Initial GeoIntel V1 foundation

backend/app/schemas/__init__.py

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+from __future__ import annotations
+
+from .common import ApiErrorEnvelope, ApiErrorItem, Envelope, PaginationEnvelope
+from .project import ProjectCreate, ProjectList, ProjectRead, ProjectUpdate
+from .area import AreaCreate, AreaList, AreaRead, AreaUpdate
+from .dataset import DatasetCreateResponse, DatasetList
+from .detection import (
+    DetectionListResponse,
+    DetectionModelCapability,
+    DetectionModelsResponse,
+    DetectionQaRequest,
+    DetectionRead,
+    DetectionRunListResponse,
+    DetectionRunRead,
+    DetectionRunRequest,
+    DetectionRunResponse,
+)
+from .segmentation import (
+    SegmentationListResponse,
+    SegmentationModelCapability,
+    SegmentationModelsResponse,
+    SegmentationQaRequest,
+    SegmentationRead,
+    SegmentationRunListResponse,
+    SegmentationRunRead,
+    SegmentationRunRequest,
+    SegmentationRunResponse,
+)
+from .health import HealthResponse, SystemCapabilities
+from .job import JobCreate, JobList, JobRead, JobStatus
+from .external import (
+    ExternalFetchRequest,
+    ExternalFetchResponse,
+    ProviderCapabilitiesResponse,
+    ProviderCapabilityResponse,
+    ProviderImportRequest,
+    ProviderImportResponse,
+    ProviderLayersResponse,
+    ProviderStatusResponse,
+)
+from .export import (
+    ExportContentResponse,
+    ExportCreateResponse,
+    ExportListResponse,
+    ExportRead,
+    GeoJsonExportRequest,
+    MetadataExportRequest,
+    ReportExportRequest,
+)
+from .qa import QaProviderComparisonRequest, QaProviderComparisonResult
+from .operations import (
+    RasterClipRequest,
+    RasterIndexBaseRequest,
+    RasterMetadataResponse,
+    RasterNdviRequest,
+    RasterNdwiRequest,
+    RasterNdbiRequest,
+    RasterOperationResult,
+    RasterPreviewResponse,
+    RasterReprojectRequest,
+    RasterReprojectResponse,
+    RasterStatsResponse,
+    RasterTileManifest,
+    RasterTileManifestTile,
+    RasterTileRequest,
+    RasterTileResponse,
+    VectorBBoxResponse,
+    VectorBufferRequest,
+    VectorClipRequest,
+    VectorIntersectRequest,
+    VectorOperationRequest,
+    VectorOperationResult,
+    VectorStatsRequest,
+    VectorStatsResponse,
+)
+
+__all__ = [
+    "Envelope",
+    "ApiErrorEnvelope",
+    "ApiErrorItem",
+    "PaginationEnvelope",
+    "ProjectCreate",
+    "ProjectRead",
+    "ProjectUpdate",
+    "ProjectList",
+    "AreaCreate",
+    "AreaRead",
+    "AreaUpdate",
+    "AreaList",
+    "DatasetCreateResponse",
+    "DatasetList",
+    "DetectionListResponse",
+    "DetectionModelCapability",
+    "DetectionModelsResponse",
+    "DetectionQaRequest",
+    "DetectionRead",
+    "DetectionRunListResponse",
+    "DetectionRunRead",
+    "DetectionRunRequest",
+    "DetectionRunResponse",
+    "SegmentationListResponse",
+    "SegmentationModelCapability",
+    "SegmentationModelsResponse",
+    "SegmentationQaRequest",
+    "SegmentationRead",
+    "SegmentationRunListResponse",
+    "SegmentationRunRead",
+    "SegmentationRunRequest",
+    "SegmentationRunResponse",
+    "HealthResponse",
+    "SystemCapabilities",
+    "JobCreate",
+    "JobList",
+    "JobRead",
+    "JobStatus",
+    "VectorBBoxResponse",
+    "VectorClipRequest",
+    "VectorBufferRequest",
+    "VectorIntersectRequest",
+    "VectorOperationRequest",
+    "VectorOperationResult",
+    "RasterClipRequest",
+    "RasterStatsResponse",
+    "RasterReprojectRequest",
+    "RasterReprojectResponse",
+    "RasterTileRequest",
+    "RasterMetadataResponse",
+    "RasterOperationResult",
+    "RasterPreviewResponse",
+    "RasterTileManifestTile",
+    "RasterTileManifest",
+    "RasterTileResponse",
+    "RasterIndexBaseRequest",
+    "RasterNdviRequest",
+    "RasterNdwiRequest",
+    "RasterNdbiRequest",
+    "VectorStatsRequest",
+    "VectorStatsResponse",
+    "ExternalFetchRequest",
+    "ExternalFetchResponse",
+    "ProviderCapabilitiesResponse",
+    "ProviderCapabilityResponse",
+    "ProviderImportRequest",
+    "ProviderImportResponse",
+    "ProviderLayersResponse",
+    "ProviderStatusResponse",
+    "GeoJsonExportRequest",
+    "MetadataExportRequest",
+    "ReportExportRequest",
+    "ExportRead",
+    "ExportCreateResponse",
+    "ExportListResponse",
+    "ExportContentResponse",
+    "QaProviderComparisonRequest",
+    "QaProviderComparisonResult",
+]

