def __init__(self, *args, **kwargs): # noqa: E501
"""INDefault - a model defined in OpenAPI
Keyword Args:
_check_type (bool): if True, values for parameters in openapi_types
will be type checked and a TypeError will be
raised if the wrong type is input.
Defaults to True
_path_to_item (tuple/list): This is a list of keys or values to
drill down to the model in received_data
when deserializing a response
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_configuration (Configuration): the instance to use when
deserializing a file_type parameter.
If passed, type conversion is attempted
If omitted no type conversion is done.
_visited_composed_classes (tuple): This stores a tuple of
classes that we have traveled through so that
if we see that class again we will not use its
discriminator again.
When traveling through a discriminator, the
composed schema that is
is traveled through is added to this set.
For example if Animal has a discriminator
petType and we pass in "Dog", and the class Dog
allOf includes Animal, we move through Animal
once using the discriminator, and pick Dog.
Then in Dog, we will make an instance of the
Animal class but this time we won't travel
through its discriminator because we passed in
_visited_composed_classes = (Animal,)
thresh (float): Threshold when an object can be recognized. Lowering the value will increase the probability of recognizing objects. A threshhold of 0.5 would mean, that 50% of an object like a face must be visible, to be detected.Setting the value too low however, can cause false positives.. [optional] if omitted the server will use the default value of 0.5 # noqa: E501
grey (int): A grey scale color to use for frame or masking. '0' will represent black, while the maximum '255' will be white.. [optional] if omitted the server will use the default value of 127 # noqa: E501
"""
_check_type = kwargs.pop('_check_type', True)
_spec_property_naming = kwargs.pop('_spec_property_naming', False)
_path_to_item = kwargs.pop('_path_to_item', ())
_configuration = kwargs.pop('_configuration', None)
_visited_composed_classes = kwargs.pop('_visited_composed_classes', ())
if args:
raise ApiTypeError(
"Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments."
% (
args,
self.__class__.__name__,
),
path_to_item=_path_to_item,
valid_classes=(self.__class__, ),
)
self._data_store = {}
self._check_type = _check_type
self._spec_property_naming = _spec_property_naming
self._path_to_item = _path_to_item
self._configuration = _configuration
self._visited_composed_classes = _visited_composed_classes + (
self.__class__, )
for var_name, var_value in kwargs.items():
if var_name not in self.attribute_map and \
self._configuration is not None and \
self._configuration.discard_unknown_keys and \
self.additional_properties_type is None:
# discard variable.
continue
setattr(self, var_name, var_value)
if var_name in self.read_only_vars:
raise ApiAttributeError(
f"`{var_name}` is a read-only attribute. Use `from_openapi_data` to instantiate "
f"class with read only attributes.")
def _from_openapi_data(cls, *args, **kwargs): # noqa: E501
"""LicenseInfo - a model defined in OpenAPI
Keyword Args:
_check_type (bool): if True, values for parameters in openapi_types
will be type checked and a TypeError will be
raised if the wrong type is input.
Defaults to True
_path_to_item (tuple/list): This is a list of keys or values to
drill down to the model in received_data
when deserializing a response
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_configuration (Configuration): the instance to use when
deserializing a file_type parameter.
If passed, type conversion is attempted
If omitted no type conversion is done.
_visited_composed_classes (tuple): This stores a tuple of
classes that we have traveled through so that
if we see that class again we will not use its
discriminator again.
When traveling through a discriminator, the
composed schema that is
is traveled through is added to this set.
For example if Animal has a discriminator
petType and we pass in "Dog", and the class Dog
allOf includes Animal, we move through Animal
once using the discriminator, and pick Dog.
