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功能增加： - 新增后端 /api/ai/smooth-mask 接口，对当前 mask polygon 执行 Chaikin 边缘平滑，并返回 polygon、bbox、area 与拓扑锚点。 - 在右侧实例属性面板加入边缘平滑强度和应用边缘平滑操作，应用后将 mask 标记为 draft/dirty，并通过正常保存链路落库。 - 保存标注与传播 seed 时保留 geometry_smoothing 元数据，自动传播 forward/backward 结果保存前应用同一平滑参数。 - 自动传播 seed signature 纳入平滑参数，修改平滑强度后会触发旧同源传播结果清理并重新传播。 - 支持跨帧跟随同一传播链 mask，AI 推送回工作区时保留当前帧视角。 Bugfix： - 修复中间帧向前传播时旧 forward/backward 同物体结果未被清理导致双重 mask 的问题。 - 修复 propagation worker 写入目标帧前只按旧方向清理导致 backward 重传残留的问题。 - 修复多边形顶点拖拽和编辑后画布视口异常移动的问题，并补充拖拽状态回写。 - 修复实例属性标题跟随全局 active class 而不是当前 mask label 的问题，并移除后端模型置信度展示。 开发与部署： - 新增 restart_dev_services.sh，使用 setsid 独立后台重启 FastAPI、Celery 和前端，写入 pid/log 文件并做 3000/8000 健康检查。 - 明确后端或 Celery 相关改动完成后需要运行重启脚本，保证运行态加载最新代码。 测试与文档： - 补充后端 smooth-mask、传播平滑 metadata、seed signature、传播去重方向覆盖等测试。 - 补充前端 OntologyInspector、VideoWorkspace、CanvasArea 和 api 契约测试，覆盖边缘平滑、传播参数、跨帧选区跟随和画布编辑行为。 - 更新 README、AGENTS、安装文档、前端元素审计、需求冻结、设计冻结和测试计划，记录当前真实行为与重启要求。
320 lines
8.4 KiB
Python
320 lines
8.4 KiB
Python
"""Pydantic schemas for request/response validation."""
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from datetime import datetime
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from typing import Optional, Any
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from pydantic import BaseModel, ConfigDict
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# ---------------------------------------------------------------------------
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# Project schemas
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# ---------------------------------------------------------------------------
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class ProjectBase(BaseModel):
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name: str
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description: Optional[str] = None
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video_path: Optional[str] = None
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thumbnail_url: Optional[str] = None
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status: Optional[str] = "pending"
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source_type: Optional[str] = "video"
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original_fps: Optional[float] = None
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parse_fps: Optional[float] = 30.0
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class ProjectCreate(ProjectBase):
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pass
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class ProjectUpdate(BaseModel):
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name: Optional[str] = None
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description: Optional[str] = None
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video_path: Optional[str] = None
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thumbnail_url: Optional[str] = None
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status: Optional[str] = None
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source_type: Optional[str] = None
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original_fps: Optional[float] = None
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parse_fps: Optional[float] = None
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class ProjectOut(ProjectBase):
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model_config = ConfigDict(from_attributes=True)
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id: int
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created_at: datetime
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updated_at: datetime
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frame_count: int = 0
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# ---------------------------------------------------------------------------
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# Frame schemas
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# ---------------------------------------------------------------------------
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class FrameBase(BaseModel):
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frame_index: int
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image_url: str
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width: Optional[int] = None
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height: Optional[int] = None
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timestamp_ms: Optional[float] = None
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source_frame_number: Optional[int] = None
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class FrameCreate(FrameBase):
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project_id: int
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class FrameOut(FrameBase):
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model_config = ConfigDict(from_attributes=True)
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id: int
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project_id: int
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created_at: datetime
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# ---------------------------------------------------------------------------
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# Template schemas
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# ---------------------------------------------------------------------------
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class TemplateBase(BaseModel):
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name: str
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description: Optional[str] = None
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color: str
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z_index: int = 0
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mapping_rules: Optional[dict[str, Any]] = None
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classes: Optional[list[dict[str, Any]]] = None
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rules: Optional[list[dict[str, Any]]] = None
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class TemplateCreate(TemplateBase):
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pass
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class TemplateUpdate(BaseModel):
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name: Optional[str] = None
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description: Optional[str] = None
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color: Optional[str] = None
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z_index: Optional[int] = None
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mapping_rules: Optional[dict[str, Any]] = None
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classes: Optional[list[dict[str, Any]]] = None
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rules: Optional[list[dict[str, Any]]] = None
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class TemplateOut(TemplateBase):
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model_config = ConfigDict(from_attributes=True)
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id: int
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created_at: datetime
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# ---------------------------------------------------------------------------
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# Annotation schemas
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# ---------------------------------------------------------------------------
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class AnnotationBase(BaseModel):
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project_id: int
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frame_id: Optional[int] = None
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template_id: Optional[int] = None
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mask_data: Optional[dict[str, Any]] = None
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points: Optional[list[list[float]]] = None
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bbox: Optional[list[float]] = None
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class AnnotationCreate(AnnotationBase):
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pass
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class AnnotationUpdate(BaseModel):
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mask_data: Optional[dict[str, Any]] = None
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points: Optional[list[list[float]]] = None
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bbox: Optional[list[float]] = None
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template_id: Optional[int] = None
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class AnnotationOut(AnnotationBase):
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model_config = ConfigDict(from_attributes=True)
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id: int
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created_at: datetime
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updated_at: datetime
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# ---------------------------------------------------------------------------
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# Mask schemas
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# ---------------------------------------------------------------------------
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class MaskBase(BaseModel):
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annotation_id: int
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mask_url: str
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format: str = "png"
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class MaskCreate(MaskBase):
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pass
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class MaskOut(MaskBase):
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model_config = ConfigDict(from_attributes=True)
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id: int
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created_at: datetime
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# ---------------------------------------------------------------------------
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# Processing task schemas
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# ---------------------------------------------------------------------------