backend/app/schemas/area.py

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+from __future__ import annotations
+
+from datetime import datetime
+from uuid import UUID
+
+from pydantic import BaseModel
+
+
+class AreaCreate(BaseModel):
+    name: str
+    geometry: dict
+    crs: str | None = "EPSG:4326"
+
+
+class AreaUpdate(BaseModel):
+    name: str | None = None
+    crs: str | None = None
+
+
+class AreaRead(BaseModel):
+    id: UUID
+    project_id: UUID
+    name: str
+    original_crs: str | None
+    area_m2: float | None
+    created_at: datetime | None = None
+    geometry_type: str | None = None
+
+    model_config = {"from_attributes": True}
+
+
+class AreaListItem(AreaRead):
+    pass
+
+
+class AreaList(BaseModel):
+    items: list[AreaRead]
+    total: int
+    limit: int
+    offset: int

backend/app/schemas/common.py

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+from __future__ import annotations
+
+from pydantic import BaseModel, Field
+
+
+class Envelope(BaseModel):
+    data: object
+
+
+class PaginatedEnvelope(BaseModel):
+    items: list
+    total: int
+    limit: int
+    offset: int
+
+
+class PaginationEnvelope(BaseModel):
+    items: list
+    total: int
+    limit: int = Field(default=50)
+    offset: int = Field(default=0)
+
+
+class ApiErrorItem(BaseModel):
+    code: str
+    message: str
+    details: dict = Field(default_factory=dict)
+
+
+class ApiErrorEnvelope(BaseModel):
+    error: ApiErrorItem

