Page GRB references for operator samples
GeoIntel CI / docs-smoke (push) Has been cancelled
GeoIntel CI / contract-smoke (push) Has been cancelled

This commit is contained in:
Codex
2026-07-09 15:02:12 +02:00
parent 77c45937c6
commit a63d4eaadc
8 changed files with 254 additions and 12 deletions
+8
View File
@@ -7,6 +7,14 @@
# Changelog
## Sprint 152 GRB reference paging for operator samples (2026-07-09)
- Fixed the operator real-data sample preparer so GRB GBG reference GeoJSON is fetched through OGC API `rel=next` pagination links instead of stopping at the first `limit=1000` page.
- Added `--reference-page-limit` / `OPERATOR_GRB_PAGE_LIMIT` and `--reference-max-features` / `OPERATOR_GRB_MAX_FEATURES` safeguards for dense reference AOIs.
- Generated reference GeoJSON now records fetched page URLs, page count, truncation state and paging limits for auditability.
- Added regression coverage for paged GRB responses and the new CLI help options.
- No application provider endpoint, migration, API contract, live GRB product import, model download or active YOLO model changed.
## Sprint 151 runtime GIS upload and AOI1024 YOLO candidate (2026-07-09)
- Fixed the operator YOLO training wrapper so the all-in-one runtime defaults to `/opt/geointel/venv/bin/python` when present, while still falling back to `python3` for local shells.
@@ -46,6 +46,8 @@ def test_prepare_operator_real_data_samples_help_does_not_require_gis_dependenci
assert "--width" in result.stdout
assert "--height" in result.stdout
assert "--half-size-scale" in result.stdout
assert "--reference-page-limit" in result.stdout
assert "--reference-max-features" in result.stdout
def test_multi_sample_detection_quality_matrix_runs_existing_matrix_for_each_sample() -> None:
@@ -123,6 +123,81 @@ def test_background_candidate_can_write_empty_reference_geojson(tmp_path: Path,
assert '"sample_role": "background_candidate"' in payload
def test_fetch_reference_follows_grb_next_links_until_complete(tmp_path: Path, monkeypatch) -> None:
module = load_sample_preparer()
requested: list[tuple[str, dict | None]] = []
def feature(feature_id: str) -> dict:
return {
"type": "Feature",
"id": feature_id,
"geometry": {"type": "Polygon", "coordinates": []},
"properties": {},
}
class FeatureResponse:
def __init__(self, payload: dict) -> None:
self.payload = payload
def raise_for_status(self) -> None:
return None
def json(self) -> dict:
return self.payload
class FakeRequests:
Request = module.requests.Request if module.requests else object
@staticmethod
def get(url, params=None, timeout=120):
requested.append((url, params))
if len(requested) == 1:
return FeatureResponse(
{
"type": "FeatureCollection",
"features": [feature("GBG.1")],
"numberReturned": 1,
"links": [
{
"rel": "next",
"type": "application/geo+json",
"href": "https://example.test/grb?page=2",
}
],
}
)
return FeatureResponse(
{
"type": "FeatureCollection",
"features": [feature("GBG.2")],
"numberReturned": 1,
"links": [],
}
)
monkeypatch.setattr(module, "requests", FakeRequests)
monkeypatch.setattr(module, "prepared_url", lambda url, params: f"{url}?prepared=true")
sample = module.OperatorSample(
slug="urban",
display_name="Urban",
center_lon=5.0,
center_lat=51.0,
)
source_url, feature_count = module.fetch_reference(sample, tmp_path / "urban.geojson", [4.9, 50.9, 5.1, 51.1])
payload = (tmp_path / "urban.geojson").read_text(encoding="utf-8")
assert source_url.endswith("?prepared=true")
assert feature_count == 2
assert requested == [
(module.GRB_GBG_URL, {"f": "application/geo+json", "limit": "1000", "bbox": "4.90000000,50.90000000,5.10000000,51.10000000"}),
("https://example.test/grb?page=2", None),
]
assert '"id": "GBG.1"' in payload
assert '"id": "GBG.2"' in payload
def test_reference_sample_still_rejects_empty_grb_response(tmp_path: Path, monkeypatch) -> None:
module = load_sample_preparer()
+9 -4
View File
@@ -196,10 +196,15 @@ The helper fetches explicit Digitaal Vlaanderen orthophoto/GRB GBG sample pairs
for the documented AOIs only and writes `operator_samples_manifest.json`. The
default corpus includes dense reference AOIs for Geel, Mol, Turnhout, Herentals,
Balen, Retie and Westerlo plus explicitly marked background candidates for
Postel-bos, Lommel-heide and Kasterlee-bos. Background candidates may persist
empty GRB FeatureCollections for negative-tile training; normal reference AOIs
still fail on empty GRB responses. The application itself still does not perform
live provider fetching.
