diff --git a/frontend/src/pages/DataAnnotation/Create/CreateTask.tsx b/frontend/src/pages/DataAnnotation/Create/CreateTask.tsx
index 06f626d..81b5348 100644
--- a/frontend/src/pages/DataAnnotation/Create/CreateTask.tsx
+++ b/frontend/src/pages/DataAnnotation/Create/CreateTask.tsx
@@ -12,7 +12,7 @@ import {
createAnnotationTaskUsingPost,
queryAnnotationTemplatesUsingGet,
} from "../annotation.api";
-import type { AnnotationTemplate } from "../annotation.model";
+import { DataType, type AnnotationTemplate } from "../annotation.model";
import TemplateConfigurationTreeEditor from "../components/TemplateConfigurationTreeEditor";
const DEFAULT_SEGMENTATION_ENABLED = true;
@@ -20,6 +20,22 @@ const SEGMENTATION_OPTIONS = [
{ label: "需要切片段", value: true },
{ label: "不需要切片段", value: false },
];
+const resolveTemplateDataType = (datasetType?: DatasetType) => {
+ switch (datasetType) {
+ case DatasetType.TEXT:
+ return DataType.TEXT;
+ case DatasetType.IMAGE:
+ return DataType.IMAGE;
+ case DatasetType.AUDIO:
+ return DataType.AUDIO;
+ case DatasetType.VIDEO:
+ return DataType.VIDEO;
+ default:
+ return undefined;
+ }
+};
+const resolveDefaultTemplate = (items: AnnotationTemplate[]) =>
+ items.find((template) => template.builtIn) || items[0];
export default function AnnotationTaskCreate() {
const navigate = useNavigate();
@@ -48,9 +64,17 @@ export default function AnnotationTaskCreate() {
}
};
- const fetchTemplates = async () => {
+ const fetchTemplates = async (dataType?: string) => {
+ if (!dataType) {
+ setTemplates([]);
+ return;
+ }
try {
- const response = await queryAnnotationTemplatesUsingGet({ page: 1, size: 200 });
+ const response = await queryAnnotationTemplatesUsingGet({
+ page: 1,
+ size: 200,
+ dataType,
+ });
if (response.code === 200 && response.data) {
setTemplates(response.data.content || []);
} else {
@@ -64,9 +88,39 @@ export default function AnnotationTaskCreate() {
useEffect(() => {
fetchDatasets();
- fetchTemplates();
}, []);
+ useEffect(() => {
+ if (!selectedDataset) {
+ setTemplates([]);
+ form.setFieldsValue({ templateId: undefined });
+ setLabelConfig("");
+ return;
+ }
+ const dataType = resolveTemplateDataType(selectedDataset.datasetType);
+ fetchTemplates(dataType);
+ }, [form, selectedDataset]);
+
+ useEffect(() => {
+ if (configMode !== "template" || !selectedDataset) {
+ return;
+ }
+ if (templates.length === 0) {
+ form.setFieldsValue({ templateId: undefined });
+ setLabelConfig("");
+ return;
+ }
+ const currentTemplateId = form.getFieldValue("templateId");
+ const currentTemplate = templates.find((template) => template.id === currentTemplateId);
+ if (currentTemplate) {
+ return;
+ }
+ const defaultTemplate = resolveDefaultTemplate(templates);
+ if (defaultTemplate) {
+ form.setFieldsValue({ templateId: defaultTemplate.id });
+ setLabelConfig(defaultTemplate.labelConfig || "");
+ }
+ }, [configMode, form, selectedDataset, templates]);
const handleTemplateSelect = (value?: string) => {