backend/app/schemas/dataset.py

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+from __future__ import annotations
+
+from datetime import datetime
+from uuid import UUID
+
+from pydantic import BaseModel
+
+
+class DatasetStorageResponse(BaseModel):
+    original_filename: str | None = None
+    stored_filename: str | None = None
+    content_type: str | None = None
+    size_bytes: int | None = None
+    checksum_sha256: str | None = None
+
+
+class DatasetVectorSummary(BaseModel):
+    feature_count: int | None = None
+    geometry_types: list[str] | None = None
+    bounds_json: dict | None = None
+    approximate_area_m2: float | None = None
+    crs: str | None = None
+    feature_geometry_count: int | None = None
+    invalid_features: int | None = None
+    crs_assumed: bool | None = None
+
+
+class DatasetCreateResponse(BaseModel):
+    id: UUID
+    name: str
+    dataset_type: str
+    source: str
+    dataset_role: str = "source"
+    source_name: str | None = None
+    reference_layer_name: str | None = None
+    source_metadata: dict | None = None
+    provenance_metadata: dict | None = None
+    imported_at: datetime | None = None
+    project_id: UUID
+    area_id: UUID | None = None
+    storage_path: str | None = None
+    original_filename: str | None = None
+    stored_filename: str | None = None
+    content_type: str | None = None
+    size_bytes: int | None = None
+    checksum_sha256: str | None = None
+    crs: str | None = None
+    bounds_json: dict | None = None
+    metadata_json: dict | None = None
+    vector_summary: DatasetVectorSummary | None = None
+    status: str
+    derived_from_dataset_id: UUID | None = None
+    created_at: datetime | None = None
+    feature_count: int | None = None
+
+    model_config = {"from_attributes": True}
+
+
+class DatasetList(BaseModel):
+    items: list[DatasetCreateResponse]
+    total: int
+    limit: int
+    offset: int
+
+
+class DatasetMetadataRefresh(BaseModel):
+    feature_count: int | None = None
+    geometry_types: list[str] | None = None
+    bounds_json: dict | None = None
+    crs: str | None = None
+
+
+class ExportRequest(BaseModel):
+    dataset_id: UUID
+    name: str | None = None
+
+
+class ExportRead(BaseModel):
+    export_id: UUID
+    path: str
+    status: str

backend/app/schemas/demo.py

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+from __future__ import annotations
+
+from uuid import UUID
+
+from pydantic import BaseModel
+
+
+class DemoWorkflowResponse(BaseModel):
+    project_id: UUID
+    area_id: UUID
+    reference_dataset_id: UUID
+    candidate_dataset_id: UUID
+    quality_check_id: UUID
+    metric_count: int
+    status: str
+    message: str
+    created: bool

backend/app/schemas/detection.py

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+from __future__ import annotations
+
+from datetime import datetime
+from uuid import UUID
+
+from pydantic import BaseModel, Field
+
+
+class DetectionModelCapability(BaseModel):
+    model_id: str
+    display_name: str
+    framework: str
+    task_type: str
+    supported_classes: list[str]
+    configured: bool
+    status: str
+    limitation_message: str
+    version: str | None = None
+
+
+class DetectionModelsResponse(BaseModel):
+    models: list[DetectionModelCapability]
+
+
+class DetectionRunRequest(BaseModel):
+    project_id: UUID
+    dataset_id: UUID
+    model_id: str
+    confidence_threshold: float = Field(default=0.5, ge=0.0, le=1.0)
+    class_filter: list[str] | None = None
+    tile_manifest_path: str | None = None
+    parameters_json: dict = Field(default_factory=dict)
+
+
+class DetectionQaRequest(BaseModel):
+    reference_dataset_id: UUID
+    iou_threshold: float = Field(default=0.5, ge=0.0, le=1.0)
+    class_name: str | None = None
+    min_confidence: float | None = Field(default=None, ge=0.0, le=1.0)
+
+
+class DetectionRunResponse(BaseModel):
+    analysis_run_id: UUID
+    job_id: UUID
+    project_id: UUID
+    dataset_id: UUID
+    model_id: str
+    status: str
+    detection_count: int
+    error_code: str | None = None
+    message: str
+
+
+class DetectionRunRead(BaseModel):
+    id: UUID
+    project_id: UUID
+    dataset_id: UUID | None = None
+    job_id: UUID | None = None
+    analysis_type: str
+    status: str
+    model_name: str | None = None
+    model_version: str | None = None
+    parameters_json: dict
+    result_json: dict | None = None
+    error_message: str | None = None
+    created_at: datetime | None = None
+    started_at: datetime | None = None
+    finished_at: datetime | None = None
+
+    model_config = {"from_attributes": True}
+
+
+class DetectionRunListResponse(BaseModel):
+    items: list[DetectionRunRead]
+    total: int
+
+
+class DetectionRead(BaseModel):
+    id: UUID
+    project_id: UUID
+    dataset_id: UUID | None = None
+    analysis_run_id: UUID | None = None
+    job_id: UUID | None = None
+    model_name: str
+    model_version: str | None = None
+    class_name: str
+    confidence: float
+    bbox_json: dict | None = None
+    source_tile_path: str | None = None
+    properties_json: dict | None = None
+    created_at: datetime | None = None
+
+    model_config = {"from_attributes": True}
+
+
+class DetectionListResponse(BaseModel):
+    items: list[DetectionRead]
+    total: int

