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pythondatasetsactive-learningtext-annotationdatasetnatural-language-processingdata-labelingmachine-learningannotation-tool
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95 lines
2.2 KiB
95 lines
2.2 KiB
<template>
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<v-main>
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<v-container fluid>
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<v-row justify="center">
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<v-col cols="12" md="9">
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<v-card>
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<v-card-title>
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<label-group
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:labels="items"
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:annotations="currentDoc.annotations"
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:single-label="singleLabel"
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@add="addLabel"
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@remove="removeLabel"
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/>
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</v-card-title>
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<v-divider />
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<v-img contain :src="currentDoc.filename" max-height="300" class="grey lighten-2" />
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</v-card>
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</v-col>
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<v-col cols="12" md="3">
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<list-metadata :metadata="currentDoc.meta" />
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</v-col>
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</v-row>
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</v-container>
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</v-main>
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</template>
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<script>
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import ListMetadata from '@/components/tasks/metadata/ListMetadata'
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import LabelGroup from '@/components/tasks/textClassification/LabelGroup'
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export default {
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components: {
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LabelGroup,
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ListMetadata
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},
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layout: 'demo',
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data() {
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return {
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items: [
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{
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id: 4,
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text: 'Cat',
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prefixKey: null,
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suffixKey: 'c',
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backgroundColor: '#7c20e0',
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textColor: '#ffffff'
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},
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{
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id: 5,
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text: 'Dog',
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prefixKey: null,
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suffixKey: 'd',
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backgroundColor: '#fbb028',
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textColor: '#000000'
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}
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],
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singleLabel: true,
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currentDoc: {
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id: 8,
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filename: require('~/assets/6737785.png'),
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annotations: [
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{
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id: 17,
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prob: 0.0,
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label: 4,
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user: 1,
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document: 8
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}
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],
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meta: {
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url: 'https://github.com/Hironsan'
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},
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annotation_approver: null
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}
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}
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},
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methods: {
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removeLabel(annotationId) {
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this.currentDoc.annotations = this.currentDoc.annotations.filter(
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(item) => item.id !== annotationId
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)
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},
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addLabel(labelId) {
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const payload = {
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id: Math.floor(Math.random() * Math.floor(Number.MAX_SAFE_INTEGER)),
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label: labelId
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}
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this.currentDoc.annotations.push(payload)
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}
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}
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}
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</script>
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