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System Config Machine Learning Dto

immichpy.client.generated.models.system_config_machine_learning_dto.SystemConfigMachineLearningDto pydantic-model

Bases: BaseModel

SystemConfigMachineLearningDto

Show JSON schema: 
{
  "$defs": {
    "CLIPConfig": {
      "description": "CLIPConfig",
      "properties": {
        "enabled": {
          "description": "Whether the task is enabled",
          "title": "Enabled",
          "type": "boolean"
        },
        "modelName": {
          "description": "Name of the model to use",
          "title": "Modelname",
          "type": "string"
        }
      },
      "required": [
        "enabled",
        "modelName"
      ],
      "title": "CLIPConfig",
      "type": "object"
    },
    "DuplicateDetectionConfig": {
      "description": "DuplicateDetectionConfig",
      "properties": {
        "enabled": {
          "description": "Whether the task is enabled",
          "title": "Enabled",
          "type": "boolean"
        },
        "maxDistance": {
          "anyOf": [
            {
              "maximum": 0.1,
              "minimum": 0.001,
              "type": "number"
            },
            {
              "maximum": 0,
              "minimum": 1,
              "type": "integer"
            }
          ],
          "description": "Maximum distance threshold for duplicate detection",
          "title": "Maxdistance"
        }
      },
      "required": [
        "enabled",
        "maxDistance"
      ],
      "title": "DuplicateDetectionConfig",
      "type": "object"
    },
    "FacialRecognitionConfig": {
      "description": "FacialRecognitionConfig",
      "properties": {
        "enabled": {
          "description": "Whether the task is enabled",
          "title": "Enabled",
          "type": "boolean"
        },
        "maxDistance": {
          "anyOf": [
            {
              "maximum": 2,
              "minimum": 0.1,
              "type": "number"
            },
            {
              "maximum": 2,
              "minimum": 1,
              "type": "integer"
            }
          ],
          "description": "Maximum distance threshold for face recognition",
          "title": "Maxdistance"
        },
        "minFaces": {
          "description": "Minimum number of faces required for recognition",
          "minimum": 1,
          "title": "Minfaces",
          "type": "integer"
        },
        "minScore": {
          "anyOf": [
            {
              "maximum": 1,
              "minimum": 0.1,
              "type": "number"
            },
            {
              "maximum": 1,
              "minimum": 1,
              "type": "integer"
            }
          ],
          "description": "Minimum confidence score for face detection",
          "title": "Minscore"
        },
        "modelName": {
          "description": "Name of the model to use",
          "title": "Modelname",
          "type": "string"
        }
      },
      "required": [
        "enabled",
        "maxDistance",
        "minFaces",
        "minScore",
        "modelName"
      ],
      "title": "FacialRecognitionConfig",
      "type": "object"
    },
    "MachineLearningAvailabilityChecksDto": {
      "description": "MachineLearningAvailabilityChecksDto",
      "properties": {
        "enabled": {
          "description": "Enabled",
          "title": "Enabled",
          "type": "boolean"
        },
        "interval": {
          "anyOf": [
            {
              "type": "number"
            },
            {
              "type": "integer"
            }
          ],
          "title": "Interval"
        },
        "timeout": {
          "anyOf": [
            {
              "type": "number"
            },
            {
              "type": "integer"
            }
          ],
          "title": "Timeout"
        }
      },
      "required": [
        "enabled",
        "interval",
        "timeout"
      ],
      "title": "MachineLearningAvailabilityChecksDto",
      "type": "object"
    },
    "OcrConfig": {
      "description": "OcrConfig",
      "properties": {
        "enabled": {
          "description": "Whether the task is enabled",
          "title": "Enabled",
          "type": "boolean"
        },
        "maxResolution": {
          "description": "Maximum resolution for OCR processing",
          "minimum": 1,
          "title": "Maxresolution",
          "type": "integer"
        },
        "minDetectionScore": {
          "anyOf": [
            {
              "maximum": 1,
              "minimum": 0.1,
              "type": "number"
            },
            {
              "maximum": 1,
              "minimum": 1,
              "type": "integer"
            }
          ],
          "description": "Minimum confidence score for text detection",
          "title": "Mindetectionscore"
        },
        "minRecognitionScore": {
          "anyOf": [
            {
              "maximum": 1,
              "minimum": 0.1,
              "type": "number"
            },
            {
              "maximum": 1,
              "minimum": 1,
              "type": "integer"
            }
          ],
          "description": "Minimum confidence score for text recognition",
          "title": "Minrecognitionscore"
        },
        "modelName": {
          "description": "Name of the model to use",
          "title": "Modelname",
          "type": "string"
        }
      },
      "required": [
        "enabled",
        "maxResolution",
        "minDetectionScore",
        "minRecognitionScore",
        "modelName"
      ],
      "title": "OcrConfig",
      "type": "object"
    }
  },
  "description": "SystemConfigMachineLearningDto",
  "properties": {
    "availabilityChecks": {
      "$ref": "#/$defs/MachineLearningAvailabilityChecksDto"
    },
    "clip": {
      "$ref": "#/$defs/CLIPConfig"
    },
    "duplicateDetection": {
      "$ref": "#/$defs/DuplicateDetectionConfig"
    },
    "enabled": {
      "description": "Enabled",
      "title": "Enabled",
      "type": "boolean"
    },
    "facialRecognition": {
      "$ref": "#/$defs/FacialRecognitionConfig"
    },
    "ocr": {
      "$ref": "#/$defs/OcrConfig"
    },
    "urls": {
      "items": {
        "type": "string"
      },
      "minItems": 1,
      "title": "Urls",
      "type": "array"
    }
  },
  "required": [
    "availabilityChecks",
    "clip",
    "duplicateDetection",
    "enabled",
    "facialRecognition",
    "ocr",
    "urls"
  ],
  "title": "SystemConfigMachineLearningDto",
  "type": "object"
}

