dcase_framework.application_core.AppCore

class dcase_framework.application_core.AppCore(*args, **kwargs)[source]

Constructor

Parameters:

name : str

Application name. Default value “Application”

system_desc : str

System description. Default value “None”

system_parameter_set_id : str

System parameter set id. Default value “None”

setup_label : str

Application setup label. Default value “System”

params : ParameterContainer

Parameter container containing all parameters needed by application.

dataset : str or class

Dataset, if none given dataset name is taken from parameters “dataset->parameters->name”. Default value “none”

dataset_evaluation_mode : str

Dataset evaluation mode, “full” or “folds”. If none given, taken from parameters “dataset->parameter->evaluation_mode”. Default value “none”

show_progress_in_console : bool

Show progress in console. Default value “True”

log_system_progress : bool

Show progress in log. Default value “False”

use_ascii_progress_bar : bool

Show progress bar using ASCII characters. Use this if your console does not support UTF-8 characters. Default value “False”

logger : logging

Instance of logging Default value “none”

Datasets : dict of Dataset classes

Dict of datasets available for application. Dict key is name of the dataset and value link to class inherited from Dataset base class. Given dict is used to update internal dict. Default value “none”

FeatureExtractor : class inherited from FeatureExtractor

Feature extractor class. Use this to override default class. Default value “FeatureExtractor”

FeatureNormalizer : class inherited from FeatureNormalizer

Feature normalizer class. Use this to override default class. Default value “FeatureNormalizer”

FeatureMasker : class inherited from FeatureMasker

Feature masker class. Use this to override default class. Default value “FeatureMasker”

FeatureContainer : class inherited from FeatureContainer

Feature container class. Use this to override default class. Default value “FeatureContainer”

FeatureStacker : class inherited from FeatureStacker

Feature stacker class. Use this to override default class. Default value “FeatureStacker”

FeatureAggregator : class inherited from FeatureAggregator

Feature aggregate class. Use this to override default class. Default value “FeatureAggregator”

DataProcessor : class inherited from DataProcessor

DataProcessor class. Use this to override default class. Default value “DataProcessor”

DataSequencer : class inherited from DataSequencer

DataSequencer class. Use this to override default class. Default value “DataSequencer”

ProcessingChain : class inherited from ProcessingChain

DataSequencer class. Use this to override default class. Default value “ProcessingChain”

Learners: dict of Learner classes

Dict of learners available for application. Dict key is method the class implements and value link to class inherited from LearnerContainer base class. Given dict is used to update internal dict.

SceneRecognizer : class inherited from SceneRecognizer

DataSequencer class. Use this to override default class. Default value “SceneRecognizer”

EventRecognizer : class inherited from EventRecognizer

DataSequencer class. Use this to override default class. Default value “EventRecognizer”

ui : class inherited from FancyLogger

Output formatter class. Use this to override default class. Default value “FancyLogger”

Raises

——

ValueError:

No valid ParameterContainer given.

__init__(*args, **kwargs)[source]

Constructor

Parameters:

name : str

Application name. Default value “Application”

system_desc : str

System description. Default value “None”

system_parameter_set_id : str

System parameter set id. Default value “None”

setup_label : str

Application setup label. Default value “System”

params : ParameterContainer

Parameter container containing all parameters needed by application.

dataset : str or class

Dataset, if none given dataset name is taken from parameters “dataset->parameters->name”. Default value “none”

dataset_evaluation_mode : str

Dataset evaluation mode, “full” or “folds”. If none given, taken from parameters “dataset->parameter->evaluation_mode”. Default value “none”

show_progress_in_console : bool

Show progress in console. Default value “True”

log_system_progress : bool

Show progress in log. Default value “False”

use_ascii_progress_bar : bool

Show progress bar using ASCII characters. Use this if your console does not support UTF-8 characters. Default value “False”

logger : logging

Instance of logging Default value “none”

Datasets : dict of Dataset classes

Dict of datasets available for application. Dict key is name of the dataset and value link to class inherited from Dataset base class. Given dict is used to update internal dict. Default value “none”

FeatureExtractor : class inherited from FeatureExtractor

Feature extractor class. Use this to override default class. Default value “FeatureExtractor”

FeatureNormalizer : class inherited from FeatureNormalizer

Feature normalizer class. Use this to override default class. Default value “FeatureNormalizer”

FeatureMasker : class inherited from FeatureMasker

Feature masker class. Use this to override default class. Default value “FeatureMasker”

FeatureContainer : class inherited from FeatureContainer

Feature container class. Use this to override default class. Default value “FeatureContainer”

FeatureStacker : class inherited from FeatureStacker

Feature stacker class. Use this to override default class. Default value “FeatureStacker”

FeatureAggregator : class inherited from FeatureAggregator

Feature aggregate class. Use this to override default class. Default value “FeatureAggregator”

DataProcessor : class inherited from DataProcessor

DataProcessor class. Use this to override default class. Default value “DataProcessor”

DataSequencer : class inherited from DataSequencer

DataSequencer class. Use this to override default class. Default value “DataSequencer”

ProcessingChain : class inherited from ProcessingChain

DataSequencer class. Use this to override default class. Default value “ProcessingChain”

Learners: dict of Learner classes

Dict of learners available for application. Dict key is method the class implements and value link to class inherited from LearnerContainer base class. Given dict is used to update internal dict.

SceneRecognizer : class inherited from SceneRecognizer

DataSequencer class. Use this to override default class. Default value “SceneRecognizer”

EventRecognizer : class inherited from EventRecognizer

DataSequencer class. Use this to override default class. Default value “EventRecognizer”

ui : class inherited from FancyLogger

Output formatter class. Use this to override default class. Default value “FancyLogger”

Raises

——

ValueError:

No valid ParameterContainer given.

Methods

__init__(\*args, \*\*kwargs) Constructor
check_resources()
feature_extraction(\*args, \*\*kwargs) Feature extraction stage
feature_normalization(\*args, \*\*kwargs) Feature normalization stage
initialize(\*args, \*\*kwargs) Initialize application
model_information(\*args, \*\*kwargs)
show_dataset_list() List of datasets available
show_eval()
show_parameter_set_list(set_list) List of datasets available
show_parameters() Show parameters
system_evaluation(\*args, \*\*kwargs) System evaluation stage.
system_testing([overwrite]) System testing stage
system_training(\*args, \*\*kwargs) System training stage