JensandClaude Opus 5
12aaf1bb4d
Change detection was the one analysis that ignored the selection entirely. It compared two datasets in full, loaded every feature of both into Python with no spatial predicate, and — with include_unchanged defaulting to true — returned a FeatureCollection holding both datasets. For a regional building layer that is the wrong answer to "what changed here" and a response no browser should be asked to hold. It now accepts bbox and area_id, resolved the way every other analysis resolves them, and loads through an indexed ST_Intersects predicate. Features are deliberately not clipped to the selection. A change class describes a whole object: comparing a clipped earlier footprint against an unclipped later one would report the selection edge itself as a change. Objects the edge crosses are compared in full and counted in a warning. The returned geometry is capped by preview_limit, spending that budget on modified, added and removed before unchanged, while every count still describes the whole selection. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
47 lines
1.9 KiB
Python
47 lines
1.9 KiB
Python
from __future__ import annotations
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from fastapi import APIRouter, Depends
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from sqlalchemy.orm import Session
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from app.core.errors import AppError
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from app.db.session import get_db
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from app.models import Dataset
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from app.schemas import Envelope, JobRead
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from app.schemas.analysis import ChangeDetectionRequest
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from app.services.change_detection_service import ChangeDetectionService
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from app.services.job_service import JobService
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from app.utils.response import envelope
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router = APIRouter(prefix="/analysis", tags=["analysis"])
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@router.post("/change-detection", response_model=Envelope[JobRead])
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def run_change_detection(
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payload: ChangeDetectionRequest,
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db: Session = Depends(get_db),
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) -> dict:
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source_dataset = db.get(Dataset, payload.source_dataset_id)
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if not source_dataset:
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raise AppError(code="DATASET_NOT_FOUND", message="Source dataset not found", status_code=404)
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ChangeDetectionService._get_project_vector_dataset(db, payload.source_dataset_id, source_dataset.project_id, "Source")
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job = JobService.run_sync_job(
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db=db,
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project_id=source_dataset.project_id,
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job_type="analysis.change-detection",
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parameters=payload.model_dump(mode="json"),
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input_dataset_id=payload.source_dataset_id,
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operation=lambda: ChangeDetectionService.compare_vector_datasets(
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db=db,
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project_id=source_dataset.project_id,
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source_dataset_id=payload.source_dataset_id,
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target_dataset_id=payload.target_dataset_id,
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iou_threshold=payload.iou_threshold,
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modified_threshold=payload.modified_threshold,
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include_unchanged=payload.include_unchanged,
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bbox=payload.bbox.model_dump() if payload.bbox is not None else None,
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area_id=payload.area_id,
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preview_limit=payload.preview_limit,
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).model_dump(mode="json"),
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)
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return envelope(job)
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