CAS-PEAL Database

This is the Bob database entry for the CAS-PEAL database.

bob.db.caspeal.get_config()

Returns a string containing the configuration information.

class bob.db.caspeal.Annotation(file_id, eyes)

Bases: sqlalchemy.ext.declarative.api.Base

Annotations of the CAS-PEAL database consists only of the left and right eye positions. There is exactly one annotation for each file.

file_id

id

le_x

le_y

metadata = MetaData(bind=None)

re_x

re_y

class bob.db.caspeal.Client(client_type, client_id)

Bases: sqlalchemy.ext.declarative.api.Base

Information about the clients (identities) of the CAS-PEAL database

Creates a client name by parsing the given first two part of the filename

age

age_choices = ('Y', 'M', 'O')

gender

gender_choices = ('F', 'M')

id

metadata = MetaData(bind=None)

class bob.db.caspeal.Database(original_directory=None, original_extension='.tif')

Bases: bob.db.verification.utils.database.SQLiteDatabase

The database class opens and maintains a connection opened to the Database.

It provides many different ways to probe for the characteristics of the data and for the data itself inside the database.

all_files(**kwargs)

Returns the list of all File objects that satisfy your query. For possible keyword arguments, please check the objects() function.

annotations(file)

Returns the annotations for the given file id as a dictionary {‘reye’:(y,x), ‘leye’:(y,x)}.

assert_validity()

Raise a RuntimeError if the database back-end is not available.

check_parameter_for_validity(parameter, parameter_description, valid_parameters, default_parameter=None)

Checks the given parameter for validity, i.e., if it is contained in the set of valid parameters. If the parameter is ‘None’ or empty, the default_parameter will be returned, in case it is specified, otherwise a ValueError will be raised.

This function will return the parameter after the check tuple or list of parameters, or raise a ValueError.

Keyword parameters:

parameter : str

The single parameter to be checked. Might be a string or None.

parameter_description : str

A short description of the parameter. This will be used to raise an exception in case the parameter is not valid.

valid_parameters : [str]

A list/tuple of valid values for the parameters.

default_parameters : [str] or None

The default parameter that will be returned in case parameter is None or empty. If omitted and parameter is empty, a ValueError is raised.

check_parameters_for_validity(parameters, parameter_description, valid_parameters, default_parameters=None)

Checks the given parameters for validity, i.e., if they are contained in the set of valid parameters. It also assures that the parameters form a tuple or a list. If parameters is ‘None’ or empty, the default_parameters will be returned (if default_parameters is omitted, all valid_parameters are returned).

This function will return a tuple or list of parameters, or raise a ValueError.

Keyword parameters:

parameters : str, [str] or None

The parameters to be checked. Might be a string, a list/tuple of strings, or None.

parameter_description : str

A short description of the parameter. This will be used to raise an exception in case the parameter is not valid.

valid_parameters : [str]

A list/tuple of valid values for the parameters.

default_parameters : [str] or None

The list/tuple of default parameters that will be returned in case parameters is None or empty. If omitted, all valid_parameters are used.

client_ids(groups=None, genders=None, ages=None, protocol=None)

Returns a list of client ids for the specific query by the user.

Keyword Parameters:

groups

One or several groups to which the models belong (‘world’, ‘dev’, ‘eval’). If not specified, all groups are returned.

genders

One of the genders (‘m’, ‘w’) of the clients. If not specified, clients of all genders are returned.

ages

One or several of the age ranges (‘Y’, ‘M’, ‘O’) of the clients. If not specified, clients of all age ranges are returned.

protocol

Ignored since clients are identical for all protocols.

Returns: A list containing all the client ids which have the desired properties.

clients(groups=None, genders=None, ages=None, protocol=None)

Returns a list of Client objects for the specific query by the user.

Keyword Parameters:

groups

One or several groups to which the models belong (‘world’, ‘dev’). If not specified, all groups are returned.

genders

One or several of the genders (‘F’, ‘M’) of the clients. If not specified, clients of all genders are returned.

ages

One or several of the age ranges (‘Y’, ‘M’, ‘O’) of the clients. If not specified, clients of all age ranges are returned.

protocol

Ignored since clients are identical for all protocols.

