Source code for annofabapi.pydantic_models.bounding_box_metadata

"""


No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator)

The version of the OpenAPI document: 1.0.0
Generated by OpenAPI Generator (https://openapi-generator.tech)

Do not edit the class manually.
"""

from __future__ import annotations

import json
import pprint
import re  # noqa: F401
from typing import Any, ClassVar, Dict, List, Set

from pydantic import BaseModel, ConfigDict, Field, StrictBool, StrictInt, StrictStr, field_validator
from typing_extensions import Annotated, Self

from annofabapi.pydantic_models.position_for_minimum_bounding_box_insertion import PositionForMinimumBoundingBoxInsertion




class BoundingBoxMetadata(BaseModel):
    """
    ベクター形式のアノテーション（矩形、ポリゴン、ポリライン、点）のメタデータ
    """

    min_width: StrictInt = Field(description="幅の最小値[ピクセル]")
    min_height: StrictInt = Field(description="高さの最小値[ピクセル]")
    min_warn_rule: StrictStr = Field(
        description="サイズの制約に関する情報 * `none` - 制約なし * `or` - 幅と高さの両方が最小値以上 * `and` - 幅と高さのどちらか一方が最小値以上 "
    )
    min_area: Annotated[int, Field(strict=True, ge=1)] | None = Field(default=None, description="面積の最小値[平方ピクセル]")
    max_vertices: StrictInt | None = Field(default=None, description="頂点数の最大値")
    min_vertices: StrictInt | None = Field(default=None, description="頂点数の最小値")
    position_for_minimum_bounding_box_insertion: PositionForMinimumBoundingBoxInsertion | None = None
    tolerance: StrictInt | None = Field(default=None, description="許容誤差[ピクセル]")
    has_direction: StrictBool | None = Field(
        default=False,
        description="`annotation_type` が `polyline` の場合、アノテーションに向きを持たせるかどうかを指定できます。 この値が `true` の場合、Annofabの標準画像エディタ上ではポリラインの向きを示す矢印が描画されるようになります。  `annotationType` が `polyline` 以外の場合は必ず `false` となります。 ",
    )
    __properties: ClassVar[List[str]] = [
        "min_width",
        "min_height",
        "min_warn_rule",
        "min_area",
        "max_vertices",
        "min_vertices",
        "position_for_minimum_bounding_box_insertion",
        "tolerance",
        "has_direction",
    ]



    @field_validator("min_warn_rule")
    def min_warn_rule_validate_enum(cls, value):
        """Validates the enum"""
        if value not in set(["none", "or", "and"]):
            raise ValueError("must be one of enum values ('none', 'or', 'and')")
        return value


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



    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) -> Self | None:
        """Create an instance of BoundingBoxMetadata 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,
        )
        # override the default output from pydantic by calling `to_dict()` of position_for_minimum_bounding_box_insertion
        if self.position_for_minimum_bounding_box_insertion:
            _dict["position_for_minimum_bounding_box_insertion"] = self.position_for_minimum_bounding_box_insertion.to_dict()
        return _dict




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

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

        _obj = cls.model_validate(
            {
                "min_width": obj.get("min_width"),
                "min_height": obj.get("min_height"),
                "min_warn_rule": obj.get("min_warn_rule"),
                "min_area": obj.get("min_area"),
                "max_vertices": obj.get("max_vertices"),
                "min_vertices": obj.get("min_vertices"),
                "position_for_minimum_bounding_box_insertion": PositionForMinimumBoundingBoxInsertion.from_dict(
                    obj["position_for_minimum_bounding_box_insertion"]
                )
                if obj.get("position_for_minimum_bounding_box_insertion") is not None
                else None,
                "tolerance": obj.get("tolerance"),
                "has_direction": obj.get("has_direction") if obj.get("has_direction") is not None else False,
            }
        )
        return _obj