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class ProcessingTaskOut(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: int
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task_type: str
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status: str
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progress: int
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message: Optional[str] = None
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project_id: Optional[int] = None
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celery_task_id: Optional[str] = None
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payload: Optional[dict[str, Any]] = None
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result: Optional[dict[str, Any]] = None
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error: Optional[str] = None
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created_at: datetime
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started_at: Optional[datetime] = None
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finished_at: Optional[datetime] = None
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updated_at: datetime
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# ---------------------------------------------------------------------------
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# AI schemas
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# ---------------------------------------------------------------------------
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class PredictRequest(BaseModel):
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image_id: int
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prompt_type: str # point / box / semantic
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prompt_data: Any
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model: Optional[str] = None
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options: Optional[dict[str, Any]] = None
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class PredictResponse(BaseModel):
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polygons: list[list[list[float]]]
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scores: Optional[list[float]] = None
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class MaskAnalysisRequest(BaseModel):
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frame_id: Optional[int] = None
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mask_data: dict[str, Any]
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points: Optional[list[list[float]]] = None
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bbox: Optional[list[float]] = None
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extract_skeleton: bool = False
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class MaskAnalysisResponse(BaseModel):
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confidence: Optional[float] = None
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confidence_source: str
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topology_anchor_count: int
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topology_anchors: list[list[float]]
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area: float
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bbox: Optional[list[float]] = None
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source: Optional[str] = None
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message: str
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class SmoothMaskRequest(BaseModel):
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frame_id: Optional[int] = None
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mask_data: dict[str, Any]
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points: Optional[list[list[float]]] = None
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bbox: Optional[list[float]] = None
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strength: float = 0.0
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method: str = "chaikin"
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class SmoothMaskResponse(BaseModel):
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polygons: list[list[list[float]]]
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topology_anchor_count: int
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topology_anchors: list[list[float]]
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area: float
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bbox: Optional[list[float]] = None
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smoothing: dict[str, Any]
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message: str
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class PropagationSeed(BaseModel):
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polygons: Optional[list[list[list[float]]]] = None
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bbox: Optional[list[float]] = None
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points: Optional[list[list[float]]] = None
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labels: Optional[list[int]] = None
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label: Optional[str] = None
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color: Optional[str] = None
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class_metadata: Optional[dict[str, Any]] = None
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template_id: Optional[int] = None
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source_mask_id: Optional[str] = None
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source_annotation_id: Optional[int] = None
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propagation_seed_signature: Optional[str] = None
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smoothing: Optional[dict[str, Any]] = None
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class PropagateRequest(BaseModel):
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project_id: int
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frame_id: int
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model: Optional[str] = "sam2.1_hiera_tiny"
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seed: PropagationSeed
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direction: str = "forward"
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max_frames: int = 30
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include_source: bool = False
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save_annotations: bool = True
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class PropagateResponse(BaseModel):
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model: str
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direction: str
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source_frame_id: int
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processed_frame_count: int
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created_annotation_count: int
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annotations: list[AnnotationOut]
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class PropagateTaskStep(BaseModel):
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seed: PropagationSeed
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direction: str = "forward"
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max_frames: int = 30
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class PropagateTaskRequest(BaseModel):
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project_id: int
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frame_id: int
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model: Optional[str] = "sam2.1_hiera_tiny"
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steps: list[PropagateTaskStep]
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include_source: bool = False
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save_annotations: bool = True
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class AiModelStatus(BaseModel):
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id: str
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label: str
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available: bool
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loaded: bool = False
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device: str
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supports: list[str]
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message: str
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package_available: bool = False
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checkpoint_exists: bool = False
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checkpoint_path: Optional[str] = None
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python_ok: bool = True
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torch_ok: bool = True
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cuda_required: bool = False
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external_available: bool = False
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external_python: Optional[str] = None
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class GpuStatus(BaseModel):
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available: bool
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device: str
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name: Optional[str] = None
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torch_available: bool
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torch_version: Optional[str] = None
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cuda_version: Optional[str] = None
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class AiRuntimeStatus(BaseModel):
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selected_model: str
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gpu: GpuStatus
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models: list[AiModelStatus]
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# ---------------------------------------------------------------------------
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# Export schemas
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# ---------------------------------------------------------------------------
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class ExportStatus(BaseModel):
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url: str
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format: str
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