Postel-bos, Lommel-heide, Kasterlee-bos, Dessel-heide, Ravels-bos,
Meerhout-bos, Geel-Bel, Arendonk-heide and Herenthout-bos. Background
candidates may persist empty GRB FeatureCollections for negative-tile training;
normal reference AOIs still fail on empty GRB responses. Dense GRB references
are fetched through OGC API `rel=next` pagination links instead of trusting only
the first 1000-feature page. Generated reference GeoJSON records
`reference_pages_fetched`, `reference_truncated`, `reference_page_limit`,
`reference_max_features` and `source_urls` for auditability. The application
itself still does not perform live provider fetching.
For confidence-threshold calibration, use the sweep wrapper:
+26
View File
@@ -5938,6 +5938,32 @@ Open:
- Use `yolo-building-tile-uniquehardneg160` as the next safer hard-negative training dataset candidate. Benchmark after training before changing defaults.
# Sprint 152 - GRB reference paging for operator samples
## What changed
- Fixed `scripts/prepare_operator_real_data_samples.py` so GRB GBG reference exports follow OGC API `rel=next` pagination links instead of silently trusting only the first `limit=1000` page.
- Added operator controls:
- `--reference-page-limit` / `OPERATOR_GRB_PAGE_LIMIT`, default `1000`.
- `--reference-max-features` / `OPERATOR_GRB_MAX_FEATURES`, default `100000`.
- Generated reference GeoJSON now records `source_urls`, `reference_pages_fetched`, `reference_truncated`, `reference_page_limit` and `reference_max_features`.
- Kept the change operator-only: no GeoIntel API route calls this helper, no product provider endpoint changed, no live GRB/OSM import was added, no migration changed and no YOLO model was activated.
## What was tested
- RED: `python -m pytest backend\tests\test_sprint131_operator_sample_expansion.py::test_fetch_reference_follows_grb_next_links_until_complete -q` failed because only the first GRB page was persisted.
- GREEN: `python -m pytest backend\tests\test_sprint131_operator_sample_expansion.py::test_fetch_reference_follows_grb_next_links_until_complete -q`
- `python -m pytest backend\tests\test_sprint127_operator_sample_quality_matrix.py backend\tests\test_sprint131_operator_sample_expansion.py -q`
## Known limitations
- Existing Tower AOI1024 artifacts were generated before this fix. Regenerate the operator samples with `--force` before retraining or re-auditing dense AOI labels.
- This does not make the Sprint 7B GRB provider a live product importer; it only fixes explicit operator sample preparation.
## Next recommended pass
- Regenerate `/app/storage/operator-data/operator-samples-1024` on Tower with the paged script, re-export the AOI1024 YOLO tile dataset, rerun the dataset audit and only then consider another inactive training candidate.
# Sprint 151 - Runtime GIS upload and AOI1024 YOLO candidate
## What changed
+2 -1
View File
@@ -472,5 +472,6 @@ This file now starts with the current implementation status. Older preparation/b
- [x] Run AOI1024 background/hard-negative matrix for `geointel-building-yolov8s-aoi1024visible025e50-pt`.
- [x] Fix promotion-report parsing for `multi_sample_quality_summary.json` inputs.
- [x] Generate AOI1024 promotion report and keep recommended candidate as `none`.
- [ ] Add GRB paging or smaller dense AOI sampling before trusting 1000-feature-capped dense reference exports as full ground truth.
- [x] Add GRB paging before trusting dense reference exports as full ground truth.
- [ ] Regenerate Tower AOI1024 operator samples with paged GRB references, then re-export and audit labels before any new training attempt.
- [ ] Keep every local YOLO candidate inactive until positive-AOI and hard-negative promotion reports recommend default activation.
+11
View File
@@ -190,6 +190,15 @@ returns no buildings; background candidates are explicitly marked with
negative-tile training. The helper fetches only the explicit documented AOIs,
records Digitaal Vlaanderen attribution and reuses existing files by default.
Use `--force` only when the local runtime artifacts should be regenerated.
GRB building references are fetched through the provider's OGC API
`rel=next` pagination links, so dense AOIs are not silently limited to the
first 1000 features. The default page size is `1000`; override it with
`--reference-page-limit` or `OPERATOR_GRB_PAGE_LIMIT`. The safety cap defaults
to `100000` features per sample and can be adjusted with
`--reference-max-features` or `OPERATOR_GRB_MAX_FEATURES`. Generated reference
GeoJSON files record `reference_pages_fetched`, `reference_truncated`,
`reference_page_limit`, `reference_max_features` and every fetched
`source_urls` page for auditability.