Returns: A list containing all the Client objects which have the desired properties.

enroll_files(protocol=None, model_id=None, groups='dev', **kwargs)

Returns the list of enrollment File objects from the given model id of the given protocol for the given groups that satisfy your query. If the model_id is None (the default), enrollment files for all models are returned. For possible keyword arguments, please check the objects() function.

file_names(files, directory, extension)

This function returns the list of original file names for the given list of File objects.

Keyword parameters:

files : [File]

The list of File objects for which the file names should be retrieved

directory : str

The base directory where the files are stored

extension : str

The file name extension of the files

Return value : [str]

The file names for the given File objects, in the same order.

files(ids, preserve_order=True)

Returns a list of File objects with the given file ids

Keyword Parameters:

ids : [various type]

The ids of the object in the database table “file”. This object should be a python iterable (such as a tuple or list).

preserve_order : bool

If True (the default) the order of elements is preserved, but the execution time increases.

Returns a list (that may be empty) of File objects.

get_client_id_from_file_id(file_id, **kwargs)

Returns the client_id attached to the given file_id

Keyword Parameters:

file_id

The file_id to consider

Returns: The client_id attached to the given file_id

get_client_id_from_model_id(model_id)

Returns the client_id attached to the given model_id

Keyword Parameters:

model_id

The model id to consider

Returns: The client_id attached to the given model_id

groups(protocol=None)

Returns a list of groups for the given protocol

Keyword Parameters:

protocol

Ignored since groups are identical for all protocols.

Returns: a list of groups

has_protocol(name)

Tells if a certain protocol is available

is_valid()

Returns if a valid session has been opened for reading the database.

model_ids(groups=None, genders=None, ages=None, protocol=None)

Returns a list of client ids for the specific query by the user.

Keyword Parameters:

groups

One or several groups to which the models belong (‘world’, ‘dev’, ‘eval’). If not specified, all groups are returned.

genders

One of the genders (‘m’, ‘w’) of the clients. If not specified, clients of all genders are returned.

ages

One or several of the age ranges (‘Y’, ‘M’, ‘O’) of the clients. If not specified, clients of all age ranges are returned.

protocol

Ignored since clients are identical for all protocols.

Returns: A list containing all the client ids which have the desired properties.

objects(groups=None, protocol=None, purposes=None, model_ids=None, genders=None, ages=None, lightings=None, poses=None, expressions=None, accessories=None, distances=None, sessions=None, backgrounds=None)

Using the specified restrictions, this function returns a list of File objects.

Note that in rare cases, File objects with the same path, but different ID’s might be returned. This is due to the fact that some images are in both the training list and in one of the gallery or probe lists.

Note further that the training set consists only of files with frontal pose (‘M+00’).

Keyword Parameters:

groups

One or several groups to which the models belong (‘world’, ‘dev’).

protocol

One of the CAS-PEAL protocols (‘accessory’, ‘aging’, ‘background’, ‘distance’, ‘expression’, ‘lighting’, ‘pose’). Note: this field is ignored for group ‘world’. Note: this field is ignored for purpose ‘enroll’.

purposes

One or several purposes for which files should be retrieved (‘enroll’, ‘probe’). Note: this field is ignored for group ‘world’.

model_ids

If given (as a list of model id’s or a single one), only the files belonging to the specified model id is returned. For ‘probe’ purposes, this field is ignored since probe files are identical for all models.

genders

One or several of the genders (‘F’, ‘M’) of the clients. If not specified, objects of all genders are returned.

ages

One or several of the age ranges (‘Y’, ‘M’, ‘O’) of the clients. If not specified, objects of all age ranges are returned.

lightings

One or several of the possible lightings (e.g. ‘EU+00’ or ‘FM-45’). If not specified, objects of all lightings will be returned. Note: this field is ignored for purpose ‘enroll’.