Config:

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

Fields:

enabled pydantic-field 

enabled: StrictBool

Enabled

from_dict classmethod 

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

Create an instance of SystemConfigMachineLearningDto from a dict

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

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

    _obj = cls.model_validate(
        {
            "availabilityChecks": MachineLearningAvailabilityChecksDto.from_dict(
                obj["availabilityChecks"]
            )
            if obj.get("availabilityChecks") is not None
            else None,
            "clip": CLIPConfig.from_dict(obj["clip"])
            if obj.get("clip") is not None
            else None,
            "duplicateDetection": DuplicateDetectionConfig.from_dict(
                obj["duplicateDetection"]
            )
            if obj.get("duplicateDetection") is not None
            else None,
            "enabled": obj.get("enabled"),
            "facialRecognition": FacialRecognitionConfig.from_dict(
                obj["facialRecognition"]
            )
            if obj.get("facialRecognition") is not None
            else None,
            "ocr": OcrConfig.from_dict(obj["ocr"])
            if obj.get("ocr") is not None
            else None,
            "urls": obj.get("urls"),
        }
    )
    return _obj

from_json classmethod 

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

Create an instance of SystemConfigMachineLearningDto from a JSON string

Source code in immichpy/client/generated/models/system_config_machine_learning_dto.py 
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@classmethod
def from_json(cls, json_str: str) -> Optional[Self]:
    """Create an instance of SystemConfigMachineLearningDto 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/system_config_machine_learning_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,
    )
    # override the default output from pydantic by calling `to_dict()` of availability_checks
    if self.availability_checks:
        _dict["availabilityChecks"] = self.availability_checks.to_dict()
    # override the default output from pydantic by calling `to_dict()` of clip
    if self.clip:
        _dict["clip"] = self.clip.to_dict()
    # override the default output from pydantic by calling `to_dict()` of duplicate_detection
    if self.duplicate_detection:
        _dict["duplicateDetection"] = self.duplicate_detection.to_dict()
    # override the default output from pydantic by calling `to_dict()` of facial_recognition
    if self.facial_recognition:
        _dict["facialRecognition"] = self.facial_recognition.to_dict()
    # override the default output from pydantic by calling `to_dict()` of ocr
    if self.ocr:
        _dict["ocr"] = self.ocr.to_dict()
    return _dict

to_json 

to_json() -> str

Returns the JSON representation of the model using alias

Source code in immichpy/client/generated/models/system_config_machine_learning_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/system_config_machine_learning_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))