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Asset Ocr Response Dto

immichpy.client.generated.models.asset_ocr_response_dto.AssetOcrResponseDto pydantic-model

Bases: BaseModel

AssetOcrResponseDto

Show JSON schema: 
{
  "description": "AssetOcrResponseDto",
  "properties": {
    "assetId": {
      "format": "uuid",
      "title": "Assetid",
      "type": "string"
    },
    "boxScore": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "integer"
        }
      ],
      "description": "Confidence score for text detection box",
      "title": "Boxscore"
    },
    "id": {
      "format": "uuid",
      "title": "Id",
      "type": "string"
    },
    "text": {
      "description": "Recognized text",
      "title": "Text",
      "type": "string"
    },
    "textScore": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "integer"
        }
      ],
      "description": "Confidence score for text recognition",
      "title": "Textscore"
    },
    "x1": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "integer"
        }
      ],
      "description": "Normalized x coordinate of box corner 1 (0-1)",
      "title": "X1"
    },
    "x2": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "integer"
        }
      ],
      "description": "Normalized x coordinate of box corner 2 (0-1)",
      "title": "X2"
    },
    "x3": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "integer"
        }
      ],
      "description": "Normalized x coordinate of box corner 3 (0-1)",
      "title": "X3"
    },
    "x4": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "integer"
        }
      ],
      "description": "Normalized x coordinate of box corner 4 (0-1)",
      "title": "X4"
    },
    "y1": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "integer"
        }
      ],
      "description": "Normalized y coordinate of box corner 1 (0-1)",
      "title": "Y1"
    },
    "y2": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "integer"
        }
      ],
      "description": "Normalized y coordinate of box corner 2 (0-1)",
      "title": "Y2"
    },
    "y3": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "integer"
        }
      ],
      "description": "Normalized y coordinate of box corner 3 (0-1)",
      "title": "Y3"
    },
    "y4": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "integer"
        }
      ],
      "description": "Normalized y coordinate of box corner 4 (0-1)",
      "title": "Y4"
    }
  },
  "required": [
    "assetId",
    "boxScore",
    "id",
    "text",
    "textScore",
    "x1",
    "x2",
    "x3",
    "x4",
    "y1",
    "y2",
    "y3",
    "y4"
  ],
  "title": "AssetOcrResponseDto",
  "type": "object"
}

Config:

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

Fields:

box_score pydantic-field 

box_score: Union[StrictFloat, StrictInt]

Confidence score for text detection box

text pydantic-field 

text: StrictStr

Recognized text

text_score pydantic-field 

text_score: Union[StrictFloat, StrictInt]

Confidence score for text recognition

x1 pydantic-field 

x1: Union[StrictFloat, StrictInt]

Normalized x coordinate of box corner 1 (0-1)

x2 pydantic-field 

x2: Union[StrictFloat, StrictInt]

Normalized x coordinate of box corner 2 (0-1)

x3 pydantic-field 

x3: Union[StrictFloat, StrictInt]

Normalized x coordinate of box corner 3 (0-1)

x4 pydantic-field 

x4: Union[StrictFloat, StrictInt]

Normalized x coordinate of box corner 4 (0-1)

y1 pydantic-field 

y1: Union[StrictFloat, StrictInt]

Normalized y coordinate of box corner 1 (0-1)

y2 pydantic-field 

y2: Union[StrictFloat, StrictInt]

Normalized y coordinate of box corner 2 (0-1)

y3 pydantic-field 

y3: Union[StrictFloat, StrictInt]

Normalized y coordinate of box corner 3 (0-1)

y4 pydantic-field 

y4: Union[StrictFloat, StrictInt]

Normalized y coordinate of box corner 4 (0-1)

from_dict classmethod 

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

Create an instance of AssetOcrResponseDto from a dict

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

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

    _obj = cls.model_validate(
        {
            "assetId": obj.get("assetId"),
            "boxScore": obj.get("boxScore"),
            "id": obj.get("id"),
            "text": obj.get("text"),
            "textScore": obj.get("textScore"),
            "x1": obj.get("x1"),
            "x2": obj.get("x2"),
            "x3": obj.get("x3"),
            "x4": obj.get("x4"),
            "y1": obj.get("y1"),
            "y2": obj.get("y2"),
            "y3": obj.get("y3"),
            "y4": obj.get("y4"),
        }
    )
    return _obj

from_json classmethod 

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

Create an instance of AssetOcrResponseDto from a JSON string

Source code in immichpy/client/generated/models/asset_ocr_response_dto.py 
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@classmethod
def from_json(cls, json_str: str) -> Optional[Self]:
    """Create an instance of AssetOcrResponseDto 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_ocr_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_ocr_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_ocr_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))