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pythondatasetsactive-learningtext-annotationdatasetnatural-language-processingdata-labelingmachine-learningannotation-tool
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143 lines
4.0 KiB
143 lines
4.0 KiB
from rest_framework import serializers
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from rest_polymorphic.serializers import PolymorphicSerializer
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from .models import (Comment, Example, ExampleState,
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ImageClassificationProject,
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IntentDetectionAndSlotFillingProject, Project,
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Seq2seqProject, SequenceLabelingProject,
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Speech2textProject, Tag, TextClassificationProject)
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class CommentSerializer(serializers.ModelSerializer):
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class Meta:
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model = Comment
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fields = ('id', 'user', 'username', 'example', 'text', 'created_at', )
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read_only_fields = ('user', 'example')
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class TagSerializer(serializers.ModelSerializer):
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class Meta:
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model = Tag
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fields = ('id', 'project', 'text', )
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read_only_fields = ('id', 'project')
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class ExampleSerializer(serializers.ModelSerializer):
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annotation_approver = serializers.SerializerMethodField()
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is_confirmed = serializers.SerializerMethodField()
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@classmethod
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def get_annotation_approver(cls, instance):
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approver = instance.annotations_approved_by
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return approver.username if approver else None
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def get_is_confirmed(self, instance):
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user = self.context.get('request').user
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if instance.project.collaborative_annotation:
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states = instance.states.all()
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else:
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states = instance.states.filter(confirmed_by_id=user.id)
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return states.count() > 0
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class Meta:
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model = Example
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fields = [
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'id',
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'filename',
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'meta',
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'annotation_approver',
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'comment_count',
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'text',
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'is_confirmed'
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]
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read_only_fields = ['filename', 'is_confirmed']
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class ExampleStateSerializer(serializers.ModelSerializer):
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class Meta:
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model = ExampleState
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fields = ('id', 'example', 'confirmed_by')
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read_only_fields = ('id', 'example', 'confirmed_by')
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class ProjectSerializer(serializers.ModelSerializer):
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tags = TagSerializer(many=True, required=False)
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class Meta:
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model = Project
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fields = (
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'id',
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'name',
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'description',
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'guideline',
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'project_type',
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'updated_at',
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'random_order',
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'created_by',
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'collaborative_annotation',
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'single_class_classification',
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'is_text_project',
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'can_define_label',
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'can_define_relation',
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'can_define_category',
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'can_define_span',
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'tags'
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)
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read_only_fields = (
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'updated_at',
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'is_text_project',
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'can_define_label',
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'can_define_relation',
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'can_define_category',
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'can_define_span',
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'tags'
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)
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class TextClassificationProjectSerializer(ProjectSerializer):
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class Meta(ProjectSerializer.Meta):
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model = TextClassificationProject
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class SequenceLabelingProjectSerializer(ProjectSerializer):
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class Meta(ProjectSerializer.Meta):
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model = SequenceLabelingProject
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fields = ProjectSerializer.Meta.fields + ('allow_overlapping', 'grapheme_mode')
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class Seq2seqProjectSerializer(ProjectSerializer):
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class Meta(ProjectSerializer.Meta):
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model = Seq2seqProject
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class IntentDetectionAndSlotFillingProjectSerializer(ProjectSerializer):
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class Meta(ProjectSerializer.Meta):
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model = IntentDetectionAndSlotFillingProject
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class Speech2textProjectSerializer(ProjectSerializer):
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class Meta(ProjectSerializer.Meta):
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model = Speech2textProject
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class ImageClassificationProjectSerializer(ProjectSerializer):
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class Meta(ProjectSerializer.Meta):
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model = ImageClassificationProject
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class ProjectPolymorphicSerializer(PolymorphicSerializer):
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model_serializer_mapping = {
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Project: ProjectSerializer,
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**{
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cls.Meta.model: cls for cls in ProjectSerializer.__subclasses__()
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}
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}
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