Then in Dog, we will make an instance of the
Animal class but this time we won't travel
through its discriminator because we passed in
_visited_composed_classes = (Animal,)
credits_used (int): Credits used for the license key.. [optional] # noqa: E501
credits_remaining (int): Credits remaining for the license key.. [optional] # noqa: E501
total_credits (int): Total credits contained within the license.. [optional] # noqa: E501
"""
_check_type = kwargs.pop('_check_type', True)
_spec_property_naming = kwargs.pop('_spec_property_naming', False)
_path_to_item = kwargs.pop('_path_to_item', ())
_configuration = kwargs.pop('_configuration', None)
_visited_composed_classes = kwargs.pop('_visited_composed_classes', ())
self = super(OpenApiModel, cls).__new__(cls)
if args:
raise ApiTypeError(
"Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments."
% (
args,
self.__class__.__name__,
),
path_to_item=_path_to_item,
valid_classes=(self.__class__, ),
)
self._data_store = {}
self._check_type = _check_type
self._spec_property_naming = _spec_property_naming
self._path_to_item = _path_to_item
self._configuration = _configuration
self._visited_composed_classes = _visited_composed_classes + (
self.__class__, )
for var_name, var_value in kwargs.items():
if var_name not in self.attribute_map and \
self._configuration is not None and \
self._configuration.discard_unknown_keys and \
self.additional_properties_type is None:
# discard variable.
continue
setattr(self, var_name, var_value)
return self
def __init__(self, *args, **kwargs): # noqa: E501
"""INDefineAI - a model defined in OpenAPI
Keyword Args:
_check_type (bool): if True, values for parameters in openapi_types
will be type checked and a TypeError will be
raised if the wrong type is input.
Defaults to True
_path_to_item (tuple/list): This is a list of keys or values to
drill down to the model in received_data
when deserializing a response
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_configuration (Configuration): the instance to use when
deserializing a file_type parameter.
If passed, type conversion is attempted
If omitted no type conversion is done.
_visited_composed_classes (tuple): This stores a tuple of
classes that we have traveled through so that
if we see that class again we will not use its
discriminator again.
When traveling through a discriminator, the
composed schema that is
is traveled through is added to this set.
For example if Animal has a discriminator
petType and we pass in "Dog", and the class Dog
allOf includes Animal, we move through Animal
once using the discriminator, and pick Dog.
Then in Dog, we will make an instance of the
Animal class but this time we won't travel
through its discriminator because we passed in
_visited_composed_classes = (Animal,)
in_image ([INImage]): Configures your detection. As there are literally hundreds of parameters, INDefine uses prototypes to get usefull behaviour. This includes a default setting for parameters and rules that should be applied to images. You can combine multiple detections by using more than 1 prototype. [optional] # noqa: E501
"""
_check_type = kwargs.pop('_check_type', True)
_spec_property_naming = kwargs.pop('_spec_property_naming', False)
_path_to_item = kwargs.pop('_path_to_item', ())
_configuration = kwargs.pop('_configuration', None)
_visited_composed_classes = kwargs.pop('_visited_composed_classes', ())
if args:
raise ApiTypeError(
"Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments."
% (
args,
self.__class__.__name__,
),
path_to_item=_path_to_item,
valid_classes=(self.__class__, ),
)
self._data_store = {}
self._check_type = _check_type
self._spec_property_naming = _spec_property_naming
self._path_to_item = _path_to_item
self._configuration = _configuration
self._visited_composed_classes = _visited_composed_classes + (
self.__class__, )
for var_name, var_value in kwargs.items():
if var_name not in self.attribute_map and \
self._configuration is not None and \
self._configuration.discard_unknown_keys and \
self.additional_properties_type is None:
# discard variable.
continue
setattr(self, var_name, var_value)
if var_name in self.read_only_vars:
raise ApiAttributeError(
f"`{var_name}` is a read-only attribute. Use `from_openapi_data` to instantiate "
f"class with read only attributes.")
def __init__(self, *args, **kwargs): # noqa: E501
"""INObject - a model defined in OpenAPI
Keyword Args:
_check_type (bool): if True, values for parameters in openapi_types
will be type checked and a TypeError will be
raised if the wrong type is input.