For model-training candidates, prepare a larger operator-only sample manifest so
tile overlap can create meaningful context instead of one tile per source
@@ -202,6 +211,8 @@ docker exec -it geointel python3 /app/scripts/prepare_operator_real_data_samples
--width 1024 \
--height 1024 \
--half-size-scale 2 \
--reference-page-limit 1000 \
--reference-max-features 100000 \
--force
```
+121 -7
View File
@@ -20,6 +20,8 @@ from typing import Any
WMS_URL = "https://geo.api.vlaanderen.be/omwrgbmrvl/wms"
GRB_GBG_URL = "https://geo.api.vlaanderen.be/GRB/ogc/features/v1/collections/GBG/items"
DEFAULT_OUTPUT_DIR = Path("/app/storage/operator-data")
DEFAULT_GRB_PAGE_LIMIT = 1000
DEFAULT_GRB_MAX_FEATURES = 100000
requests: Any = None
rasterio: Any = None
Transformer: Any = None
@@ -214,6 +216,18 @@ def parse_args() -> argparse.Namespace:
default=float(os.environ.get("OPERATOR_SAMPLE_HALF_SIZE_SCALE", "1")),
help="Multiplier applied to each documented AOI half-size in meters.",
)
parser.add_argument(
"--reference-page-limit",
type=int,
default=int(os.environ.get("OPERATOR_GRB_PAGE_LIMIT", str(DEFAULT_GRB_PAGE_LIMIT))),
help="GRB OGC API Features page size for reference buildings.",
)
parser.add_argument(
"--reference-max-features",
type=int,
default=int(os.environ.get("OPERATOR_GRB_MAX_FEATURES", str(DEFAULT_GRB_MAX_FEATURES))),
help="Safety cap for paged GRB reference features per sample.",
)
return parser.parse_args()
@@ -316,6 +330,45 @@ def sample_artifact_paths(sample: OperatorSample, output_dir: Path) -> tuple[Pat
return ortho_path, reference_path
def next_geojson_link(payload: dict[str, Any]) -> str | None:
for link in payload.get("links") or []:
if link.get("rel") == "next" and "geo+json" in str(link.get("type", "")).lower():
href = link.get("href")
if href:
return str(href)
for link in payload.get("links") or []:
if link.get("rel") == "next":
href = link.get("href")
if href:
return str(href)
return None
def merge_reference_page_features(
pages: list[dict[str, Any]],
*,
max_features: int,
) -> tuple[list[dict[str, Any]], bool]:
features: list[dict[str, Any]] = []
seen_feature_keys: set[str] = set()
truncated = False
for page in pages:
for feature in page.get("features") or []:
feature_key = str(feature.get("id") or json.dumps(feature.get("geometry"), sort_keys=True))
if feature_key in seen_feature_keys:
continue
if len(features) >= max_features:
truncated = True
break
seen_feature_keys.add(feature_key)
features.append(feature)
if truncated:
break
return features, truncated
def fetch_orthophoto(sample: OperatorSample, ortho_path: Path, lambert_bbox: tuple[float, float, float, float]) -> str:
minx, miny, maxx, maxy = lambert_bbox
wms_params = {
@@ -362,27 +415,69 @@ def fetch_orthophoto(sample: OperatorSample, ortho_path: Path, lambert_bbox: tup
return prepared_url(WMS_URL, wms_params)
def fetch_reference(sample: OperatorSample, reference_path: Path, geo_bbox: list[float]) -> tuple[str, int]:
def fetch_reference(
sample: OperatorSample,
reference_path: Path,
geo_bbox: list[float],
*,
page_limit: int = DEFAULT_GRB_PAGE_LIMIT,
max_features: int = DEFAULT_GRB_MAX_FEATURES,
) -> tuple[str, int]:
if page_limit <= 0:
raise SystemExit("--reference-page-limit must be a positive integer")
if max_features <= 0:
raise SystemExit("--reference-max-features must be a positive integer")
ogc_params = {
"f": "application/geo+json",
"limit": "1000",
"limit": str(page_limit),
"bbox": ",".join(f"{value:.8f}" for value in geo_bbox),
}
pages: list[dict[str, Any]] = []
page_urls = [prepared_url(GRB_GBG_URL, ogc_params)]
response = requests.get(GRB_GBG_URL, params=ogc_params, timeout=120)
response.raise_for_status()
reference = response.json()
features = reference.get("features") or []
seen_next_urls: set[str] = set()
stopped_at_feature_cap = False
while True:
response.raise_for_status()
page = response.json()
pages.append(page)
next_url = next_geojson_link(page)
if not next_url:
break
if next_url in seen_next_urls:
