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pythondatasetsactive-learningtext-annotationdatasetnatural-language-processingdata-labelingmachine-learningannotation-tool
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72 lines
1.7 KiB
72 lines
1.7 KiB
"""
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Represents label collection.
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"""
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import abc
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from collections import defaultdict
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from typing import Dict, List, Tuple
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from django.db.models import QuerySet
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from data_export.models import (
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ExportedBoundingBox,
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ExportedCategory,
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ExportedExample,
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ExportedLabel,
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ExportedRelation,
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ExportedSegmentation,
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ExportedSpan,
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ExportedText,
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)
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class Labels(abc.ABC):
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label_class = ExportedLabel
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column = "labels"
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fields: Tuple[str, ...] = ("example", "label") # To boost performance
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def __init__(self, examples: QuerySet[ExportedExample], user=None):
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self.label_groups = defaultdict(list)
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labels = self.label_class.objects.filter(example__in=examples)
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if user:
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labels = labels.filter(user=user)
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for label in labels.select_related(*self.fields):
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self.label_groups[label.example.id].append(label)
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def find_by(self, example_id: int) -> Dict[str, List[ExportedLabel]]:
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return {self.column: self.label_groups[example_id]}
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class Categories(Labels):
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label_class = ExportedCategory
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column = "categories"
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fields = ("example", "label")
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class Spans(Labels):
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label_class = ExportedSpan
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column = "entities"
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fields = ("example", "label")
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class Relations(Labels):
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label_class = ExportedRelation
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column = "relations"
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fields = ("example", "type")
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class Texts(Labels):
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label_class = ExportedText
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column = "labels"
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fields = ("example",)
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class BoundingBoxes(Labels):
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label_class = ExportedBoundingBox
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column = "labels"
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fields = ("example", "label")
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class Segments(Labels):
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label_class = ExportedSegmentation
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column = "labels"
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fields = ("example", "label")
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