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page detection and segmentation results instead of returning all of them

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/detection/runs/{id}/detections and its GeoJSON sibling returned every
persisted detection, as did the segmentation equivalents. A regional run holds
tens of thousands, and these are the endpoints the results table and the map
overlay call after every run.

They now take limit and offset, default to 2.000, and report total, limit,
offset and truncated so the complete population stays visible while what is
transferred does not. The GeoJSON responses carry the same window in a
geointel_result_window foreign member.

Rows are ordered by confidence, so a capped overlay draws the strongest
detections rather than an arbitrary slice, and the lab says how many of how
many are being shown rather than silently presenting a page as the whole run.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
This commit is contained in:
Jens
2026-08-22 15:24:46 +02:00
co-authored by Claude Opus 5
parent 5278fcd361
commit 5b3839dc89
12 changed files with 271 additions and 8 deletions
Download Patch File Download Diff File Expand all files Collapse all files
backend/app/api/routes/detection.py
+33 -1
View File
@@ -2,7 +2,7 @@ from __future__ import annotations
from uuid import UUID
from fastapi import APIRouter, Depends
from fastapi import APIRouter, Depends, Query
from sqlalchemy.orm import Session
from app.db.session import get_db
@@ -118,6 +118,13 @@ def list_detection_run_detections(
dataset_id: UUID | None = None,
class_name: str | None = None,
min_confidence: float | None = None,
limit: int = Query(
default=DetectionService.DEFAULT_RESULT_LIMIT,
ge=0,
le=50_000,
description="Maximum results to return; 0 returns everything. Highest confidence first.",
),
offset: int = Query(default=0, ge=0),
db: Session = Depends(get_db),
) -> dict:
return envelope(
@@ -127,6 +134,8 @@ def list_detection_run_detections(
dataset_id=dataset_id,
class_name=class_name,
min_confidence=min_confidence,
limit=limit,
offset=offset,
).model_dump()
)
@@ -140,6 +149,13 @@ def list_dataset_detections(
analysis_run_id: UUID | None = None,
class_name: str | None = None,
min_confidence: float | None = None,
limit: int = Query(
default=DetectionService.DEFAULT_RESULT_LIMIT,
ge=0,
le=50_000,
description="Maximum results to return; 0 returns everything. Highest confidence first.",
),
offset: int = Query(default=0, ge=0),
db: Session = Depends(get_db),
) -> dict:
return envelope(
@@ -149,6 +165,8 @@ def list_dataset_detections(
dataset_id=dataset_id,
class_name=class_name,
min_confidence=min_confidence,
limit=limit,
offset=offset,
).model_dump()
)
@@ -166,11 +184,18 @@ def get_detection_run_geojson(
analysis_run_id: UUID,
class_name: str | None = None,
min_confidence: float | None = None,
limit: int = Query(
default=DetectionService.DEFAULT_RESULT_LIMIT,
ge=0,
le=50_000,
description="Maximum results to return; 0 returns everything. Highest confidence first.",
),
db: Session = Depends(get_db),
) -> dict:
return envelope(
DetectionService.detections_to_geojson(
db,
limit=limit,
analysis_run_id=analysis_run_id,
class_name=class_name,
min_confidence=min_confidence,
@@ -187,11 +212,18 @@ def get_dataset_detection_geojson(
analysis_run_id: UUID | None = None,
class_name: str | None = None,
min_confidence: float | None = None,
limit: int = Query(
default=DetectionService.DEFAULT_RESULT_LIMIT,
ge=0,
le=50_000,
description="Maximum results to return; 0 returns everything. Highest confidence first.",
),
db: Session = Depends(get_db),
) -> dict:
return envelope(
DetectionService.detections_to_geojson(
db,
limit=limit,
analysis_run_id=analysis_run_id,
dataset_id=dataset_id,
class_name=class_name,
backend/app/api/routes/segmentation.py
+34 -1
View File
@@ -2,7 +2,7 @@ from __future__ import annotations
from uuid import UUID
from fastapi import APIRouter, Depends
from fastapi import APIRouter, Depends, Query
from sqlalchemy.orm import Session
from app.db.session import get_db
@@ -21,6 +21,7 @@ from app.schemas import (
SegmentationRunResponse,
)
from app.services.model_registry_service import ModelRegistryService
from app.services.detection_service import DetectionService
from app.services.segmentation_service import SegmentationService
from app.utils.response import envelope
@@ -91,11 +92,20 @@ def list_segmentation_run_outputs(
dataset_id: UUID | None = None,
class_name: str | None = None,
min_confidence: float | None = None,
limit: int = Query(
default=DetectionService.DEFAULT_RESULT_LIMIT,
ge=0,
le=50_000,
description="Maximum results to return; 0 returns everything. Highest confidence first.",
),
offset: int = Query(default=0, ge=0),
db: Session = Depends(get_db),
) -> dict:
return envelope(
SegmentationService.list_segmentations(
db,
limit=limit,
offset=offset,
analysis_run_id=analysis_run_id,
dataset_id=dataset_id,
class_name=class_name,
@@ -113,11 +123,20 @@ def list_dataset_segmentations(
analysis_run_id: UUID | None = None,
class_name: str | None = None,
min_confidence: float | None = None,
limit: int = Query(
default=DetectionService.DEFAULT_RESULT_LIMIT,
ge=0,
le=50_000,
description="Maximum results to return; 0 returns everything. Highest confidence first.",
),
offset: int = Query(default=0, ge=0),
db: Session = Depends(get_db),
) -> dict:
return envelope(
SegmentationService.list_segmentations(
db,
limit=limit,
offset=offset,
analysis_run_id=analysis_run_id,
dataset_id=dataset_id,
class_name=class_name,
@@ -139,11 +158,18 @@ def get_segmentation_run_geojson(
analysis_run_id: UUID,
class_name: str | None = None,
min_confidence: float | None = None,
limit: int = Query(
default=DetectionService.DEFAULT_RESULT_LIMIT,
ge=0,
le=50_000,
description="Maximum results to return; 0 returns everything. Highest confidence first.",
),
db: Session = Depends(get_db),
) -> dict:
return envelope(
SegmentationService.segmentations_to_geojson(
db,
limit=limit,
analysis_run_id=analysis_run_id,
class_name=class_name,
min_confidence=min_confidence,
@@ -160,11 +186,18 @@ def get_dataset_segmentation_geojson(
analysis_run_id: UUID | None = None,
class_name: str | None = None,
min_confidence: float | None = None,
limit: int = Query(
default=DetectionService.DEFAULT_RESULT_LIMIT,
ge=0,
le=50_000,
description="Maximum results to return; 0 returns everything. Highest confidence first.",
),
db: Session = Depends(get_db),
) -> dict:
return envelope(
SegmentationService.segmentations_to_geojson(
db,
limit=limit,
analysis_run_id=analysis_run_id,
dataset_id=dataset_id,
class_name=class_name,