Defaults to True
_path_to_item (tuple/list): This is a list of keys or values to
drill down to the model in received_data
when deserializing a response
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_configuration (Configuration): the instance to use when
deserializing a file_type parameter.
If passed, type conversion is attempted
If omitted no type conversion is done.
_visited_composed_classes (tuple): This stores a tuple of
classes that we have traveled through so that
if we see that class again we will not use its
discriminator again.
When traveling through a discriminator, the
composed schema that is
is traveled through is added to this set.
For example if Animal has a discriminator
petType and we pass in "Dog", and the class Dog
allOf includes Animal, we move through Animal
once using the discriminator, and pick Dog.
Then in Dog, we will make an instance of the
Animal class but this time we won't travel
through its discriminator because we passed in
_visited_composed_classes = (Animal,)
in_class (str): The classification of the recognized object.. [optional] # noqa: E501
in_group (str): The group of the classification.. [optional] # noqa: E501
in_id (str): The group of the classification.. [optional] # noqa: E501
color (str): The color of the object, e.g. the color of the hair. Is only available for certain classification objects. See list below: * _hair_ - black, brown, blonde, grey, red, other. [optional] # noqa: E501
style (str): The style attribute of the object, e.g. the style of the hair. Is only available for certain classification objects. See list below: * _hair_ - longHaired, shortHaired. [optional] # noqa: E501
x0 (float): The center of the rectangle in the horizontal (x) direction.. [optional] # noqa: E501
y0 (float): The center of the rectangle in the vertical (y) direction.. [optional] # noqa: E501
width (float): The total width of the rectangle in the horizontal (x) direction. Use _x0 - width / 2_ and _x0 + width / 2_ to get the left and right edges of the rectangle.. [optional] # noqa: E501
height (float): The total height of the rectangle in the vertical (y) direction. Use _y0 - height / 2_ and _y0 + height / 2_ to get the top and bottom edges of the rectangle.. [optional] # noqa: E501
probability (int): The probability that the object found matches the classification.. [optional] # noqa: E501
"""
_check_type = kwargs.pop('_check_type', True)
_spec_property_naming = kwargs.pop('_spec_property_naming', False)
_path_to_item = kwargs.pop('_path_to_item', ())
_configuration = kwargs.pop('_configuration', None)
_visited_composed_classes = kwargs.pop('_visited_composed_classes', ())
if args:
raise ApiTypeError(
"Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments." % (
args,
self.__class__.__name__,
),
path_to_item=_path_to_item,
valid_classes=(self.__class__,),
)
self._data_store = {}
self._check_type = _check_type
self._spec_property_naming = _spec_property_naming
self._path_to_item = _path_to_item
self._configuration = _configuration
self._visited_composed_classes = _visited_composed_classes + (self.__class__,)
for var_name, var_value in kwargs.items():
if var_name not in self.attribute_map and \
self._configuration is not None and \
self._configuration.discard_unknown_keys and \
self.additional_properties_type is None:
# discard variable.
continue
setattr(self, var_name, var_value)
if var_name in self.read_only_vars:
raise ApiAttributeError(f"`{var_name}` is a read-only attribute. Use `from_openapi_data` to instantiate "
f"class with read only attributes.")
def __init__(self, *args, **kwargs): # noqa: E501
"""INParam - a model defined in OpenAPI
Keyword Args:
_check_type (bool): if True, values for parameters in openapi_types
will be type checked and a TypeError will be
raised if the wrong type is input.
Defaults to True
_path_to_item (tuple/list): This is a list of keys or values to
drill down to the model in received_data
when deserializing a response
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_configuration (Configuration): the instance to use when
deserializing a file_type parameter.
If passed, type conversion is attempted
If omitted no type conversion is done.
_visited_composed_classes (tuple): This stores a tuple of
classes that we have traveled through so that
if we see that class again we will not use its
discriminator again.
