source code 浏览git 
from typing import Type, Dict, Optional, List, Tuple, Any, Union
from pydantic import BaseModel, confloat


class PredictionValue(BaseModel):
    """ """

    model_version: Optional[Any] = None
    score: Optional[float] = 0.00
    result: Optional[List[Any]] = []
    # cluster: Optional[Any] = None
    # neighbors: Optional[Any] = None

    def serialize(self):
        from label_studio_sdk.label_interface.region import Region

        return {
            "model_version": self.model_version,
            "score": self.score,
            "result": [r._dict() if isinstance(r, Region) else r for r in self.result],
        }


class AnnotationValue(BaseModel):
    """ """

    result: Optional[List[dict]]


class TaskValue(BaseModel):
    """ """

    data: Optional[dict]
    annotations: Optional[List[AnnotationValue]]
    predictions: Optional[List[PredictionValue]]

类

class AnnotationValue (**data: Any)

通过解析和验证来自关键字参数的输入数据来创建新模型。

如果输入数据无法验证为有效模型，则引发 [ValidationError][pydantic_core.ValidationError]。

self 被显式声明为仅限位置参数，以允许将 self 用作字段名称。

source code 浏览git 
class AnnotationValue(BaseModel):
    """ """

    result: Optional[List[dict]]

常量

model_computed_fields
model_config
model_fields
result : Optional[List[dict]]
class PredictionValue (**data: Any)

通过解析和验证来自关键字参数的输入数据来创建新模型。

如果输入数据无法验证为有效模型，则引发 [ValidationError][pydantic_core.ValidationError]。

self 被显式声明为仅限位置参数，以允许将 self 用作字段名。

source code 浏览Git 
class PredictionValue(BaseModel):
    """ """

    model_version: Optional[Any] = None
    score: Optional[float] = 0.00
    result: Optional[List[Any]] = []
    # cluster: Optional[Any] = None
    # neighbors: Optional[Any] = None

    def serialize(self):
        from label_studio_sdk.label_interface.region import Region

        return {
            "model_version": self.model_version,
            "score": self.score,
            "result": [r._dict() if isinstance(r, Region) else r for r in self.result],
        }

常量

model_computed_fields
model_config
model_fields
model_version : Optional[Any]
result : Optional[List[Any]]
score : Optional[float]

方法

def serialize(self)
source code 浏览git 
def serialize(self):
    from label_studio_sdk.label_interface.region import Region

    return {
        "model_version": self.model_version,
        "score": self.score,
        "result": [r._dict() if isinstance(r, Region) else r for r in self.result],
    }
class TaskValue (**data: Any)

通过解析和验证来自关键字参数的输入数据来创建新模型。

如果输入数据无法验证为有效模型，则引发[ValidationError][pydantic_core.ValidationError]。

self 被显式声明为仅限位置参数，以允许将 self 用作字段名称。

source code 浏览git 
class TaskValue(BaseModel):
    """ """

    data: Optional[dict]
    annotations: Optional[List[AnnotationValue]]
    predictions: Optional[List[PredictionValue]]

常量

annotations : Optional[List[AnnotationValue]]
data : Optional[dict]
model_computed_fields
model_config
model_fields
predictions : Optional[List[PredictionValue]]