if (!value) {
setLabelConfig("");
@@ -171,6 +225,8 @@ export default function AnnotationTaskCreate() {
}))}
onChange={(value) => {
setSelectedDatasetId(value);
+ form.setFieldsValue({ templateId: undefined });
+ setLabelConfig("");
const dataset = datasets.find((item) => item.id === value);
if (dataset?.datasetType === DatasetType.TEXT) {
const currentValue = form.getFieldValue("segmentationEnabled");
diff --git a/frontend/src/pages/DataAnnotation/Create/components/CreateAnnotationTaskDialog.tsx b/frontend/src/pages/DataAnnotation/Create/components/CreateAnnotationTaskDialog.tsx
index 2498617..d993971 100644
--- a/frontend/src/pages/DataAnnotation/Create/components/CreateAnnotationTaskDialog.tsx
+++ b/frontend/src/pages/DataAnnotation/Create/components/CreateAnnotationTaskDialog.tsx
@@ -13,7 +13,7 @@ import {
queryAnnotationTemplatesUsingGet,
} from "../../annotation.api";
import { DatasetType, type Dataset } from "@/pages/DataManagement/dataset.model";
-import type { AnnotationTemplate, AnnotationTask } from "../../annotation.model";
+import { DataType, type AnnotationTemplate, type AnnotationTask } from "../../annotation.model";
import LabelStudioEmbed from "@/components/business/LabelStudioEmbed";
import TemplateConfigurationTreeEditor from "../../components/TemplateConfigurationTreeEditor";
import { useTagConfig } from "@/hooks/useTagConfig";
@@ -57,6 +57,22 @@ const SEGMENTATION_OPTIONS = [
{ label: "需要切片段", value: true },
{ label: "不需要切片段", value: false },
];
+const resolveTemplateDataType = (datasetType?: DatasetType) => {
+ switch (datasetType) {
+ case DatasetType.TEXT:
+ return DataType.TEXT;
+ case DatasetType.IMAGE:
+ return DataType.IMAGE;
+ case DatasetType.AUDIO:
+ return DataType.AUDIO;
+ case DatasetType.VIDEO:
+ return DataType.VIDEO;
+ default:
+ return undefined;
+ }
+};
+const resolveDefaultTemplate = (items: AnnotationTemplate[]) =>
+ items.find((template) => template.builtIn) || items[0];
export default function CreateAnnotationTask({
open,
@@ -112,19 +128,6 @@ export default function CreateAnnotationTask({
});
setDatasets(datasetData.content.map(mapDataset) || []);
- // Fetch templates
- const templateResponse = await queryAnnotationTemplatesUsingGet({
- page: 1,
- size: 100,
- });
-
- if (templateResponse.code === 200 && templateResponse.data) {
- const fetchedTemplates = templateResponse.data.content || [];
- setTemplates(fetchedTemplates);
- } else {
- console.error("Failed to fetch templates:", templateResponse);
- setTemplates([]);
- }
} catch (error) {
console.error("Error fetching data:", error);
setTemplates([]);
@@ -133,6 +136,66 @@ export default function CreateAnnotationTask({
fetchData();
}, [open]);
+ const fetchTemplates = async (dataType?: string) => {
+ if (!dataType) {
+ setTemplates([]);
+ return;
+ }
+ try {
+ const templateResponse = await queryAnnotationTemplatesUsingGet({
+ page: 1,
+ size: 200,
+ dataType,
+ });
+