poses

One or several of the possible poses (e.g. ‘M+00’, ‘U-67’). If not specified, objects of all poses are returned. Note: this field is ignored for purpose ‘enroll’. Note: for group ‘world’, only pose ‘M+00’ is available.

expressions

One or several expressions from (‘N’, ‘L’, ‘F’, ‘S’, ‘C’, ‘O’). If not specified, objects of all expressions are returned. Note: this field is ignored for purpose ‘enroll’.

accessories

One or several accessories from (0, 1, 2, 3, 4, 5, 6). If not specified, objects of all accessories are returned. Note: this field is ignored for purpose ‘enroll’.

distances

One or several distances from (0, 1, 2). If not specified, objects of all distances are returned. Note: this field is ignored for purpose ‘enroll’.

sessions

One or several sessions from (0, 1, 2). If not specified, objects of all sessions are returned. Note: this field is ignored for purpose ‘enroll’.

backgrounds

One or several backgrounds from (‘B’, ‘R’, ‘D’, ‘Y’, ‘W’). If not specified, objects of all backgrounds are returned. Note: this field is ignored for purpose ‘enroll’.

original_file_name(file, check_existence=True)

This function returns the original file name for the given File object.

Keyword parameters:

file : File or a derivative

The File objects for which the file name should be retrieved

check_existence : bool

Check if the original file exists?

Return value : str

The original file name for the given File object

original_file_names(files, check_existence=True)

This function returns the list of original file names for the given list of File objects.

Keyword parameters:

files : [File]

The list of File objects for which the file names should be retrieved

check_existence : bool

Check if the original files exists?

Return value : [str]

The original file names for the given File objects, in the same order.

paths(ids, prefix=None, suffix=None, preserve_order=True)

Returns a full file paths considering particular file ids, a given directory and an extension

Keyword Parameters:

ids : [various type]

The ids of the object in the database table “file”. This object should be a python iterable (such as a tuple or list).

prefix : str or None

The bit of path to be prepended to the filename stem

suffix : str or None

The extension determines the suffix that will be appended to the filename stem.

preserve_order : bool

If True (the default) the order of elements is preserved, but the execution time increases.

Returns a list (that may be empty) of the fully constructed paths given the file ids.

probe_files(protocol=None, model_id=None, groups='dev', **kwargs)

Returns the list of probe File objects to probe the model with the given model id of the given protocol for the given groups that satisfy your query. If the model_id is None (the default), all possible probe files are returned. For possible keyword arguments, please check the objects() function.

protocol_names()

Returns all registered protocol names

protocols()

Returns all registered protocols

provides_file_set_for_protocol(protocol=None)

Returns True if the given protocol specifies file sets for probes, instead of a single probe file. In this default implementation, False is returned, throughout. If you need different behavior, please overload this function in your derived class.

query(*args)

Creates a query to the database using the given arguments.

reverse(paths, preserve_order=True)

Reverses the lookup: from certain paths, return a list of File objects

Keyword Parameters:

paths : [str]

The filename stems to query for. This object should be a python iterable (such as a tuple or list)

preserve_order : True

If True (the default) the order of elements is preserved, but the execution time increases.

Returns a list (that may be empty).

test_files(protocol=None, groups='dev', **kwargs)

Returns the list of all test File objects of the given groups that satisfy your query. Test objects are all File objects that serve either for enrollment or probing. For possible keyword arguments, please check the objects() function.

training_files(protocol=None, **kwargs)

Returns the list of all training (world) File objects that satisfy your query. For possible keyword arguments, please check the objects() function.

uniquify(file_list)

Sorts the given list of File objects and removes duplicates from it.

Keyword parameters:

file_list : [File]

A list of File objects to be handled. Also other objects can be handled, as long as they are sortable.