backend/app/schemas/export.py

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+from __future__ import annotations
+
+from datetime import datetime
+from typing import Literal
+from uuid import UUID
+
+from pydantic import BaseModel, model_validator
+
+
+ExportKind = Literal["dataset", "detection_run", "segmentation_run"]
+
+
+class GeoJsonExportRequest(BaseModel):
+    dataset_id: UUID | None = None
+    analysis_run_id: UUID | None = None
+    export_kind: ExportKind = "dataset"
+    name: str | None = None
+
+    @model_validator(mode="after")
+    def validate_target(self) -> "GeoJsonExportRequest":
+        if self.export_kind == "dataset" and self.dataset_id is None:
+            raise ValueError("dataset_id is required for dataset GeoJSON exports")
+        if self.export_kind in {"detection_run", "segmentation_run"} and self.analysis_run_id is None:
+            raise ValueError("analysis_run_id is required for run GeoJSON exports")
+        return self
+
+
+class MetadataExportRequest(BaseModel):
+    project_id: UUID
+    name: str | None = None
+
+
+class ReportExportRequest(BaseModel):
+    project_id: UUID
+    name: str | None = None
+
+
+class ExportRead(BaseModel):
+    id: UUID
+    project_id: UUID
+    analysis_run_id: UUID | None = None
+    export_type: str
+    storage_path: str
+    metadata_json: dict | None = None
+    created_at: datetime | None = None
+    status: str = "ready"
+
+    model_config = {"from_attributes": True}
+
+
+class ExportCreateResponse(BaseModel):
+    export_id: UUID
+    path: str
+    status: str
+    export_type: str
+    metadata_json: dict | None = None
+
+
+class ExportListResponse(BaseModel):
+    items: list[ExportRead]
+    total: int
+    limit: int
+    offset: int
+
+
+class ExportContentResponse(BaseModel):
+    export_id: UUID
+    export_type: str
+    content: dict

backend/app/schemas/external.py

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+from __future__ import annotations
+
+from uuid import UUID
+from pydantic import BaseModel
+
+
+class ProviderCapabilityResponse(BaseModel):
+    provider_name: str
+    display_name: str
+    authority_level: str
+    supported_layers: list[str]
+    supported_geometry_types: list[str]
+    supported_query_modes: list[str]
+    fetch_signature: str
+    configured: bool
+    status: str
+    limitation_message: str
+    attribution: str
+    license_note: str
+    not_configured_reason: str | None = None
+
+
+class ProviderCapabilitiesResponse(BaseModel):
+    providers: list[ProviderCapabilityResponse]
+
+
+class ProviderLayersResponse(BaseModel):
+    provider_name: str
+    layers: list[str]
+
+
+class ProviderStatusResponse(BaseModel):
+    provider_name: str
+    configured: bool
+    status: str
+    limitation_message: str
+
+
+class ExternalFetchRequest(BaseModel):
+    project_id: UUID
+    area_id: UUID | None = None
+    layers: list[str] = []
+
+
+class ExternalFetchResponse(BaseModel):
+    provider: str
+    status: str
+    message: str
+    requested_layers: list[str]
+    project_id: UUID
+    area_id: UUID | None = None
+
+
+class ProviderImportRequest(BaseModel):
+    project_id: str
+    area_id: str | None = None
+    layers: list[str] = []
+    dataset_role: str | None = None
+
+
+class ProviderImportResponse(BaseModel):
+    provider_name: str
+    status: str
+    message: str
+    requested_layers: list[str]
+    dataset_id: str | None = None
+    dataset_role: str | None = None
+    source_name: str | None = None