+ if (templateResponse.code === 200 && templateResponse.data) {
+ const fetchedTemplates = templateResponse.data.content || [];
+ setTemplates(fetchedTemplates);
+ } else {
+ console.error("Failed to fetch templates:", templateResponse);
+ setTemplates([]);
+ }
+ } catch (error) {
+ console.error("Error fetching templates:", error);
+ setTemplates([]);
+ }
+ };
+
+ useEffect(() => {
+ if (!open || isEditMode) {
+ return;
+ }
+ if (!selectedDataset) {
+ setTemplates([]);
+ manualForm.setFieldsValue({ templateId: undefined });
+ setLabelConfig("");
+ return;
+ }
+ const dataType = resolveTemplateDataType(selectedDataset.datasetType);
+ fetchTemplates(dataType);
+ }, [isEditMode, manualForm, open, selectedDataset]);
+
+ useEffect(() => {
+ if (!open || isEditMode || configMode !== "template" || !selectedDataset) {
+ return;
+ }
+ if (templates.length === 0) {
+ manualForm.setFieldsValue({ templateId: undefined });
+ setLabelConfig("");
+ return;
+ }
+ const currentTemplateId = manualForm.getFieldValue("templateId");
+ const currentTemplate = templates.find((template) => template.id === currentTemplateId);
+ if (currentTemplate) {
+ return;
+ }
+ const defaultTemplate = resolveDefaultTemplate(templates);
+ if (defaultTemplate) {
+ manualForm.setFieldsValue({ templateId: defaultTemplate.id });
+ setLabelConfig(defaultTemplate.labelConfig || "");
+ }
+ }, [configMode, isEditMode, manualForm, open, selectedDataset, templates]);
+
// Reset form and manual-edit flag when modal opens, or load task data in edit mode
useEffect(() => {
if (open) {
@@ -587,6 +650,10 @@ export default function CreateAnnotationTask({
})}
onChange={(value) => {
setSelectedDatasetId(value);
+ if (!isEditMode) {
+ manualForm.setFieldsValue({ templateId: undefined });
+ setLabelConfig("");
+ }
const dataset = datasets.find((item) => item.id === value);
if (dataset?.datasetType === DatasetType.TEXT) {
const currentValue = manualForm.getFieldValue("segmentationEnabled");
diff --git a/runtime/datamate-python/app/module/annotation/service/builtin_templates.py b/runtime/datamate-python/app/module/annotation/service/builtin_templates.py
index 7c9ec8b..02d994f 100644
--- a/runtime/datamate-python/app/module/annotation/service/builtin_templates.py
+++ b/runtime/datamate-python/app/module/annotation/service/builtin_templates.py
@@ -13,7 +13,11 @@ from app.module.annotation.utils.config_validator import LabelStudioConfigValida
logger = get_logger(__name__)
DATA_TYPE_IMAGE = "image"
+DATA_TYPE_AUDIO = "audio"
+DATA_TYPE_VIDEO = "video"
CATEGORY_COMPUTER_VISION = "computer-vision"
+CATEGORY_AUDIO_SPEECH = "audio-speech"
+CATEGORY_VIDEO = "video"
STYLE_HORIZONTAL = "horizontal"
VERSION_DEFAULT = "1.0.0"
@@ -51,6 +55,105 @@ SEMANTIC_SEGMENTATION_POLYGON_LABEL_CONFIG = """
"""
+ASR_SEGMENTS_LABEL_CONFIG = """
+
+
+
+
+ """
+
+ASR_LABEL_CONFIG = """
+
+
+
+"""
+
+CONVERSATION_ANALYSIS_LABEL_CONFIG = """
+ """
+
+INTENT_CLASSIFICATION_LABEL_CONFIG = """
