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# coding: utf-8 # Copyright (c) 2016, 2024, Oracle and/or its affiliates. All rights reserved. # This software is dual-licensed to you under the Universal Permissive License (UPL) 1.0 as shown at https://oss.oracle.com/licenses/upl or Apache License 2.0 as shown at http://www.apache.org/licenses/LICENSE-2.0. You may choose either license. # NOTE: This class is auto generated by OracleSDKGenerator. DO NOT EDIT. API Version: 20220125 from oci.util import formatted_flat_dict, NONE_SENTINEL, value_allowed_none_or_none_sentinel # noqa: F401 from oci.decorators import init_model_state_from_kwargs @init_model_state_from_kwargs class Face(object): """ The detected face. """ def __init__(self, **kwargs): """ Initializes a new Face object with values from keyword arguments. The following keyword arguments are supported (corresponding to the getters/setters of this class): :param confidence: The value to assign to the confidence property of this Face. :type confidence: float :param bounding_polygon: The value to assign to the bounding_polygon property of this Face. :type bounding_polygon: oci.ai_vision.models.BoundingPolygon :param quality_score: The value to assign to the quality_score property of this Face. :type quality_score: float :param landmarks: The value to assign to the landmarks property of this Face. :type landmarks: list[oci.ai_vision.models.Landmark] """ self.swagger_types = { 'confidence': 'float', 'bounding_polygon': 'BoundingPolygon', 'quality_score': 'float', 'landmarks': 'list[Landmark]' } self.attribute_map = { 'confidence': 'confidence', 'bounding_polygon': 'boundingPolygon', 'quality_score': 'qualityScore', 'landmarks': 'landmarks' } self._confidence = None self._bounding_polygon = None self._quality_score = None self._landmarks = None @property def confidence(self): """ **[Required]** Gets the confidence of this Face. The confidence score, between 0 and 1. :return: The confidence of this Face. :rtype: float """ return self._confidence @confidence.setter def confidence(self, confidence): """ Sets the confidence of this Face. The confidence score, between 0 and 1. :param confidence: The confidence of this Face. :type: float """ self._confidence = confidence @property def bounding_polygon(self): """ **[Required]** Gets the bounding_polygon of this Face. :return: The bounding_polygon of this Face. :rtype: oci.ai_vision.models.BoundingPolygon """ return self._bounding_polygon @bounding_polygon.setter def bounding_polygon(self, bounding_polygon): """ Sets the bounding_polygon of this Face. :param bounding_polygon: The bounding_polygon of this Face. :type: oci.ai_vision.models.BoundingPolygon """ self._bounding_polygon = bounding_polygon @property def quality_score(self): """ **[Required]** Gets the quality_score of this Face. The quality score of the face detected, between 0 and 1. :return: The quality_score of this Face. :rtype: float """ return self._quality_score @quality_score.setter def quality_score(self, quality_score): """ Sets the quality_score of this Face. The quality score of the face detected, between 0 and 1. :param quality_score: The quality_score of this Face. :type: float """ self._quality_score = quality_score @property def landmarks(self): """ Gets the landmarks of this Face. A point of interest within a face. :return: The landmarks of this Face. :rtype: list[oci.ai_vision.models.Landmark] """ return self._landmarks @landmarks.setter def landmarks(self, landmarks): """ Sets the landmarks of this Face. A point of interest within a face. :param landmarks: The landmarks of this Face. :type: list[oci.ai_vision.models.Landmark] """ self._landmarks = landmarks def __repr__(self): return formatted_flat_dict(self) def __eq__(self, other): if other is None: return False return self.__dict__ == other.__dict__ def __ne__(self, other): return not self == other