backend/app/schemas/health.py

@@ -0,0 +1,37 @@
+from __future__ import annotations
+
+from pydantic import BaseModel, Field
+
+
+class ProviderCapability(BaseModel):
+    provider_name: str
+    display_name: str
+    authority_level: str
+    supported_layers: list[str]
+    supported_geometry_types: list[str]
+    supported_query_modes: list[str]
+    fetch_signature: str
+    configured: bool
+    status: str
+    limitation_message: str
+    attribution: str
+    license_note: str
+    not_configured_reason: str | None = None
+
+
+class HealthResponse(BaseModel):
+    status: str
+    service: str
+    version: str
+    database: str | None = None
+
+
+class SystemCapabilities(BaseModel):
+    postgis: bool
+    rasterio: bool
+    geopandas: bool
+    yolo: bool | str
+    sam: bool | str
+    grb: str
+    sentinel: str
+    providers: list[ProviderCapability] = Field(default_factory=list)

backend/app/schemas/job.py

@@ -0,0 +1,51 @@
+from __future__ import annotations
+
+from datetime import datetime
+from uuid import UUID
+
+from pydantic import BaseModel, Field
+
+
+class JobCreate(BaseModel):
+    job_type: str
+    project_id: UUID
+    dataset_id: UUID | None = None
+    input_dataset_id: UUID | None = None
+    output_dataset_id: UUID | None = None
+    parameters_json: dict = Field(default_factory=dict)
+
+
+class JobRead(BaseModel):
+    id: UUID
+    job_type: str
+    status: str
+    project_id: UUID
+    dataset_id: UUID | None = None
+    input_dataset_id: UUID | None = None
+    output_dataset_id: UUID | None = None
+    parameters_json: dict
+    result_json: dict | None = None
+    error_message: str | None = None
+    created_at: datetime | None = None
+    started_at: datetime | None = None
+    finished_at: datetime | None = None
+
+    model_config = {"from_attributes": True}
+
+
+class JobStatus(BaseModel):
+    id: UUID
+    status: str
+    error_message: str | None = None
+    started_at: datetime | None = None
+    finished_at: datetime | None = None
+    result_json: dict | None = None
+
+    model_config = {"from_attributes": True}
+
+
+class JobList(BaseModel):
+    items: list[JobRead]
+    total: int
+    limit: int
+    offset: int