+
+
+
+ """
+
+SIGNAL_QUALITY_LABEL_CONFIG = """
+
+ """
+
+SOUND_EVENT_DETECTION_LABEL_CONFIG = """
+
+
+ """
+
+SPEAKER_SEGMENTATION_LABEL_CONFIG = """
+
+
+
+"""
+
+VIDEO_CLASSIFICATION_LABEL_CONFIG = """
+ """
+
+VIDEO_OBJECT_TRACKING_LABEL_CONFIG = """
+
+
+ """
+
+VIDEO_TIMELINE_SEGMENTATION_LABEL_CONFIG = """
+ """
+
@dataclass(frozen=True)
class BuiltInTemplateDefinition:
@@ -122,6 +225,122 @@ BUILT_IN_TEMPLATES: List[BuiltInTemplateDefinition] = [
category=CATEGORY_COMPUTER_VISION,
version=VERSION_DEFAULT,
),
+ BuiltInTemplateDefinition(
+ id="tpl-asr-segments-001",
+ name="语音识别（分段）",
+ description=(
+ "对音频进行语音活动分段并转录文本，适用于呼叫中心转录、会议记录、播客转录等场景。"
+ "关联模型：Whisper、Wav2Vec2、DeepSpeech"
+ ),
+ data_type=DATA_TYPE_AUDIO,
+ labeling_type="asr-segments",
+ label_config=ASR_SEGMENTS_LABEL_CONFIG,
+ style=STYLE_HORIZONTAL,
+ category=CATEGORY_AUDIO_SPEECH,
+ version=VERSION_DEFAULT,
+ ),
+ BuiltInTemplateDefinition(
+ id="tpl-asr-001",
+ name="语音识别",
+ description=(
+ "转录音频内容，适用于播客转录、会议记录、客服通话、字幕生成等场景。"
+ "关联模型：Whisper、Wav2Vec、DeepSpeech"
+ ),
+ data_type=DATA_TYPE_AUDIO,
+ labeling_type="asr",
+ label_config=ASR_LABEL_CONFIG,
+ style=STYLE_HORIZONTAL,
+ category=CATEGORY_AUDIO_SPEECH,
+ version=VERSION_DEFAULT,
+ ),
+ BuiltInTemplateDefinition(
+ id="tpl-conversation-analysis-001",
+ name="对话分析",
+ description="分析对话语句并标注事实和情感方面，适用于呼叫中心质检、客服分析、会议分析等场景",
+ data_type=DATA_TYPE_AUDIO,
+ labeling_type="conversation-analysis",
+ label_config=CONVERSATION_ANALYSIS_LABEL_CONFIG,
+ style=STYLE_HORIZONTAL,
+ category=CATEGORY_AUDIO_SPEECH,
+ version=VERSION_DEFAULT,
+ ),
+ BuiltInTemplateDefinition(
+ id="tpl-intent-classification-001",
+ name="意图分类",
+ description="进行语音活动分段并选择语音意图，适用于语音助手、智能音箱、IVR系统等场景",
+ data_type=DATA_TYPE_AUDIO,
+ labeling_type="intent-classification",
+ label_config=INTENT_CLASSIFICATION_LABEL_CONFIG,
+ style=STYLE_HORIZONTAL,
+ category=CATEGORY_AUDIO_SPEECH,
+ version=VERSION_DEFAULT,
+ ),
+ BuiltInTemplateDefinition(
+ id="tpl-signal-quality-001",
+ name="信号质量检测",
+ description="评估音频信号质量，适用于电信、呼叫中心质检、音频制作、VoIP质量评估等场景",
+ data_type=DATA_TYPE_AUDIO,
+ labeling_type="signal-quality",
+ label_config=SIGNAL_QUALITY_LABEL_CONFIG,
+ style=STYLE_HORIZONTAL,
+ category=CATEGORY_AUDIO_SPEECH,
+ version=VERSION_DEFAULT,
+ ),
+ BuiltInTemplateDefinition(
+ id="tpl-sound-event-001",
+ name="声音事件检测",
+ description="选择音频片段并分类声音事件，适用于安防监控、智慧城市、环境监测、工业监测等场景",
+ data_type=DATA_TYPE_AUDIO,
+ labeling_type="sound-event-detection",
+ label_config=SOUND_EVENT_DETECTION_LABEL_CONFIG,
+ style=STYLE_HORIZONTAL,
+ category=CATEGORY_AUDIO_SPEECH,
+ version=VERSION_DEFAULT,
+ ),
+ BuiltInTemplateDefinition(
+ id="tpl-speaker-segmentation-001",
+ name="说话人分割",
+ description="执行说话人分割/话者分离任务，适用于会议转录、播客制作、呼叫中心分析等场景",
+ data_type=DATA_TYPE_AUDIO,
+ labeling_type="speaker-segmentation",
+ label_config=SPEAKER_SEGMENTATION_LABEL_CONFIG,
+ style=STYLE_HORIZONTAL,
+ category=CATEGORY_AUDIO_SPEECH,
