115 lines
3.4 KiB
Python
115 lines
3.4 KiB
Python
from __future__ import annotations
|
|
|
|
from datetime import datetime
|
|
from typing import Any
|
|
from uuid import UUID
|
|
|
|
from pydantic import BaseModel, Field
|
|
|
|
from app.schemas.common import GeoJsonFeatureCollection
|
|
|
|
|
|
class QaProviderComparisonRequest(BaseModel):
|
|
candidate_dataset_id: UUID
|
|
reference_dataset_id: UUID
|
|
iou_threshold: float = Field(default=0.5, ge=0.0, le=1.0)
|
|
area_id: UUID | None = None
|
|
|
|
|
|
class QaProviderComparisonResult(BaseModel):
|
|
status: str
|
|
warnings: list[str] = Field(default_factory=list)
|
|
candidate_feature_count: int
|
|
reference_feature_count: int
|
|
matches: int
|
|
false_positives: int
|
|
false_negatives: int
|
|
precision: float | None
|
|
recall: float | None
|
|
f1_score: float | None
|
|
mean_iou: float | None
|
|
iou_threshold: float
|
|
unsupported_geometry: bool = False
|
|
unsupported_geometries: list[str] = Field(default_factory=list)
|
|
match_evidence: list[dict] = Field(default_factory=list)
|
|
false_positive_evidence: list[dict] = Field(default_factory=list)
|
|
false_negative_evidence: list[dict] = Field(default_factory=list)
|
|
generated_at: datetime
|
|
|
|
|
|
class MetricRead(BaseModel):
|
|
id: UUID
|
|
quality_check_id: UUID | None = None
|
|
analysis_run_id: UUID | None = None
|
|
metric_key: str
|
|
metric_value: float | None = None
|
|
metric_unit: str | None = None
|
|
label: str | None = None
|
|
metadata_json: dict | None = None
|
|
created_at: datetime | None = None
|
|
|
|
model_config = {"from_attributes": True}
|
|
|
|
|
|
class QualityCheckRead(BaseModel):
|
|
id: UUID
|
|
project_id: UUID
|
|
job_id: UUID | None = None
|
|
analysis_run_id: UUID | None = None
|
|
candidate_dataset_id: UUID | None = None
|
|
reference_dataset_id: UUID
|
|
check_type: str
|
|
status: str
|
|
score: float | None = None
|
|
parameters_json: dict | None = None
|
|
findings_json: dict | None = None
|
|
created_at: datetime | None = None
|
|
completed_at: datetime | None = None
|
|
metrics: list[MetricRead] = Field(default_factory=list)
|
|
|
|
model_config = {"from_attributes": True}
|
|
|
|
|
|
class QualityCheckList(BaseModel):
|
|
items: list[QualityCheckRead]
|
|
total: int
|
|
limit: int
|
|
offset: int
|
|
|
|
|
|
class QualityEvidenceResponse(BaseModel):
|
|
quality_check_id: UUID
|
|
project_id: UUID
|
|
candidate_dataset_id: UUID | None = None
|
|
reference_dataset_id: UUID
|
|
analysis_run_id: UUID | None = None
|
|
feature_count: int
|
|
warnings: list[str] = Field(default_factory=list)
|
|
geojson: GeoJsonFeatureCollection
|
|
|
|
|
|
class AnalysisQaResponse(BaseModel):
|
|
status: str
|
|
quality_check_id: UUID
|
|
analysis_run_id: UUID
|
|
reference_dataset_id: UUID
|
|
candidate_feature_count: int
|
|
reference_feature_count: int
|
|
candidate_feature_count_raw: int | None = None
|
|
reference_feature_count_raw: int | None = None
|
|
matches: int
|
|
false_positives: int
|
|
false_negatives: int
|
|
precision: float | None = None
|
|
recall: float | None = None
|
|
f1_score: float | None = None
|
|
mean_iou: float | None = None
|
|
iou_threshold: float
|
|
warnings: list[str] = Field(default_factory=list)
|
|
coverage: dict[str, Any] | None = None
|
|
temporal_compatibility: dict[str, Any] | None = None
|
|
box_to_footprint_diagnostics: dict[str, Any] | None = None
|
|
match_evidence: list[dict[str, Any]] = Field(default_factory=list)
|
|
false_positive_evidence: list[dict[str, Any]] = Field(default_factory=list)
|
|
false_negative_evidence: list[dict[str, Any]] = Field(default_factory=list)
|