When traveling through a discriminator, the
composed schema that is
is traveled through is added to this set.
For example if Animal has a discriminator
petType and we pass in "Dog", and the class Dog
allOf includes Animal, we move through Animal
once using the discriminator, and pick Dog.
Then in Dog, we will make an instance of the
Animal class but this time we won't travel
through its discriminator because we passed in
_visited_composed_classes = (Animal,)
in_class (str): The classification of the object, that the element refers to. The following is a tree representation of the prototypes and their containing classifications. Default parameter values are defined per classification object. The default values of 'min', 'max' and 'drawMode' are witten after the name of the classification object in that order. Use the prototype names to set parameters to all of the containing classifications. ##### nudityCheck > _A prototype containing classifications for basic human attributes and sexual contents. This prototype and the containing classifications are activated by default_ * _face_ _(1, 3, 0)_ * _hand_ _(0, -1, 0)_ * _foot_ _(0, -1, 0)_ * _footwear_ _(0, -1, 0)_ * _chest_ _(0, -1, 0)_ * _breast_ _(0, 0, 2)_ * _vulva_ _(0, 0, 2)_ * _penis_ _(0, 0, 2)_ * _vagina_ _(0, 0, 2)_ * _buttocks_ _(0, 0, 2)_ * _anus_ _(0, 0, 2)_ * _toy_ _(0, -1, 0)_ * _oral_ _(0, 0, 2)_ * _penetration_ _(0, 0, 2)_ ##### ageEstimation > _Contains classification objects for estimating the age of a human face. This prototype activates nudityCheck_ * _child (*)_ _(0, 0, 6)_ * _adult (*)_ _(0, -1, 0)_ * _senior (*)_ _(0, -1, 0)_ * _pose_ _(0, 0, 0)_ - The age can not be estimated, due to a pose that hides facial features. ##### attributesCheck > _Contains classification objects for various attributes of the human face. This prototype activates nudityCheck_ * _female (*)_ _(0, -1, 0)_ * _male (*)_ _(0, -1, 0)_ * _hair_ _(0, -1, 0)_ * _hairless_ _(0, -1, 0)_ * _beard_ _(0, -1, 0)_ * _moustache_ _(0, -1, 0)_ * _headpiece_ _(0, -1, 0)_ * _glasses_ _(0, -1, 0)_ * _sunglasses_ _(0, -1, 0)_ * _mask_ _(0, -1, 0)_ ##### nippleCheck > _Contains classifications for determining if the object recognized as breast has a nipple. This prototype activates nudityCheck_ * _noNipple_ _(0, 0, 0)_ * _hasNipple_ _(0, 0, 0)_ ##### illegalSymbols > _Contains various classification objects of symbols that are prohibited in Germany (e.g. Hakenkreuz, SS, etc). These are grouped under a single name_ * _illegalSymbols_ _(0, 0, 1)_ ##### textRecognition > _Contains letters, numbers and some symbols (e.g. @, #, etc) as classification objects. These are grouped under a single name_ * _textRecognition_ _(0, 6, 6)_ _Classification objects that are marked with (*) are sub-classifications of face. Both face and the marked classification are affected by the given parameter values._ _Please be aware that the default values can be subject to change. This is due to the difficulty of recognizing certain objects e.g. objects that are classified as toy._. [optional] # noqa: E501
min (int): The minimum amount of objects allowed on the source media. Setting the value to -1 will cause the AI to ignore this rule.. [optional] # noqa: E501
max (int): The maximum amount of objects allowed on the source media. Setting the value to -1 will cause the AI to ignore this rule.. [optional] # noqa: E501
severity (int): Set a value to define the severity of a broken rule of the given classification object.. [optional] if omitted the server will use the default value of 100 # noqa: E501
draw_mode (int): The draw mode that will be used for the creating the media. * _0_ - will draw nothing, * _1_ - will draw a frame with class name surrounding the object, * _2_ - will draw a filled rectangle that will mask the object, * _3_ - is a combination between _1_ and _2_ (frame/name + mask), * _6_ - will blur the object and * _7_ - is a combination between _1_ and _6_ (frame/name + blur).. [optional] # noqa: E501
grey (int): A grey scale color to use for masking. '0' will represent black, while the maximum '255' will be white.. [optional] if omitted the server will use the default value of 127 # noqa: E501
scale (float): Scale of the draw rectangle around the classification object. Specify a value to increase or decrease the size of the border.. [optional] if omitted the server will use the default value of 1.0 # noqa: E501
"""
_check_type = kwargs.pop('_check_type', True)
_spec_property_naming = kwargs.pop('_spec_property_naming', False)
_path_to_item = kwargs.pop('_path_to_item', ())
_configuration = kwargs.pop('_configuration', None)
_visited_composed_classes = kwargs.pop('_visited_composed_classes', ())
if args:
raise ApiTypeError(
"Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments."