+ version=VERSION_DEFAULT,
+ ),
+ BuiltInTemplateDefinition(
+ id="tpl-video-classification-001",
+ name="视频分类",
+ description="对视频进行整体分类，适用于内容审核、媒体分析、质检等场景",
+ data_type=DATA_TYPE_VIDEO,
+ labeling_type="video-classification",
+ label_config=VIDEO_CLASSIFICATION_LABEL_CONFIG,
+ style=STYLE_HORIZONTAL,
+ category=CATEGORY_VIDEO,
+ version=VERSION_DEFAULT,
+ ),
+ BuiltInTemplateDefinition(
+ id="tpl-video-object-tracking-001",
+ name="视频目标追踪",
+ description="在视频中追踪目标对象，适用于安防监控、交通分析、行为分析等场景",
+ data_type=DATA_TYPE_VIDEO,
+ labeling_type="video-object-tracking",
+ label_config=VIDEO_OBJECT_TRACKING_LABEL_CONFIG,
+ style=STYLE_HORIZONTAL,
+ category=CATEGORY_VIDEO,
+ version=VERSION_DEFAULT,
+ ),
+ BuiltInTemplateDefinition(
+ id="tpl-video-timeline-segmentation-001",
+ name="视频时间线分割",
+ description="对视频时间线进行分段标注，适用于视频剪辑、内容索引等场景",
+ data_type=DATA_TYPE_VIDEO,
+ labeling_type="video-timeline-segmentation",
+ label_config=VIDEO_TIMELINE_SEGMENTATION_LABEL_CONFIG,
+ style=STYLE_HORIZONTAL,
+ category=CATEGORY_VIDEO,
+ version=VERSION_DEFAULT,
+ ),
]
assert len({template.id for template in BUILT_IN_TEMPLATES}) == len(BUILT_IN_TEMPLATES), (
diff --git a/runtime/datamate-python/app/module/annotation/service/editor.py b/runtime/datamate-python/app/module/annotation/service/editor.py
index 2c18594..b74fb1e 100644
--- a/runtime/datamate-python/app/module/annotation/service/editor.py
+++ b/runtime/datamate-python/app/module/annotation/service/editor.py
@@ -43,6 +43,8 @@ logger = get_logger(__name__)
TEXT_DATA_KEY = "text"
IMAGE_DATA_KEY = "image"
+AUDIO_DATA_KEY = "audio"
+VIDEO_DATA_KEY = "video"
DATASET_ID_KEY = "dataset_id"
FILE_ID_KEY = "file_id"
FILE_NAME_KEY = "file_name"
@@ -53,9 +55,19 @@ SEGMENT_INDEX_KEY = "segment_index"
SEGMENT_INDEX_CAMEL_KEY = "segmentIndex"
JSONL_EXTENSION = ".jsonl"
TEXTUAL_OBJECT_CATEGORIES = {"text", "document"}
-MEDIA_OBJECT_CATEGORIES = {"image"}
+IMAGE_OBJECT_CATEGORIES = {"image"}
+MEDIA_OBJECT_CATEGORIES = {"media"}
OBJECT_NAME_HEADER_PREFIX = "dm_object_header_"
-SUPPORTED_EDITOR_DATASET_TYPES = ("TEXT", "IMAGE")
+DATASET_TYPE_TEXT = "TEXT"
+DATASET_TYPE_IMAGE = "IMAGE"
+DATASET_TYPE_AUDIO = "AUDIO"
+DATASET_TYPE_VIDEO = "VIDEO"
+SUPPORTED_EDITOR_DATASET_TYPES = (
+ DATASET_TYPE_TEXT,
+ DATASET_TYPE_IMAGE,
+ DATASET_TYPE_AUDIO,
+ DATASET_TYPE_VIDEO,
+)
SEGMENTATION_ENABLED_KEY = "segmentation_enabled"
@@ -174,21 +186,19 @@ class AnnotationEditorService:
return keys[0]
@classmethod
- def _resolve_primary_media_key(
+ def _resolve_media_value_keys(
cls,
label_config: Optional[str],
default_key: str,
categories: Optional[set[str]] = None,
- ) -> str:
+ ) -> List[str]:
if not label_config:
- return default_key
+ return [default_key]
target_categories = categories or set()
keys = cls._extract_object_value_keys_by_category(label_config, target_categories)
if not keys:
- return default_key
- if default_key in keys:
- return default_key
- return keys[0]
+ return [default_key]