backend/app/schemas/operations.py

@@ -0,0 +1,193 @@
+from __future__ import annotations
+
+from pydantic import BaseModel
+
+
+class VectorOperationResult(BaseModel):
+    feature_count: int
+    geometry_type_summary: dict[str, int]
+    bounds_json: dict | None = None
+    crs: str | None = None
+    source_dataset_id: str
+
+
+class VectorOperationRequest(BaseModel):
+    output_name: str | None = None
+
+
+class VectorClipRequest(VectorOperationRequest):
+    area_id: str
+
+
+class VectorBufferRequest(VectorOperationRequest):
+    distance_m: float
+    dissolve: bool = False
+
+
+class VectorIntersectRequest(VectorOperationRequest):
+    other_dataset_id: str
+
+
+class VectorStatsRequest(BaseModel):
+    pass
+
+
+class RasterReadyResponse(BaseModel):
+    dataset_id: str
+    ready: bool
+    message: str | None = None
+
+
+class RasterOperationResult(BaseModel):
+    dataset_id: str
+    ready: bool
+    metadata: dict | None = None
+    output_dataset_id: str | None = None
+    operation: str | None = None
+
+
+class RasterMetadataResponse(BaseModel):
+    dataset_id: str
+    driver: str | None = None
+    width: int | None = None
+    height: int | None = None
+    band_count: int | None = None
+    crs: str | None = None
+    bounds: list[float] | None = None
+    resolution: list[float] | None = None
+    dtype: list[str] | None = None
+    nodata: list[float] | float | None = None
+    transform: list[float] | None = None
+    size_bytes: int | None = None
+    checksum_sha256: str | None = None
+    path: str | None = None
+
+
+class RasterPreviewResponse(BaseModel):
+    dataset_id: str
+    ready: bool
+    preview: dict
+    metadata: dict | None = None
+
+
+class RasterBandStats(BaseModel):
+    band_index: int
+    dtype: str | None = None
+    min: float | None = None
+    max: float | None = None
+    mean: float | None = None
+    std: float | None = None
+    nodata_count: int
+    nodata_ratio: float
+    valid_pixel_count: int
+    histogram: list[int] | None = None
+    histogram_bins: list[float] | None = None
+
+
+class RasterStatsResponse(BaseModel):
+    dataset_id: str
+    source_dataset_id: str | None = None
+    bands: list[RasterBandStats]
+    generated_at: str | None = None
+    metadata: dict | None = None
+
+
+class RasterReprojectRequest(BaseModel):
+    target_crs: str | None = "EPSG:31370"
+    resampling: str = "nearest"
+    output_name: str | None = None
+
+
+class RasterClipRequest(BaseModel):
+    area_id: str
+    output_name: str | None = None
+
+
+class RasterTileRequest(BaseModel):
+    tile_size: int = 512
+    overlap: int = 64
+    output_name: str | None = None
+
+
+class RasterIndexBaseRequest(BaseModel):
+    output_name: str | None = None
+
+
+class RasterNdviRequest(RasterIndexBaseRequest):
+    nir_band: int
+    red_band: int
+
+
+class RasterNdwiRequest(RasterIndexBaseRequest):
+    green_band: int
+    nir_band: int
+
+
+class RasterNdbiRequest(RasterIndexBaseRequest):
+    swir_band: int
+    nir_band: int
+
+
+class RasterTileManifestTile(BaseModel):
+    path: str
+    pixel_window: list[int]
+    bounds: list[float]
+    transform: list[float]
+    index: int
+
+
+class RasterTileManifest(BaseModel):
+    tile_set_id: str
+    source_dataset_id: str
+    source_raster_id: str
+    bounds: list[float]
+    tile_size: int
+    overlap: int
+    parameters: dict[str, str | int | float | bool | None]
+    created_at: str
+    tile_paths: list[str]
+    count: int
+    tiles: list[RasterTileManifestTile]
+    ai_inference: bool = False
+    tile_server: str | None = None
+
+
+class RasterTileResponse(BaseModel):
+    dataset_id: str
+    ready: bool
+    operation: str
+    tile_set_id: str
+    tile_size: int
+    overlap: int
+    manifest_path: str
+    count: int
+    manifest: RasterTileManifest
+
+
+class RasterReprojectResponse(BaseModel):
+    dataset_id: str
+    ready: bool
+    operation: str
+    output_dataset_id: str
+    source_dataset_id: str
+    target_dataset_id: str | None = None
+
+
+class RasterOperationUnavailable(BaseModel):
+    code: str
+    message: str
+
+
+class VectorBBoxResponse(BaseModel):
+    dataset_id: str
+    bounds_json: dict | None
+    feature_count: int
+    crs: str | None = None
+
+
+class VectorStatsResponse(BaseModel):
+    dataset_id: str
+    feature_count: int
+    geometry_type_summary: dict[str, int]
+    bounds_json: dict | None
+    crs: str | None = None