Returns

A sorted copy of the given file_list with the duplicates removed.

class bob.db.caspeal.File(image_path, protocol)

Bases: sqlalchemy.ext.declarative.api.Base, bob.db.verification.utils.file.File

Information about the files of the CAS-PEAL face database. Each file includes

• the session
• the expression
• the pose
• the lighting
• the camera distance
• the accessory
• the background
• a privacy field describing whether the image file might be published in papers
• the client id
• the path

a = '+90'

accessory

accessory_choices = [0, 1, 2, 3, 4, 5, 6]

accessory_type()

annotation

background

background_choices = ('B', 'R', 'D', 'Y', 'W')

background_type()

client

client_id

distance

distance_choices = [0, 1, 2]

e = 'D'

elevation_choices = ('U', 'M', 'D')

expression

expression_choices = ('N', 'L', 'F', 'S', 'C', 'O')

expression_type()

id

itertools = <module 'itertools' from '/home/travis/virtualenv/python3.12.2/lib/python2.7/lib-dynload/itertools.so'>

lighting

lighting_azimuth()

lighting_azimuth_choices = ('-90', '-45', '+00', '+45', '+90')

lighting_choices = ['EU-90', 'EU-45', 'EU+00', 'EU+45', 'EU+90', 'EM-90', 'EM-45', 'EM+00', 'EM+45', 'EM+90', 'ED-90', 'ED-45', 'ED+00', 'ED+45', 'ED+90', 'FU-90', 'FU-45', 'FU+00', 'FU+45', 'FU+90', 'FM-90', 'FM-45', 'FM+00', 'FM+45', 'FM+90', 'FD-90', 'FD-45', 'FD+00', 'FD+45', 'FD+90', 'LU-90', 'LU-45', 'LU+00', 'LU+45', 'LU+90', 'LM-90', 'LM-45', 'LM+00', 'LM+45', 'LM+90', 'LD-90', 'LD-45', 'LD+00', 'LD+45', 'LD+90']

lighting_elevation()

lighting_type()

lighting_type_choices = ('E', 'F', 'L')

make_path(directory=None, extension=None)

Wraps the current path so that a complete path is formed

Keyword parameters:

directory : str or None

An optional directory name that will be prefixed to the returned result.

extension : str or None

An optional extension that will be suffixed to the returned filename. The extension normally includes the leading . character as in .jpg or .hdf5.

Returns a string containing the newly generated file path.

metadata = MetaData(bind=None)

path

pose

pose_azimuth()

pose_azimuth_choices = ('-90', '-67', '-45', '-30', '-22', '-15', '+00', '+15', '+22', '+30', '+45', '+67', '+90')

pose_choices = ['U-90', 'U-67', 'U-45', 'U-30', 'U-22', 'U-15', 'U+00', 'U+15', 'U+22', 'U+30', 'U+45', 'U+67', 'U+90', 'M-90', 'M-67', 'M-45', 'M-30', 'M-22', 'M-15', 'M+00', 'M+15', 'M+22', 'M+30', 'M+45', 'M+67', 'M+90', 'D-90', 'D-67', 'D-45', 'D-30', 'D-22', 'D-15', 'D+00', 'D+15', 'D+22', 'D+30', 'D+45', 'D+67', 'D+90']

pose_elevation()

privacy

protocol

protocol_id

purpose

purpose_choices = ('world', 'enroll', 'probe')

save(data, directory=None, extension='.hdf5', create_directories=True)

Saves the input data at the specified location and using the given extension.

Keyword parameters:

data : various types

The data blob to be saved (normally a numpy.ndarray).

directory : str or None

If not empty or None, this directory is prefixed to the final file destination

extension : str or None

The extension of the filename. This extension will control the type of output and the codec for saving the input blob.

create_directories : bool

Should the directory structure be created (if necessary) before writing the data?

session

session_choices = [0, 1, 2]

t = 'L'

class bob.db.caspeal.Protocol(name)

Bases: sqlalchemy.ext.declarative.api.Base

The probe protocols of the CAS-PEAL database. Training and enrollment is identical for all protocols of CAS-PEAL.

id

metadata = MetaData(bind=None)

name

protocol_choices = ('training', 'gallery', 'accessory', 'aging', 'background', 'distance', 'expression', 'lighting', 'pose')