+ return keys
@staticmethod
def _try_parse_json_payload(text_content: str) -> Optional[Dict[str, Any]]:
@@ -467,7 +477,10 @@ class AnnotationEditorService:
dataset_type = self._normalize_dataset_type(await self._get_dataset_type(project.dataset_id))
if dataset_type not in SUPPORTED_EDITOR_DATASET_TYPES:
- raise HTTPException(status_code=400, detail="当前仅支持 TEXT/IMAGE 项目的内嵌编辑器")
+ raise HTTPException(
+ status_code=400,
+ detail="当前仅支持 TEXT/IMAGE/AUDIO/VIDEO 项目的内嵌编辑器",
+ )
file_result = await self.db.execute(
select(DatasetFiles).where(
@@ -479,9 +492,15 @@ class AnnotationEditorService:
if not file_record:
raise HTTPException(status_code=404, detail=f"文件不存在或不属于该项目: {file_id}")
- if dataset_type == "IMAGE":
+ if dataset_type == DATASET_TYPE_IMAGE:
return await self._build_image_task(project, file_record, file_id)
+ if dataset_type == DATASET_TYPE_AUDIO:
+ return await self._build_audio_task(project, file_record, file_id)
+
+ if dataset_type == DATASET_TYPE_VIDEO:
+ return await self._build_video_task(project, file_record, file_id)
+
return await self._build_text_task(project, file_record, file_id, segment_index)
async def _build_text_task(
@@ -668,23 +687,20 @@ class AnnotationEditorService:
currentSegmentIndex=current_segment_index,
)
- async def _build_image_task(
+ async def _build_media_task(
self,
project: LabelingProject,
file_record: DatasetFiles,
file_id: str,
+ default_key: str,
+ categories: set[str],
) -> EditorTaskResponse:
label_config = await self._resolve_project_label_config(project)
- image_key = self._resolve_primary_media_key(
- label_config,
- IMAGE_DATA_KEY,
- MEDIA_OBJECT_CATEGORIES,
- )
+ media_keys = self._resolve_media_value_keys(label_config, default_key, categories)
preview_url = self._build_file_preview_url(project.dataset_id, file_id)
file_name = str(getattr(file_record, "file_name", ""))
task_data: Dict[str, Any] = {
- image_key: preview_url,
FILE_ID_KEY: file_id,
FILE_ID_CAMEL_KEY: file_id,
DATASET_ID_KEY: project.dataset_id,
@@ -692,6 +708,9 @@ class AnnotationEditorService:
FILE_NAME_KEY: file_name,
FILE_NAME_CAMEL_KEY: file_name,
}
+ for key in media_keys:
+ task_data[key] = preview_url
+ self._apply_text_placeholders(task_data, label_config)
# 获取现有标注
ann_result = await self.db.execute(
@@ -738,6 +757,48 @@ class AnnotationEditorService:
currentSegmentIndex=0,
)
+ async def _build_image_task(
+ self,
+ project: LabelingProject,
+ file_record: DatasetFiles,
+ file_id: str,
+ ) -> EditorTaskResponse:
+ return await self._build_media_task(
+ project=project,
+ file_record=file_record,
+ file_id=file_id,
+ default_key=IMAGE_DATA_KEY,
+ categories=IMAGE_OBJECT_CATEGORIES,
+ )
+
+ async def _build_audio_task(
+ self,
+ project: LabelingProject,
+ file_record: DatasetFiles,
+ file_id: str,
+ ) -> EditorTaskResponse:
+ return await self._build_media_task(
+ project=project,
+ file_record=file_record,
+ file_id=file_id,
+ default_key=AUDIO_DATA_KEY,