% (
args,
self.__class__.__name__,
),
path_to_item=_path_to_item,
valid_classes=(self.__class__, ),
)
self._data_store = {}
self._check_type = _check_type
self._spec_property_naming = _spec_property_naming
self._path_to_item = _path_to_item
self._configuration = _configuration
self._visited_composed_classes = _visited_composed_classes + (
self.__class__, )
for var_name, var_value in kwargs.items():
if var_name not in self.attribute_map and \
self._configuration is not None and \
self._configuration.discard_unknown_keys and \
self.additional_properties_type is None:
# discard variable.
continue
setattr(self, var_name, var_value)
if var_name in self.read_only_vars:
raise ApiAttributeError(
f"`{var_name}` is a read-only attribute. Use `from_openapi_data` to instantiate "
f"class with read only attributes.")
def __init__(self, *args, **kwargs): # noqa: E501
"""IrisNet - a model defined in OpenAPI
Keyword Args:
_check_type (bool): if True, values for parameters in openapi_types
will be type checked and a TypeError will be
raised if the wrong type is input.
Defaults to True
_path_to_item (tuple/list): This is a list of keys or values to
drill down to the model in received_data
when deserializing a response
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_configuration (Configuration): the instance to use when
deserializing a file_type parameter.
If passed, type conversion is attempted
If omitted no type conversion is done.
_visited_composed_classes (tuple): This stores a tuple of
classes that we have traveled through so that
if we see that class again we will not use its
discriminator again.
When traveling through a discriminator, the
composed schema that is
is traveled through is added to this set.
For example if Animal has a discriminator
petType and we pass in "Dog", and the class Dog
allOf includes Animal, we move through Animal
once using the discriminator, and pick Dog.
Then in Dog, we will make an instance of the
Animal class but this time we won't travel
through its discriminator because we passed in
_visited_composed_classes = (Animal,)
rules_broken (int): The amount of broken rules that are contained in the source media.. [optional] # noqa: E501
help_suggested (int): In cases where the AI is uncertain, this attribute is set (1), indication that it could be useful to double check the source media by a human.. [optional] # noqa: E501
severity (int): The highest severity value found amongst the broken rules.. [optional] # noqa: E501
getn_classes (int): The amount of classification objects that were checked against on the source media. This does not mean that all of the classifications were found.. [optional] # noqa: E501
getn_objects (int): The amount of objects that were recognized on the source image.. [optional] # noqa: E501
in_rule ([INRule]): This list contains one rule per classification. Rules for classification objects that were not found, are omitted.. [optional] # noqa: E501
in_object ([INObject]): A list of all instances of the classification objects found on the source image.. [optional] # noqa: E501
"""
_check_type = kwargs.pop('_check_type', True)
_spec_property_naming = kwargs.pop('_spec_property_naming', False)
_path_to_item = kwargs.pop('_path_to_item', ())
_configuration = kwargs.pop('_configuration', None)
_visited_composed_classes = kwargs.pop('_visited_composed_classes', ())
if args:
raise ApiTypeError(
"Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments."
