Files
geointel/scripts/build_regional_yolo_dataset.py
T
Jens e5a642a7f7
GeoIntel release gates / Compile, test, contracts and builds (push) Canceled after 0s
GeoIntel release gates / Python and npm vulnerability policy (push) Canceled after 0s
GeoIntel release gates / GIS image, SBOM and container scan (push) Canceled after 0s
Add auditable SAM roof label refinement
2026-07-27 06:46:42 +02:00

78 lines
2.9 KiB
Python

#!/usr/bin/env python3
"""Create a checksummed regional YOLO view without copying protected data."""
from __future__ import annotations
import argparse
import hashlib
import json
from pathlib import Path
from typing import Any
def sha256(path: Path) -> str:
digest = hashlib.sha256()
with path.open("rb") as stream:
for chunk in iter(lambda: stream.read(1024 * 1024), b""):
digest.update(chunk)
return digest.hexdigest()
def select_paths(summary: dict[str, Any], manifest: dict[str, Any], region: str) -> tuple[list[str], list[str]]:
samples = {item["sample_slug"]: item for item in manifest["samples"]}
train: list[str] = []
val: list[str] = []
for tile in summary["tiles"]:
sample = samples[tile["sample_slug"]]
if sample["region"] != region or not tile.get("kept", True):
continue
if sample["split"] == "train" and tile["split"] == "train":
train.append(tile["image_path"])
elif sample["split"] == "val" and tile["split"] == "val":
val.append(tile["image_path"])
if not train or not val:
raise ValueError(f"Region {region!r} must contain train and validation images")
return sorted(train), sorted(val)
def main() -> int:
parser = argparse.ArgumentParser()
parser.add_argument("--summary", type=Path, required=True)
parser.add_argument("--corpus-manifest", type=Path, required=True)
parser.add_argument("--region", required=True)
parser.add_argument("--output-dir", type=Path, required=True)
args = parser.parse_args()
summary = json.loads(args.summary.read_text(encoding="utf-8"))
manifest = json.loads(args.corpus_manifest.read_text(encoding="utf-8"))
train, val = select_paths(summary, manifest, args.region)
args.output_dir.mkdir(parents=True, exist_ok=True)
train_list = args.output_dir / "train.txt"
val_list = args.output_dir / "val.txt"
train_list.write_text("\n".join(train) + "\n", encoding="utf-8")
val_list.write_text("\n".join(val) + "\n", encoding="utf-8")
dataset_yaml = args.output_dir / "dataset.yaml"
dataset_yaml.write_text(
f"path: {args.output_dir}\ntrain: {train_list}\nval: {val_list}\nnames:\n 0: building\n",
encoding="utf-8",
)
evidence = {
"schema_version": 1,
"status": "ok",
"region": args.region,
"train_image_count": len(train),
"validation_image_count": len(val),
"summary": str(args.summary),
"summary_sha256": sha256(args.summary),
"corpus_manifest": str(args.corpus_manifest),
"corpus_manifest_sha256": sha256(args.corpus_manifest),
"dataset_yaml": str(dataset_yaml),
"protected_splits_in_training": [],
}
(args.output_dir / "regional-dataset.json").write_text(json.dumps(evidence, indent=2), encoding="utf-8")
print(json.dumps(evidence, indent=2))
return 0
if __name__ == "__main__":
raise SystemExit(main())