raise SystemExit(f"GRB GBG pagination loop detected for {sample.slug}: {next_url}")
if sum(len(current_page.get("features") or []) for current_page in pages) >= max_features:
stopped_at_feature_cap = True
break
seen_next_urls.add(next_url)
page_urls.append(next_url)
response = requests.get(next_url, params=None, timeout=120)
reference = pages[0] if pages else {"type": "FeatureCollection", "features": []}
features, truncated = merge_reference_page_features(pages, max_features=max_features)
truncated = truncated or stopped_at_feature_cap
if not features and not sample.allow_empty_reference:
raise SystemExit(f"GRB GBG returned no building features for {sample.slug} bbox {geo_bbox}")
reference["features"] = features
reference["name"] = f"GRB GBG buildings - {sample.display_name} sample AOI"
reference["source"] = "Digitaal Vlaanderen GRB OGC API Features collection GBG"
reference["source_url"] = prepared_url(GRB_GBG_URL, ogc_params)
reference["source_urls"] = page_urls
reference["attribution"] = "Bron: Grootschalig Referentie Bestand Vlaanderen, Digitaal Vlaanderen"
reference["bbox"] = geo_bbox
reference["sample_slug"] = sample.slug
reference["sample_role"] = sample.sample_role
reference["allow_empty_reference"] = sample.allow_empty_reference
reference["reference_page_limit"] = page_limit
reference["reference_max_features"] = max_features
reference["reference_pages_fetched"] = len(pages)
reference["reference_truncated"] = truncated
reference["numberReturned"] = len(features)
if "links" in reference:
reference["links"] = [link for link in reference.get("links") or [] if link.get("rel") != "next"]
for feature in features:
props = feature.setdefault("properties", {})
props.setdefault("source_name", "grb")
@@ -394,7 +489,14 @@ def fetch_reference(sample: OperatorSample, reference_path: Path, geo_bbox: list
return prepared_url(GRB_GBG_URL, ogc_params), len(features)
def prepare_sample(sample: OperatorSample, output_dir: Path, force: bool) -> dict[str, Any]:
def prepare_sample(
sample: OperatorSample,
output_dir: Path,
force: bool,
*,
reference_page_limit: int = DEFAULT_GRB_PAGE_LIMIT,
reference_max_features: int = DEFAULT_GRB_MAX_FEATURES,
) -> dict[str, Any]:
ortho_path, reference_path = sample_artifact_paths(sample, output_dir)
lambert_bbox, geo_bbox = sample_bounds(sample)
skip_existing = ortho_path.exists() and reference_path.exists() and not force
@@ -402,7 +504,13 @@ def prepare_sample(sample: OperatorSample, output_dir: Path, force: bool) -> dic
source_urls: dict[str, str | None] = {"orthophoto": None, "reference": None}
if not skip_existing:
source_urls["orthophoto"] = fetch_orthophoto(sample, ortho_path, lambert_bbox)
source_urls["reference"], reference_feature_count = fetch_reference(sample, reference_path, geo_bbox)
source_urls["reference"], reference_feature_count = fetch_reference(
sample,
reference_path,
geo_bbox,
page_limit=reference_page_limit,
max_features=reference_max_features,
)
else:
reference_feature_count = geojson_feature_count(reference_path)
@@ -424,6 +532,8 @@ def prepare_sample(sample: OperatorSample, output_dir: Path, force: bool) -> dic
"epsg31370_bbox": list(lambert_bbox),
"skip_existing": skip_existing,
"source_urls": source_urls,
"reference_page_limit": reference_page_limit,
"reference_max_features": reference_max_features,
"attribution": {
"orthophoto": "Bron: Orthofotomozaiek Vlaanderen, Digitaal Vlaanderen",
"reference": "Bron: Grootschalig Referentie Bestand Vlaanderen, Digitaal Vlaanderen",
@@ -470,6 +580,8 @@ def main() -> int:
),
output_dir,
force=args.force,
reference_page_limit=args.reference_page_limit,
reference_max_features=args.reference_max_features,
)
for sample in selected_samples(args.samples)
]
@@ -482,6 +594,8 @@ def main() -> int:
"sample_width": args.width,
"sample_height": args.height,
"half_size_scale": args.half_size_scale,
"reference_page_limit": args.reference_page_limit,
"reference_max_features": args.reference_max_features,
"samples": samples,
}
manifest_path = output_dir / args.manifest_name