Commit e1762da8 authored by Amir MOHAMMADI's avatar Amir MOHAMMADI
Browse files

Merge branch 'pkglist' into 'master'

Improve docs and package list

See merge request !227
parents 2e5952d7 f64a3f8d
Pipeline #9246 passed with stages
in 12 minutes and 47 seconds
name: bob-devel-py27
channels:
- http://www.idiap.ch/software/bob/conda
- defaults
dependencies:
- python=2.7
- cython
- dask
- hdf5
- jpeg
- libpng
- libtiff
- matplotlib
- nose
- numexpr
- numpy
- pillow
- pip
- psutil
- scikit-image
- scikit-learn
- scipy
- sphinx
- sqlalchemy
- anaconda=4.2.0 # [linux]
- anaconda=4.3.0 # [osx]
- boost=1.61
- caffe # [linux]
- cmake
- coverage
- cyvlfeat=0.4.5
- docopt
- ffmpeg=2.8.10
- gcc=4.8.5 # [linux]
- libgcc=4.8.5 # [linux]
- giflib=5.1.4
- ipdb=0.10.2
- ipython
- libblitz=0.10
- libmatio=1.5
- libsvm=3.21
- menpo=0.7.7
- menpofit=0.4.1
- menpowidgets=0.2.1p3
- mne=0.13.1
- openblas=0.2.19
- opencv=3
- pkgtools=0.7.3
- pkg-config
- pyedflib=0.1.6
- schema=0.6.5
- sox=14.4.2
- sphinx_rtd_theme
- toolchain=2.3.2
- vlfeat=0.9.20
- zc.buildout=2.9.2
- pip:
- tensorflow==1.0.1
name: bob-devel-py34
channels:
- http://www.idiap.ch/software/bob/conda
- defaults
dependencies:
- python=3.4
- cython
- dask
- hdf5
- jpeg
- libpng
- libtiff
- matplotlib
- nose
- numexpr
- numpy
- pillow
- pip
- psutil
- scikit-image
- scikit-learn
- scipy
- sphinx
- sqlalchemy
- anaconda=4.2.0 # [linux]
- anaconda=4.3.0 # [osx]
- boost=1.61
- caffe # [linux]
- cmake
- coverage
- cyvlfeat=0.4.5
- docopt
- ffmpeg=2.8.10
- gcc=4.8.5 # [linux]
- libgcc=4.8.5 # [linux]
- giflib=5.1.4
- ipdb=0.10.2
- ipython
- libblitz=0.10
- libmatio=1.5
- libsvm=3.21
- menpo=0.7.7
- menpofit=0.4.1
- menpowidgets=0.2.1p3
- mne=0.13.1
- openblas=0.2.19
- opencv=3
- pkgtools=0.7.3
- pkg-config
- pyedflib=0.1.6
- schema=0.6.5
- sox=14.4.2
- sphinx_rtd_theme
- toolchain=2.3.2
- vlfeat=0.9.20
- zc.buildout=2.9.2
- pip:
- tensorflow==1.0.1
name: bob-devel-py35
channels:
- http://www.idiap.ch/software/bob/conda
- defaults
dependencies:
- python=3.5
- cython
- dask
- hdf5
- jpeg
- libpng
- libtiff
- matplotlib
- nose
- numexpr
- numpy
- pillow
- pip
- psutil
- scikit-image
- scikit-learn
- scipy
- sphinx
- sqlalchemy
- anaconda=4.2.0 # [linux]
- anaconda=4.3.0 # [osx]
- boost=1.61
- caffe # [linux]
- cmake
- coverage
- cyvlfeat=0.4.5
- docopt
- ffmpeg=2.8.10
- gcc=4.8.5 # [linux]
- libgcc=4.8.5 # [linux]
- giflib=5.1.4
- ipdb=0.10.2
- ipython
- libblitz=0.10
- libmatio=1.5
- libsvm=3.21
- menpo=0.7.7
- menpofit=0.4.1
- menpowidgets=0.2.1p3
- mne=0.13.1
- openblas=0.2.19
- opencv=3
- pkgtools=0.7.3
- pkg-config
- pyedflib=0.1.6
- schema=0.6.5
- sox=14.4.2
- sphinx_rtd_theme
- toolchain=2.3.2
- vlfeat=0.9.20
- zc.buildout=2.9.2
- pip:
- tensorflow==1.0.1
bob-devel-py27.yml
\ No newline at end of file
.. vim: set fileencoding=utf-8 :
.. Andre Anjos <andre.anjos@idiap.ch>
.. Fri 23 Mar 2012 11:41:00 CET
..
.. Copyright (C) 2011-2013 Idiap Research Institute, Martigny, Switzerland
.. _bob.iris_example:
......
......@@ -2,5 +2,6 @@ bob.bio.base
bob.bio.face
bob.bio.video
bob.bio.spear
bob.bio.gmm
matplotlib
scipy
.. vim: set fileencoding=utf-8 :
.. Andre Anjos <andre.anjos@idiap.ch>
.. Mon 17 Feb 2014 17:40:07 CET
.. Copyright (C) 2011-2017 Idiap Research Institute, Martigny, Switzerland
=======================
Bob
=======================
Bob is a free signal-processing and machine learning toolbox originally
Bob_ is a free signal-processing and machine learning toolbox originally
developed by the Biometrics group at `Idiap`_ Research Institute, Switzerland.
The toolbox is written in a mix of `Python`_ and `C++`_ and is designed to be
both efficient and reduce development time. It is composed of a reasonably
large number of `packages`_ that implement tools for image, audio & video
processing, machine learning and pattern recognition.
processing, machine learning & pattern recognition, and a lot more task
specific packages.
.. todolist::
......@@ -25,6 +23,7 @@ processing, machine learning and pattern recognition.
example
list
source
Bob's Wiki <https://www.idiap.ch/software/bob/wiki>
.. include:: links.rst
......@@ -34,7 +34,7 @@ Now you can create an envrionment and install |project| in that environment:
Be aware that if you use packages from our channel and other user/community
channels (especially ``conda-forge``) in one environment, you may end up
with a broken envrionment. We can only guarantee that the packages in our
channel is compatible with the ``defaults`` channel.
channel are compatible with the ``defaults`` channel.
You can install other |project| `packages`_ by reading the instructions on
their webpage. In most cases, the installation should be as simple as:
......
.. _anaconda: https://www.continuum.io/anaconda
.. _Artistic-2.0: http://www.opensource.org/licenses/Artistic-2.0
.. _Blitz++: http://www.oonumerics.org/blitz
.. _Bob: https://www.idiap.ch/software/bob
.. _Boost: http://www.boost.org
.. _BSD-2-Clause: http://www.opensource.org/licenses/BSD-2-Clause
.. _BSD-3-Clause: http://www.opensource.org/licenses/BSD-3-Clause
......@@ -47,3 +48,4 @@
