bio.base>`.
Particularly, the installation of this and other ``bob.bio`` packages, please read the :ref:`bob.bio.base.installation`.
diff --git a/doc/links.rst b/doc/links.rst
index b055ac96..f4b19432 100644
--- a/doc/links.rst
+++ b/doc/links.rst
@@ -14,7 +14,5 @@
.. _nist: http://www.nist.gov/itl/iad/ig/focs.cfm
.. _pypi: http://pypi.python.org
.. _sge: http://wiki.idiap.ch/linux/SunGridEngine
-.. _csu face recognition resources: http://www.cs.colostate.edu/facerec
-.. _xfacereclib.extension.csu: http://pypi.python.org/pypi/xfacereclib.extension.CSU
.. _virtualbox: https://www.virtualbox.org
.. _hdf5: http://www.hdfgroup.org/HDF5
diff --git a/doc/references.rst b/doc/references.rst
index c1cfb2c8..22fb8ffc 100644
--- a/doc/references.rst
+++ b/doc/references.rst
@@ -9,8 +9,6 @@ References
.. [TP91] *M. Turk and A. Pentland*. **Eigenfaces for recognition**. Journal of Cognitive Neuroscience, 3(1):71-86, 1991.
.. [ZKC98] *W. Zhao, A. Krishnaswamy, R. Chellappa, D. Swets and J. Weng*. **Discriminant analysis of principal components for face recognition**, pages 73-85. Springer Verlag Berlin, 1998.
.. [MWP98] *B. Moghaddam, W. Wahid and A. Pentland*. **Beyond eigenfaces: probabilistic matching for face recognition**. IEEE International Conference on Automatic Face and Gesture Recognition, pages 30-35. 1998.
-.. [PBD11] *P.J. Phillips, J.R. Beveridge, B.A. Draper, G. Givens, A.J. O'Toole, D.S. Bolme, J. Dunlop, Y.M. Lui, H. Sahibzada and S. Weimer*. **An introduction to the good, the bad, & the ugly face recognition challenge problem**. Automatic face gesture recognition and workshops (FG 2011), pages 346-353. 2011.
-.. [LBP12] *Y.M. Lui, D. Bolme, P.J. Phillips, J.R. Beveridge and B.A. Draper*. **Preliminary studies on the good, the bad, and the ugly face recognition challenge problem**. Computer vision and pattern recognition workshops (CVPRW), pages 9-16. 2012.
.. [GHW12] *M. Günther, D. Haufe and R.P. Würtz*. **Face recognition with disparity corrected Gabor phase differences**. In Artificial neural networks and machine learning, volume 7552 of Lecture Notes in Computer Science, pages 411-418. 9/2012.
.. [ZSG05] *W. Zhang, S. Shan, W. Gao, X. Chen and H. Zhang*. **Local Gabor binary pattern histogram sequence (LGBPHS): a novel non-statistical model for face representation and recognition**. Computer Vision, IEEE International Conference on, 1:786-791, 2005.
.. [MM09] *C. McCool, S. Marcel*. **Parts-based face verification using local frequency bands**. In Advances in biometrics, volume 5558 of Lecture Notes in Computer Science. 2009.
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