# coding: utf-8

"""
    Generated by: https://openapi-generator.tech
"""

from __future__ import annotations
import pprint
import re  # noqa: F401
import json

from pydantic import BaseModel, ConfigDict, Field, StrictFloat, StrictInt
from typing import Any, ClassVar, Dict, List, Optional, Union
from regula.facesdk.webclient.gen.models.image_source import ImageSource
from typing import Optional, Set
from typing_extensions import Self
from pydantic import SkipValidation, Field

class MatchImageResult(BaseModel):
    """
    MatchImageResult
    """ # noqa: E501
    first_index: SkipValidation[int] = Field(alias="firstIndex", description="The image index number. Can be given; if not given, the index numbers are set automatically starting from `0`. All index numbers must be whole and unique—not repeated.")
    first_face_index: SkipValidation[Optional[float]] = Field(alias="firstFaceIndex", default=None, description="The detected face index number.")
    first: SkipValidation[Optional[ImageSource]] = Field(alias="first", default=None)
    second_index: SkipValidation[int] = Field(alias="secondIndex", description="The image index number. Can be given; if not given, the index numbers are set automatically starting from `0`. All index numbers must be whole and unique—not repeated.")
    second_face_index: SkipValidation[Optional[float]] = Field(alias="secondFaceIndex", default=None, description="The detected face index number.")
    second: SkipValidation[Optional[ImageSource]] = Field(alias="second", default=None)
    score: SkipValidation[Optional[float]] = Field(alias="score", default=None, description="A dimensionless number that shows how similar the compared faces are. 0—absolutely identical faces.")
    similarity: SkipValidation[Optional[float]] = Field(alias="similarity", default=None, description="The detected faces similarity, %. 100%—absolutely identical faces, 0%—absolutely not identical.")
    __properties: ClassVar[List[str]] = ["firstIndex", "firstFaceIndex", "first", "secondIndex", "secondFaceIndex", "second", "score", "similarity"]

    model_config = ConfigDict(
        populate_by_name=True,
        validate_assignment=True,
        protected_namespaces=(),
        arbitrary_types_allowed=True,
        use_enum_values=True
    )


    def to_str(self) -> str:
        """Returns the string representation of the model using alias"""
        return pprint.pformat(self.model_dump(by_alias=True))

    def to_json(self) -> str:
        """Returns the JSON representation of the model using alias"""
        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
        return json.dumps(self.to_dict())

    @classmethod
    def from_json(cls, json_str: str) -> Optional[Self]:
        """Create an instance of MatchImageResult from a JSON string"""
        return cls.from_dict(json.loads(json_str))

    def to_dict(self) -> Dict[str, Any]:
        """Return the dictionary representation of the model using alias.

        This has the following differences from calling pydantic's
        `self.model_dump(by_alias=True)`:

        * `None` is only added to the output dict for nullable fields that
          were set at model initialization. Other fields with value `None`
          are ignored.
        """
        excluded_fields: Set[str] = set([
        ])

        _dict = self.model_dump(
            by_alias=True,
            exclude=excluded_fields,
            exclude_none=True,
        )
        return _dict

    @classmethod
    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
        """Create an instance of MatchImageResult from a dict"""
        if obj is None:
            return None

        if not isinstance(obj, dict):
            return cls.model_validate(obj)

        _obj = cls.model_validate({
            "firstIndex": obj.get("firstIndex"),
            "firstFaceIndex": obj.get("firstFaceIndex"),
            "first": obj.get("first"),
            "secondIndex": obj.get("secondIndex"),
            "secondFaceIndex": obj.get("secondFaceIndex"),
            "second": obj.get("second"),
            "score": obj.get("score"),
            "similarity": obj.get("similarity")
        })
        return _obj


