Python API

This is the Bob database entry for the GBU (Good, Bad and Ugly) database.

bob.db.gbu.get_config()

Returns a string containing the configuration information.

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

Bases: sqlalchemy.ext.declarative.api.Base

Annotations of the GBU 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.gbu.Client(signature)

Bases: sqlalchemy.ext.declarative.api.Base

The client of the GBU database consists of an integral ID as well as the ‘signature’ as read from the file lists.

id

metadata = MetaData(bind=None)

class bob.db.gbu.Database(original_directory=None, original_extension='.jpg')

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

The dataset 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 object 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, subworld=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’).

subworld

One or several training sets (‘x1’, ‘x2’, ‘x4’, ‘x8’), only valid if group is ‘world’.

protocol

One or several of the GBU protocols (‘Good’, ‘Bad’, ‘Ugly’), only valid if group is ‘dev’.

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

clients(groups=None, subworld=None, protocol=None)

Returns a list of clients for the specific query by the user.

Keyword Parameters:

groups

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

subworld

One or several training sets (‘x1’, ‘x2’, ‘x4’, ‘x8’), only valid if group is ‘world’.

protocol

One or several of the GBU protocols (‘Good’, ‘Bad’, ‘Ugly’), only valid if group is ‘dev’.

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 (real 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, group='dev', protocol_type='gbu', **kwargs)

Returns the client id attached to the given model id. Dependent on the protocol type and the group, it is expected that

• model_id is a file id, when protocol type is ‘gbu’
• model_id is a client id, when protocol type is ‘multi’ or group is ‘world’

Keyword Parameters:

model_id

The model id to consider

group

The group to which the model belong, might be ‘world’ or ‘dev’.

protocol_type

One protocol type from (‘gbu’, ‘multi’)

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

One or several of the GBU protocols (‘Good’, ‘Bad’, ‘Ugly’), only valid if group is ‘dev’.

Returns: a list of groups

is_valid()

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

model_ids(groups=None, subworld=None, protocol=None, protocol_type='gbu')

Returns a list of model ids for the specific query by the user. The returned list depends on the protocol_type:

• ‘gbu’: A list containing file id’s (there is one model per file)
• ‘multi’: A list containing client id’s (there is one model per client)

Note

for the ‘world’ group, model ids are ALWAYS client ids

Keyword Parameters:

groups

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

subworld

One or several training sets (‘x1’, ‘x2’, ‘x4’, ‘x8’), only valid if group is ‘world’.

protocol

One or several of the GBU protocols (‘Good’, ‘Bad’, ‘Ugly’), only valid if group is ‘dev’.

protocol_type

One protocol type from (‘gbu’, ‘multi’)

Returns: A list containing all the model id’s belonging to the given group.

models(groups=None, subworld=None, protocol=None, protocol_type='gbu')

Returns a list of models for the specific query by the user. The returned type of model depends on the protocol_type:

• ‘gbu’: A list containing File objects (there is one model per file)
• ‘multi’: A list containing Client objects (there is one model per client)

Keyword Parameters:

groups

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

subworld

One or several training sets (‘x1’, ‘x2’, ‘x4’, ‘x8’), only valid if group is ‘world’.

protocol

One or several of the GBU protocols (‘Good’, ‘Bad’, ‘Ugly’), only valid if group is ‘dev’.

protocol_type

One protocol type from (‘gbu’, ‘multi’)

Returns: A list containing all the models belonging to the given group.

objects(groups=None, subworld=None, protocol=None, purposes=None, model_ids=None, protocol_type='gbu')

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

Keyword Parameters:

groups

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

subworld

One or several training sets (‘x1’, ‘x2’, ‘x4’, ‘x8’), only valid if group is ‘world’.

protocol

One or several of the GBU protocols (‘Good’, ‘Bad’, ‘Ugly’), only valid if group is ‘dev’.

purposes

One or several groups for which objects should be retrieved (‘enroll’, ‘probe’), only valid when the group is ‘dev’·

model_ids

If given (as a list of model id’s or a single one), only the objects belonging to the specified model id is returned. The content of the model id is dependent on the protocol type:

• model id is a file id, when protocol type is ‘gbu’
• model id is a client id, when protocol type is ‘multi’, or when group is ‘world’

protocol_type

One protocol type from (‘gbu’, ‘multi’), only required when model_ids are specified

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.

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.gbu.File(presentation, signature, path)

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

The file of the GBU database consists of an integral id as well as the ‘presentation’ as read from the file lists. Each file has one annotation and one associated client.

annotation

client

client_id

id

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

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?

class bob.db.gbu.Protocol(name, purpose)

Bases: sqlalchemy.ext.declarative.api.Base

The protocol class stores both the protocol name, as well as the purpose.

files

id

metadata = MetaData(bind=None)

name

protocol_choices = ('Good', 'Bad', 'Ugly')

purpose

purpose_choices = ('enroll', 'probe')

class bob.db.gbu.Subworld(name)

Bases: sqlalchemy.ext.declarative.api.Base

The subworld class defines different training set sizes. It is created from the ‘x1’, ‘x2’, ‘x4’ and ‘x8’ training lists from the GBU database.

files

id

metadata = MetaData(bind=None)

name

subworld_choices = ('x1', 'x2', 'x4', 'x8')