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pythonannotation-tooldatasetsactive-learningtext-annotationdatasetnatural-language-processingdata-labelingmachine-learning
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55 lines
1.5 KiB
55 lines
1.5 KiB
from typing import List
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from projects.models import Project
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from .labels import Label, SpanLabel
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class Cleaner:
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def __init__(self, project: Project):
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pass
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def clean(self, labels: List[Label]) -> List[Label]:
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return labels
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@property
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def message(self) -> str:
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return ""
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class SpanCleaner(Cleaner):
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def __init__(self, project: Project):
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super().__init__(project)
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self.allow_overlapping = getattr(project, "allow_overlapping", False)
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def clean(self, labels: List[SpanLabel]) -> List[SpanLabel]: # type: ignore
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if self.allow_overlapping:
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return labels
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labels.sort(key=lambda label: label.start_offset)
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last_offset = -1
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new_labels = []
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for label in labels:
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if label.start_offset >= last_offset:
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last_offset = label.end_offset
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new_labels.append(label)
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return new_labels
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@property
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def message(self) -> str:
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return "This project cannot allow label overlapping. It's cleaned."
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class CategoryCleaner(Cleaner):
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def __init__(self, project: Project):
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super().__init__(project)
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self.exclusive = getattr(project, "single_class_classification", False)
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def clean(self, labels: List[Label]) -> List[Label]:
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if self.exclusive:
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return labels[:1]
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else:
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return labels
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@property
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def message(self) -> str:
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return "This project only one label can apply but multiple label found. It's cleaned."
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