backend/app/schemas/project.py

@@ -0,0 +1,41 @@
+from __future__ import annotations
+
+from datetime import datetime
+from uuid import UUID
+
+from pydantic import BaseModel
+
+
+class ProjectCreate(BaseModel):
+    name: str
+    description: str | None = None
+    region: str | None = "Kempen"
+
+
+class ProjectUpdate(BaseModel):
+    name: str | None = None
+    description: str | None = None
+    region: str | None = None
+
+
+class ProjectRead(BaseModel):
+    id: UUID
+    name: str
+    description: str | None = None
+    region: str
+    status: str
+    created_at: datetime | None = None
+    updated_at: datetime | None = None
+
+    model_config = {"from_attributes": True}
+
+
+class ProjectListItem(ProjectRead):
+    pass
+
+
+class ProjectList(BaseModel):
+    items: list[ProjectRead]
+    total: int
+    limit: int
+    offset: int

backend/app/schemas/qa.py

@@ -0,0 +1,71 @@
+from __future__ import annotations
+
+from datetime import datetime
+from uuid import UUID
+
+from pydantic import BaseModel, Field
+
+
+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)
+    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

backend/app/schemas/segmentation.py

@@ -0,0 +1,95 @@
+from __future__ import annotations
+
+from datetime import datetime
+from uuid import UUID
+
+from pydantic import BaseModel, Field
+
+from app.schemas.detection import DetectionModelCapability
+
+
+SegmentationModelCapability = DetectionModelCapability
+
+
+class SegmentationModelsResponse(BaseModel):
+    models: list[SegmentationModelCapability]
+
+
+class SegmentationRunRequest(BaseModel):
+    project_id: UUID
+    dataset_id: UUID
+    model_id: str
+    confidence_threshold: float = Field(default=0.5, ge=0.0, le=1.0)
+    class_filter: list[str] | None = None
+    tile_manifest_path: str | None = None
+    parameters_json: dict = Field(default_factory=dict)
+
+
+class SegmentationQaRequest(BaseModel):
+    reference_dataset_id: UUID
+    iou_threshold: float = Field(default=0.5, ge=0.0, le=1.0)
+    class_name: str | None = None
+    min_confidence: float | None = Field(default=None, ge=0.0, le=1.0)
+
+
+class SegmentationRunResponse(BaseModel):
+    analysis_run_id: UUID
+    job_id: UUID
+    project_id: UUID
+    dataset_id: UUID
+    model_id: str
+    status: str
+    segmentation_count: int
+    error_code: str | None = None
+    message: str
+
+
+class SegmentationRunRead(BaseModel):
+    id: UUID
+    project_id: UUID
+    dataset_id: UUID | None = None
+    job_id: UUID | None = None
+    analysis_type: str
+    status: str
+    model_name: str | None = None
+    model_version: str | None = None
+    parameters_json: dict
+    result_json: dict | None = None
+    error_message: str | None = None
+    created_at: datetime | None = None
+    started_at: datetime | None = None
+    finished_at: datetime | None = None
+
+    model_config = {"from_attributes": True}
+
+
+class SegmentationRunListResponse(BaseModel):
+    items: list[SegmentationRunRead]
+    total: int
+
+
+class SegmentationRead(BaseModel):
+    id: UUID
+    project_id: UUID
+    dataset_id: UUID | None = None
+    analysis_run_id: UUID | None = None
+    job_id: UUID | None = None
+    model_name: str
+    model_version: str | None = None
+    class_name: str
+    confidence: float | None = None
+    bbox_json: dict | None = None
+    area_m2: float | None = None
+    mask_path: str | None = None
+    source_tile_path: str | None = None
+    tile_index: int | None = None
+    properties_json: dict | None = None
+    provenance_json: dict | None = None
+    created_at: datetime | None = None
+
+    model_config = {"from_attributes": True}
+
+
+class SegmentationListResponse(BaseModel):
+    items: list[SegmentationRead]
+    total: int