.. _SQLAlchemy: http://www.sqlalchemy.org/
.. _SQLite: http://www.sqlite.org
.. _VLFeat: http://www.vlfeat.org/
.. _Wiki: https://www.idiap.ch/software/bob/wiki
......@@ -2,11 +2,17 @@
List of Bob packages
======================
Bob is organized in several independent python packages. Below you can find the
list of all **core** packages organized by category with their respective
documentation. For a comprehensive list of packages that are either part of
|project| or use |project|, please visit `packages`_.
Bob is organized in several independent python packages. The list of packages
are divided into two lists: **core** and **extra**.
* You can
`search PyPI <https://pypi.python.org/pypi?:action=browse&show=all&c=590>`_
for a comprehensive list of packages that **either use Bob or are part of
Bob**.
* Also, we maintain a list of active **core** and **extra** `packages`_.
Below you can find the list of all **core** packages organized by category with
their respective documentation.
Basic Functionality
-------------------
......@@ -63,4 +69,16 @@ Modules for Developers
* :ref:`bob.extension`
* :ref:`bob.blitz`
The list does not stop here, please visit `packages`_ for more. Below you can
find some notable **extra** packages:
Biometric Recognition
---------------------
* :ref:`bob.bio.base`
* :ref:`bob.bio.face`
* :ref:`bob.bio.spear`
* :ref:`bob.bio.video`
* :ref:`bob.bio.gmm`
.. include:: links.rst
......@@ -32,22 +32,15 @@ and so when using Python we have relied on the existing `NumPy`_ multi-
dimensional arrays :any:`numpy.ndarray`. This provides with greater flexibility
within the Python environment.
At the C++ level, the `Blitz++`_ library is used to handle arrays. Although we
initially bound Blitz++ Arrays in Python, we quickly realized that it might be
more clever to use the existing NumPy ndarrays from Python, as they can
directly be processed by numerous existing Python libraries such as `NumPy`_
and `SciPy`_.
This means that |project|'s multi-dimensional arrays are represented in Python
by NumPy ndarrays. This also implies that there are internal conversion
routines to convert NumPy ndarrays from/to Blitz++. As they are done
implicitly, the user has no need to care about this aspect and should just use
NumPy ndarrays everywhere.
At the C++ level, the `Blitz++`_ library is used to handle arrays. |project|
provides internal conversion routines to transparently and efficiently convert
NumPy ndarrays to/from Blitz++. As they are done implicitly, the user has no
need to care about this aspect and should just use NumPy ndarrays everywhere
while inside Python code.
For an introduction and tutorials about NumPy ndarrays, just visit the `NumPy
Reference`_ website. For a short tutorial on the bindings from NumPy ndarrays
to Blitz++, you can read the documentation of our
:ref:`bob.blitz` package.
to Blitz++, you can read the documentation of our :ref:`bob.blitz` package.
.. note::
......@@ -231,25 +224,23 @@ Here, we examine a few of the machines and trainers available in Bob.
Database interfaces
===================
Bob provides an API to easily query and interface with well known
databases. A database contains information about the organization of the
files, functions to query information such as the data which might be
used for training a model, but it usually does **not** contain the data
itself (except for some toy examples). Most of the databases are stored
in an `SQLite`_ file, whereas the smallest ones can be stored as
filelists.
Bob provides an API to easily query and interface with well known databases. A
database contains information about the organization of the files, functions to
query information such as the data which might be used for training a model,
but it usually does **not** contain the data itself (except for some toy
examples). Please visit :ref:`bob.db.base` for an excellent guide on Bob's
datbases.
Bob includes a (growing) list of supported database interfaces. There are some
small toy databases like :ref:`bob.db.iris` and the
:ref:`bob.db.mnist` database can be used to train and evaluate
classification experiments. For the former, a detailed example on how to use
Bob's machine learning techniques to classify the Iris flowers is given in
:doc:`example`.
small toy databases like :ref:`bob.db.iris` and the :ref:`bob.db.mnist`
database can be used to train and evaluate classification experiments. For the
former, a detailed example on how to use Bob's machine learning techniques to
classify the Iris flowers is given in :doc:`example`.
However, most of the databases contain face images, speech data or videos that
are used for biometric recognition and presentation attack detection
(anti-spoofing). A complete (and growing) list of database packages can be found in
our `Packages`_.
(anti-spoofing). A complete (and growing) list of database packages can be
found in our `Packages`_.
Several databases that can be used for biometric recognition share a common
interface, which is defined in the :any:`bob.bio.base.database.BioDatabase`
......
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