% (
args,
self.__class__.__name__,
),
path_to_item=_path_to_item,
valid_classes=(self.__class__, ),
)
self._data_store = {}
self._check_type = _check_type
self._spec_property_naming = _spec_property_naming
self._path_to_item = _path_to_item
self._configuration = _configuration
self._visited_composed_classes = _visited_composed_classes + (
self.__class__, )
for var_name, var_value in kwargs.items():
if var_name not in self.attribute_map and \
self._configuration is not None and \
self._configuration.discard_unknown_keys and \
self.additional_properties_type is None:
# discard variable.
continue
setattr(self, var_name, var_value)
if var_name in self.read_only_vars:
raise ApiAttributeError(
f"`{var_name}` is a read-only attribute. Use `from_openapi_data` to instantiate "
f"class with read only attributes.")
def __init__(self, *args, **kwargs): # noqa: E501
"""INImage - a model defined in OpenAPI
Keyword Args:
_check_type (bool): if True, values for parameters in openapi_types
will be type checked and a TypeError will be
raised if the wrong type is input.
Defaults to True
_path_to_item (tuple/list): This is a list of keys or values to
drill down to the model in received_data
when deserializing a response
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_configuration (Configuration): the instance to use when
deserializing a file_type parameter.
If passed, type conversion is attempted
If omitted no type conversion is done.
_visited_composed_classes (tuple): This stores a tuple of
classes that we have traveled through so that
if we see that class again we will not use its
discriminator again.
When traveling through a discriminator, the
composed schema that is
is traveled through is added to this set.
For example if Animal has a discriminator
petType and we pass in "Dog", and the class Dog
allOf includes Animal, we move through Animal
once using the discriminator, and pick Dog.
Then in Dog, we will make an instance of the
Animal class but this time we won't travel
through its discriminator because we passed in
_visited_composed_classes = (Animal,)
proto (str): Name of commonly used rule sets (prototypes). That can be used to speed up the setup process. * _nudityCheck_ - Commonly used prototype to check for nudity. * _ageVerification_ - Deprecated see 'ageEstimation'. * _ageEstimation_ - Checks if there are children, adults or seniors recognizable. This is intended to be a suggestion to help you implement further steps. * _illegalSymbols_ - Checks for symbols that are not permitted in Germany. * _textRecognition_ - Checks for text occurrences. * _attributesCheck_ - Checks for attributes of a person (e.g. female, male, glasses, hair, etc). * _nippleCheck_ - Check for determining if the object recognized as breast has a nipple. . [optional] # noqa: E501
"""
_check_type = kwargs.pop('_check_type', True)
_spec_property_naming = kwargs.pop('_spec_property_naming', False)
_path_to_item = kwargs.pop('_path_to_item', ())
_configuration = kwargs.pop('_configuration', None)
_visited_composed_classes = kwargs.pop('_visited_composed_classes', ())
if args:
raise ApiTypeError(
"Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments." % (
args,
self.__class__.__name__,
),
path_to_item=_path_to_item,
valid_classes=(self.__class__,),
)
self._data_store = {}
self._check_type = _check_type
self._spec_property_naming = _spec_property_naming
self._path_to_item = _path_to_item
self._configuration = _configuration
self._visited_composed_classes = _visited_composed_classes + (self.__class__,)
for var_name, var_value in kwargs.items():
if var_name not in self.attribute_map and \
self._configuration is not None and \
self._configuration.discard_unknown_keys and \
self.additional_properties_type is None:
# discard variable.
continue
setattr(self, var_name, var_value)
if var_name in self.read_only_vars:
raise ApiAttributeError(f"`{var_name}` is a read-only attribute. Use `from_openapi_data` to instantiate "
f"class with read only attributes.")
