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Asset Face Without Person Response Dto

immichpy.client.generated.models.asset_face_without_person_response_dto.AssetFaceWithoutPersonResponseDto pydantic-model

Bases: BaseModel

AssetFaceWithoutPersonResponseDto

Show JSON schema: 
{
  "$defs": {
    "SourceType": {
      "description": "Face detection source type",
      "enum": [
        "machine-learning",
        "exif",
        "manual"
      ],
      "title": "SourceType",
      "type": "string"
    }
  },
  "description": "AssetFaceWithoutPersonResponseDto",
  "properties": {
    "boundingBoxX1": {
      "description": "Bounding box X1 coordinate",
      "title": "Boundingboxx1",
      "type": "integer"
    },
    "boundingBoxX2": {
      "description": "Bounding box X2 coordinate",
      "title": "Boundingboxx2",
      "type": "integer"
    },
    "boundingBoxY1": {
      "description": "Bounding box Y1 coordinate",
      "title": "Boundingboxy1",
      "type": "integer"
    },
    "boundingBoxY2": {
      "description": "Bounding box Y2 coordinate",
      "title": "Boundingboxy2",
      "type": "integer"
    },
    "id": {
      "description": "Face ID",
      "format": "uuid",
      "title": "Id",
      "type": "string"
    },
    "imageHeight": {
      "description": "Image height in pixels",
      "title": "Imageheight",
      "type": "integer"
    },
    "imageWidth": {
      "description": "Image width in pixels",
      "title": "Imagewidth",
      "type": "integer"
    },
    "sourceType": {
      "anyOf": [
        {
          "$ref": "#/$defs/SourceType"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Face detection source type"
    }
  },
  "required": [
    "boundingBoxX1",
    "boundingBoxX2",
    "boundingBoxY1",
    "boundingBoxY2",
    "id",
    "imageHeight",
    "imageWidth"
  ],
  "title": "AssetFaceWithoutPersonResponseDto",
  "type": "object"
}

Config:

  • populate_by_name: True
  • validate_assignment: True
  • protected_namespaces: ()

Fields:

bounding_box_x1 pydantic-field 

bounding_box_x1: StrictInt

Bounding box X1 coordinate

bounding_box_x2 pydantic-field 

bounding_box_x2: StrictInt

Bounding box X2 coordinate

bounding_box_y1 pydantic-field 

bounding_box_y1: StrictInt

Bounding box Y1 coordinate

bounding_box_y2 pydantic-field 

bounding_box_y2: StrictInt

Bounding box Y2 coordinate

id pydantic-field 

id: UUID

Face ID

image_height pydantic-field 

image_height: StrictInt

Image height in pixels

image_width pydantic-field 

image_width: StrictInt

Image width in pixels

source_type pydantic-field 

source_type: Optional[SourceType] = None

Face detection source type

from_dict classmethod 

from_dict(obj: Optional[Dict[str, Any]]) -> Optional[Self]

Create an instance of AssetFaceWithoutPersonResponseDto from a dict

Source code in immichpy/client/generated/models/asset_face_without_person_response_dto.py 
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@classmethod
def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
    """Create an instance of AssetFaceWithoutPersonResponseDto from a dict"""
    if obj is None:
        return None

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

    _obj = cls.model_validate(
        {
            "boundingBoxX1": obj.get("boundingBoxX1"),
            "boundingBoxX2": obj.get("boundingBoxX2"),
            "boundingBoxY1": obj.get("boundingBoxY1"),
            "boundingBoxY2": obj.get("boundingBoxY2"),
            "id": obj.get("id"),
            "imageHeight": obj.get("imageHeight"),
            "imageWidth": obj.get("imageWidth"),
            "sourceType": obj.get("sourceType"),
        }
    )
    return _obj

from_json classmethod 

from_json(json_str: str) -> Optional[Self]

Create an instance of AssetFaceWithoutPersonResponseDto from a JSON string

Source code in immichpy/client/generated/models/asset_face_without_person_response_dto.py 
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@classmethod
def from_json(cls, json_str: str) -> Optional[Self]:
    """Create an instance of AssetFaceWithoutPersonResponseDto from a JSON string"""
    return cls.from_dict(json.loads(json_str))

to_dict 

to_dict() -> 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.
Source code in immichpy/client/generated/models/asset_face_without_person_response_dto.py 
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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

to_json 

to_json() -> str

Returns the JSON representation of the model using alias

Source code in immichpy/client/generated/models/asset_face_without_person_response_dto.py 
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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())

to_str 

to_str() -> str

Returns the string representation of the model using alias

Source code in immichpy/client/generated/models/asset_face_without_person_response_dto.py 
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def to_str(self) -> str:
    """Returns the string representation of the model using alias"""
    return pprint.pformat(self.model_dump(by_alias=True))