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pythondatasetsactive-learningtext-annotationdatasetnatural-language-processingdata-labelingmachine-learningannotation-tool
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128 lines
3.3 KiB
128 lines
3.3 KiB
import abc
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from typing import Any, Dict, Optional
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from pydantic import BaseModel, validator
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from label_types.models import CategoryType, LabelType, SpanType
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from labels.models import Category, Span
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from labels.models import TextLabel as TL
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from projects.models import Project
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class Label(BaseModel, abc.ABC):
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@abc.abstractmethod
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def has_name(self) -> bool:
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raise NotImplementedError()
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@property
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@abc.abstractmethod
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def name(self) -> str:
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raise NotImplementedError()
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@classmethod
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def parse(cls, obj: Any):
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raise NotImplementedError()
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@abc.abstractmethod
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def create(self, project: Project) -> Optional[LabelType]:
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raise NotImplementedError()
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@abc.abstractmethod
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def create_annotation(self, user, example, mapping):
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raise NotImplementedError
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def __hash__(self):
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return hash(tuple(self.dict()))
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class CategoryLabel(Label):
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label: str
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@validator("label")
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def label_is_not_empty(cls, value: str):
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if value:
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return value
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else:
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raise ValueError("is not empty.")
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def has_name(self) -> bool:
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return True
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@property
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def name(self) -> str:
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return self.label
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@classmethod
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def parse(cls, obj: Any):
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if isinstance(obj, str):
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return cls(label=obj)
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elif isinstance(obj, int):
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return cls(label=str(obj))
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else:
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raise TypeError(f"{obj} is not str.")
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def create(self, project: Project) -> Optional[LabelType]:
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return CategoryType(text=self.label, project=project)
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def create_annotation(self, user, example, mapping: Dict[str, LabelType]):
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return Category(user=user, example=example, label=mapping[self.label])
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class SpanLabel(Label):
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label: str
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start_offset: int
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end_offset: int
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def has_name(self) -> bool:
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return True
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@property
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def name(self) -> str:
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return self.label
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@classmethod
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def parse(cls, obj: Any):
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if isinstance(obj, list) or isinstance(obj, tuple):
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columns = ["start_offset", "end_offset", "label"]
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obj = zip(columns, obj)
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return cls.parse_obj(obj)
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elif isinstance(obj, dict):
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return cls.parse_obj(obj)
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else:
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raise TypeError(f"{obj} is invalid type.")
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def create(self, project: Project) -> Optional[LabelType]:
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return SpanType(text=self.label, project=project)
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def create_annotation(self, user, example, mapping: Dict[str, LabelType]):
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return Span(
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user=user,
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example=example,
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start_offset=self.start_offset,
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end_offset=self.end_offset,
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label=mapping[self.label],
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)
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class TextLabel(Label):
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text: str
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def has_name(self) -> bool:
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return False
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@property
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def name(self) -> str:
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return self.text
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@classmethod
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def parse(cls, obj: Any):
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if isinstance(obj, str) and obj:
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return cls(text=obj)
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else:
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raise TypeError(f"{obj} is not str or empty.")
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def create(self, project: Project) -> Optional[LabelType]:
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return None
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def create_annotation(self, user, example, mapping):
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return TL(user=user, example=example, text=self.text)
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