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f365539ff2
Bugfix：自动传播 worker 改为在本次目标帧段内按 seed 来源、方向、权重和签名查找旧传播结果；未修改且目标帧已覆盖时直接跳过，不再重复跑 SAM 造成 mask 堆叠。 Bugfix：同一 seed 被编辑、目标帧段只部分覆盖或切换 SAM 2.1 权重时，worker 会先删除本次目标帧段内同源旧自动传播标注，再重新传播。 Bugfix：未编辑的自动传播结果再次作为参考 seed 时会继承原始 propagation_seed_signature；编辑后的传播结果只保留 source_annotation_id/source_mask_id lineage，不继承旧签名，从而触发重传路径。 Bugfix：后端传播签名增加 canonical rounding，减少浮点精度细微变化导致未编辑 mask 被误判为已修改。 功能调整：清空片段遮罩改成与自动传播一致的时间轴范围选择流程，首次点击进入选区，拖拽选择起止帧后点击确认清空才执行。 接口契约：PropagationSeed 增加 propagation_seed_signature 字段，用于前端把未编辑传播结果绑定回原始 seed 传播链。 测试：补充前端 VideoWorkspace 范围清空、传播 lineage 传递测试；补充后端未编辑传播 seed 跳过重复传播、旧结果清理与换权重重传测试。 文档：同步更新 doc/03、doc/04、doc/07、doc/08、doc/09，明确 A/B 传播去重规则、清空片段范围选择和新增 seed signature 契约。
300 lines
7.8 KiB
Python
300 lines
7.8 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 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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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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