dcase_framework.application_core.AppCore¶
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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
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ValueError:
No valid ParameterContainer given.
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__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 -