+ categories=MEDIA_OBJECT_CATEGORIES,
+ )
+
+ async def _build_video_task(
+ self,
+ project: LabelingProject,
+ file_record: DatasetFiles,
+ file_id: str,
+ ) -> EditorTaskResponse:
+ return await self._build_media_task(
+ project=project,
+ file_record=file_record,
+ file_id=file_id,
+ default_key=VIDEO_DATA_KEY,
+ categories=MEDIA_OBJECT_CATEGORIES,
+ )
+
async def upsert_annotation(self, project_id: str, file_id: str, request: UpsertAnnotationRequest) -> UpsertAnnotationResponse:
project = await self._get_project_or_404(project_id)
diff --git a/scripts/db/data-annotation-init.sql b/scripts/db/data-annotation-init.sql
index ae857ec..7a9e0c6 100644
--- a/scripts/db/data-annotation-init.sql
+++ b/scripts/db/data-annotation-init.sql
@@ -95,10 +95,8 @@ DELETE FROM t_dm_annotation_templates WHERE built_in = 1;
-- =============================================
-- 1. 音频/语音处理 (Audio/Speech Processing)
--- [已注释] 以下模板暂未调试完成
+-- 已启用默认模板
-- =============================================
-
-/*
-- 1.1 自动语音识别（分段）
INSERT INTO t_dm_annotation_templates (
id, name, description, data_type, labeling_type,
@@ -318,7 +316,6 @@ INSERT INTO t_dm_annotation_templates (
1,
'1.0.0'
);
-*/
-- =============================================
-- 2. 聊天评估 (Chat)
@@ -1276,10 +1273,8 @@ INSERT INTO t_dm_annotation_templates (
-- =============================================
-- 9. 视频处理 (Videos)
--- [已注释] 以下模板暂未调试完成
+-- 已启用默认模板
-- =============================================
-
-/*
-- 9.1 视频分类
INSERT INTO t_dm_annotation_templates (
id, name, description, data_type, labeling_type,
@@ -1298,7 +1293,7 @@ INSERT INTO t_dm_annotation_templates (
),
'
-
+
@@ -1323,18 +1318,18 @@ INSERT INTO t_dm_annotation_templates (
'video-object-tracking',
JSON_OBJECT(
'labels', JSON_ARRAY(
- JSON_OBJECT('fromName', 'label', 'toName', 'video', 'type', 'VideoRectangle', 'labels', JSON_ARRAY('Person', 'Car', 'Object'))
+ JSON_OBJECT('fromName', 'videoLabels', 'toName', 'video', 'type', 'Labels', 'labels', JSON_ARRAY('Man', 'Woman', 'Other'))
),
'objects', JSON_ARRAY(JSON_OBJECT('name', 'video', 'type', 'Video', 'value', '$video'))
),
'
-
-
-
-
+
+
+
+
-
-
+
+
',
'horizontal',
'video',
@@ -1354,24 +1349,28 @@ INSERT INTO t_dm_annotation_templates (
'video-timeline-segmentation',
JSON_OBJECT(
'labels', JSON_ARRAY(
- JSON_OBJECT('fromName', 'label', 'toName', 'video', 'type', 'Labels', 'labels', JSON_ARRAY('Intro', 'Content', 'Outro'))
+ JSON_OBJECT('fromName', 'tricks', 'toName', 'audio', 'type', 'Labels', 'labels', JSON_ARRAY('Intro', 'Content', 'Outro'))
),
- 'objects', JSON_ARRAY(JSON_OBJECT('name', 'video', 'type', 'Video', 'value', '$video'))
+ 'objects', JSON_ARRAY(
+ JSON_OBJECT('name', 'video', 'type', 'Video', 'value', '$video_url'),
+ JSON_OBJECT('name', 'audio', 'type', 'Audio', 'value', '$video_url')
+ )
),
'
-
-
-
-
+
+
+
+
+
+
-
+
',
'horizontal',
'video',
1,
'1.0.0'
);
-*/
-- =============================================
-- 10. 对话AI (Conversational AI)