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feat(annotation): 支持图像数据集的内嵌标注编辑器

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- 添加文件预览接口，支持以 inline 方式预览数据集中的指定文件
- 实现图像任务构建功能，支持图像标注任务的数据结构
- 扩展标注编辑器服务以支持 TEXT 和 IMAGE 类型数据集
- 添加媒体对象分类支持，解析图像标注配置
- 实现图像文件预览 URL 构建逻辑
- 优化项目信息获取和任务响应构建流程
- 修复数据库查询中的项目 ID 引用错误
This commit is contained in:
Jerry Yan
2026-01-25 17:25:44 +08:00
parent e6d1e4763f
commit c5ace0c4cc
3 changed files with 240 additions and 49 deletions
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170
runtime/datamate-python/app/module/annotation/service/editor.py
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@@ -12,6 +12,7 @@ from __future__ import annotations
import uuid
from datetime import datetime
from typing import Any, Dict, List, Optional, Tuple
from urllib.parse import urlparse
import hashlib
import json
@@ -20,6 +21,7 @@ from fastapi import HTTPException
from sqlalchemy import func, select
from sqlalchemy.ext.asyncio import AsyncSession
from app.core.config import settings
from app.core.logging import get_logger
from app.db.models import AnnotationResult, Dataset, DatasetFiles, LabelingProject
from app.module.annotation.config import LabelStudioTagConfig
@@ -40,6 +42,7 @@ from app.module.annotation.service.text_fetcher import fetch_text_content_via_do
logger = get_logger(__name__)
TEXT_DATA_KEY = "text"
IMAGE_DATA_KEY = "image"
DATASET_ID_KEY = "dataset_id"
FILE_ID_KEY = "file_id"
FILE_NAME_KEY = "file_name"
@@ -50,7 +53,9 @@ SEGMENT_INDEX_KEY = "segment_index"
SEGMENT_INDEX_CAMEL_KEY = "segmentIndex"
JSONL_EXTENSION = ".jsonl"
TEXTUAL_OBJECT_CATEGORIES = {"text", "document"}
MEDIA_OBJECT_CATEGORIES = {"image"}
OBJECT_NAME_HEADER_PREFIX = "dm_object_header_"
SUPPORTED_EDITOR_DATASET_TYPES = ("TEXT", "IMAGE")
class AnnotationEditorService:
@@ -84,6 +89,32 @@ class AnnotationEditorService:
# 单人单份最终标签：每个 task 只保留一个 annotation，id 直接与 task 绑定即可
return self._stable_ls_id(f"annotation:{project_id}:{file_id}")
@staticmethod
def _normalize_dataset_type(dataset_type: Optional[str]) -> str:
return (dataset_type or "").upper()
@staticmethod
def _resolve_public_api_prefix() -> str:
base = (settings.datamate_backend_base_url or "").strip()
if not base:
return "/api"
parsed = urlparse(base)
if parsed.scheme and parsed.netloc:
prefix = parsed.path
else:
prefix = base
prefix = prefix.rstrip("/")
if not prefix:
return "/api"
if not prefix.startswith("/"):
prefix = "/" + prefix
return prefix
@classmethod
def _build_file_preview_url(cls, dataset_id: str, file_id: str) -> str:
prefix = cls._resolve_public_api_prefix()
return f"{prefix}/data-management/datasets/{dataset_id}/files/{file_id}/preview"
async def _get_project_or_404(self, project_id: str) -> LabelingProject:
result = await self.db.execute(
select(LabelingProject).where(
@@ -129,6 +160,23 @@ class AnnotationEditorService:
return TEXT_DATA_KEY
return keys[0]
@classmethod
def _resolve_primary_media_key(
cls,
label_config: Optional[str],
default_key: str,
categories: Optional[set[str]] = None,
) -> str:
if not label_config:
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]
@staticmethod
def _try_parse_json_payload(text_content: str) -> Optional[Dict[str, Any]]:
if not text_content:
@@ -160,7 +208,11 @@ class AnnotationEditorService:
return category in TEXTUAL_OBJECT_CATEGORIES
@classmethod
def _extract_textual_value_keys(cls, label_config: str) -> List[str]:
def _extract_object_value_keys_by_category(
cls,
label_config: str,
categories: set[str],
) -> List[str]:
try:
root = ET.fromstring(label_config)
except Exception as exc:
@@ -172,7 +224,9 @@ class AnnotationEditorService:
for element in root.iter():
if element.tag not in object_types:
continue
if not cls._is_textual_object_tag(element.tag):
config = LabelStudioTagConfig.get_object_config(element.tag) or {}
category = config.get("category")
if categories and category not in categories:
continue
value = element.attrib.get("value", "")
if not value.startswith("$"):
@@ -183,6 +237,10 @@ class AnnotationEditorService:
seen[key] = None
return list(seen.keys())
@classmethod
def _extract_textual_value_keys(cls, label_config: str) -> List[str]:
return cls._extract_object_value_keys_by_category(label_config, TEXTUAL_OBJECT_CATEGORIES)
@staticmethod
def _needs_placeholder(value: Any) -> bool:
if value is None:
@@ -310,11 +368,12 @@ class AnnotationEditorService:
async def get_project_info(self, project_id: str) -> EditorProjectInfo:
project = await self._get_project_or_404(project_id)
dataset_type = await self._get_dataset_type(project.dataset_id)
supported = (dataset_type or "").upper() == "TEXT"
dataset_type = self._normalize_dataset_type(await self._get_dataset_type(project.dataset_id))
supported = dataset_type in SUPPORTED_EDITOR_DATASET_TYPES
unsupported_reason = None
if not supported:
unsupported_reason = f"当前仅支持 TEXT，项目数据类型为: {dataset_type or 'UNKNOWN'}"
supported_hint = "/".join(SUPPORTED_EDITOR_DATASET_TYPES)
unsupported_reason = f"当前仅支持 {supported_hint}，项目数据类型为: {dataset_type or 'UNKNOWN'}"
# 优先使用项目配置中的label_config（用户编辑版本），其次使用模板默认配置
label_config = await self._resolve_project_label_config(project)
@@ -393,10 +452,9 @@ class AnnotationEditorService:
) -> EditorTaskResponse:
project = await self._get_project_or_404(project_id)
# TEXT 支持校验
dataset_type = await self._get_dataset_type(project.dataset_id)
if (dataset_type or "").upper() != "TEXT":
raise HTTPException(status_code=400, detail="当前仅支持 TEXT 项目的内嵌编辑器")
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")
file_result = await self.db.execute(
select(DatasetFiles).where(
@@ -408,6 +466,18 @@ 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":
return await self._build_image_task(project, file_record, file_id)
return await self._build_text_task(project, file_record, file_id, segment_index)
async def _build_text_task(
self,
project: LabelingProject,
file_record: DatasetFiles,
file_id: str,
segment_index: Optional[int],
) -> EditorTaskResponse:
text_content = await self._fetch_text_content_via_download_api(project.dataset_id, file_id)
assert isinstance(text_content, str)
label_config = await self._resolve_project_label_config(project)
@@ -434,13 +504,13 @@ class AnnotationEditorService:
# 获取现有标注
ann_result = await self.db.execute(
select(AnnotationResult).where(
AnnotationResult.project_id == project_id,
AnnotationResult.project_id == project.id,
AnnotationResult.file_id == file_id,
)
)
ann = ann_result.scalar_one_or_none()
ls_task_id = self._make_ls_task_id(project_id, file_id)
ls_task_id = self._make_ls_task_id(project.id, file_id)
# 判断是否需要分段（JSONL 多行或主文本超过阈值）
needs_segmentation = len(records) > 1 or any(
@@ -529,7 +599,7 @@ class AnnotationEditorService:
segment_annotations = ann.annotation.get("segments", {})
seg_ann = segment_annotations.get(str(current_segment_index), {})
stored = {
"id": self._make_ls_annotation_id(project_id, file_id) + current_segment_index,
"id": self._make_ls_annotation_id(project.id, file_id) + current_segment_index,
"task": ls_task_id,
"result": seg_ann.get("result", []),
"created_at": seg_ann.get("created_at", datetime.utcnow().isoformat() + "Z"),
@@ -541,11 +611,11 @@ class AnnotationEditorService:
stored = dict(ann.annotation or {})
stored["task"] = ls_task_id
if not isinstance(stored.get("id"), int):
stored["id"] = self._make_ls_annotation_id(project_id, file_id)
stored["id"] = self._make_ls_annotation_id(project.id, file_id)
task["annotations"] = [stored]
else:
# 首次从非分段切换到分段：提供空标注
empty_ann_id = self._make_ls_annotation_id(project_id, file_id) + current_segment_index
empty_ann_id = self._make_ls_annotation_id(project.id, file_id) + current_segment_index
task["annotations"] = [
{
"id": empty_ann_id,
@@ -557,7 +627,7 @@ class AnnotationEditorService:
]
else:
# 提供一个空 annotation，避免前端在没有选中 annotation 时无法产生 result
empty_ann_id = self._make_ls_annotation_id(project_id, file_id)
empty_ann_id = self._make_ls_annotation_id(project.id, file_id)
if needs_segmentation:
empty_ann_id += current_segment_index
task["annotations"] = [
@@ -579,6 +649,76 @@ class AnnotationEditorService:
currentSegmentIndex=current_segment_index,
)
async def _build_image_task(
self,
project: LabelingProject,
file_record: DatasetFiles,
file_id: 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,
)
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,
DATASET_ID_CAMEL_KEY: project.dataset_id,
FILE_NAME_KEY: file_name,
FILE_NAME_CAMEL_KEY: file_name,
}
# 获取现有标注
ann_result = await self.db.execute(
select(AnnotationResult).where(
AnnotationResult.project_id == project.id,
AnnotationResult.file_id == file_id,
)
)
ann = ann_result.scalar_one_or_none()
ls_task_id = self._make_ls_task_id(project.id, file_id)
task: Dict[str, Any] = {
"id": ls_task_id,
"data": task_data,
"annotations": [],
}
annotation_updated_at = None
if ann and not (ann.annotation or {}).get("segmented"):
annotation_updated_at = ann.updated_at
stored = dict(ann.annotation or {})
stored["task"] = ls_task_id
if not isinstance(stored.get("id"), int):
stored["id"] = self._make_ls_annotation_id(project.id, file_id)
task["annotations"] = [stored]
else:
empty_ann_id = self._make_ls_annotation_id(project.id, file_id)
task["annotations"] = [
{
"id": empty_ann_id,
"task": ls_task_id,
"result": [],
"created_at": datetime.utcnow().isoformat() + "Z",
"updated_at": datetime.utcnow().isoformat() + "Z",
}
]
return EditorTaskResponse(
task=task,
annotationUpdatedAt=annotation_updated_at,
segmented=False,
segments=None,
totalSegments=1,
currentSegmentIndex=0,
)
async def upsert_annotation(self, project_id: str, file_id: str, request: UpsertAnnotationRequest) -> UpsertAnnotationResponse:
project = await self._get_project_or_404(project_id)