111 lines
3.1 KiB
Python
111 lines
3.1 KiB
Python
from __future__ import annotations
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from datetime import datetime
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from uuid import UUID
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from pydantic import BaseModel, ConfigDict, Field
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from app.schemas.detection import DetectionModelCapability
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SegmentationModelCapability = DetectionModelCapability
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class SegmentationModelsResponse(BaseModel):
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models: list[SegmentationModelCapability]
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class SegmentationRunRequest(BaseModel):
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model_config = ConfigDict(protected_namespaces=())
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project_id: UUID
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dataset_id: UUID
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model_id: str
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confidence_threshold: float = Field(default=0.5, ge=0.0, le=1.0)
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class_filter: list[str] | None = None
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tile_manifest_path: str | None = None
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parameters_json: dict = Field(default_factory=dict)
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class SegmentationQaRequest(BaseModel):
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reference_dataset_id: UUID
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iou_threshold: float = Field(default=0.5, ge=0.0, le=1.0)
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class_name: str | None = None
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min_confidence: float | None = Field(default=None, ge=0.0, le=1.0)
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# Read off the one matching pass, exactly as for detection.
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calibration_thresholds: list[float] = Field(default_factory=list, max_length=32)
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class SegmentationRunResponse(BaseModel):
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model_config = ConfigDict(protected_namespaces=())
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analysis_run_id: UUID
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job_id: UUID
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project_id: UUID
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dataset_id: UUID
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model_id: str
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status: str
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segmentation_count: int
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error_code: str | None = None
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message: str
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class SegmentationRunRead(BaseModel):
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model_config = ConfigDict(from_attributes=True, protected_namespaces=())
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id: UUID
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project_id: UUID
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dataset_id: UUID | None = None
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job_id: UUID | None = None
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analysis_type: str
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status: str
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model_name: str | None = None
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model_version: str | None = None
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parameters_json: dict
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result_json: dict | None = None
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error_message: str | None = None
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created_at: datetime | None = None
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started_at: datetime | None = None
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finished_at: datetime | None = None
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class SegmentationRunListResponse(BaseModel):
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items: list[SegmentationRunRead]
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# ``total`` counts every run; ``items`` is the most recent page of them.
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total: int
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limit: int | None = None
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offset: int = 0
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truncated: bool = False
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class SegmentationRead(BaseModel):
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model_config = ConfigDict(from_attributes=True, protected_namespaces=())
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id: UUID
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project_id: UUID
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dataset_id: UUID | None = None
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analysis_run_id: UUID | None = None
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job_id: UUID | None = None
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model_name: str
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model_version: str | None = None
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class_name: str
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confidence: float | None = None
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bbox_json: dict | None = None
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area_m2: float | None = None
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mask_path: str | None = None
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source_tile_path: str | None = None
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tile_index: int | None = None
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properties_json: dict | None = None
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provenance_json: dict | None = None
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created_at: datetime | None = None
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class SegmentationListResponse(BaseModel):
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items: list[SegmentationRead]
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# ``total`` describes the complete filtered population; ``items`` is one
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# stable confidence-ranked page of it.
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total: int
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limit: int | None = None
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offset: int = 0
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truncated: bool = False
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