from __future__ import annotations import argparse from pathlib import Path import pandas as pd def verify_split(split_dir: Path) -> int: csv_path = split_dir / "metadata.csv" if not csv_path.exists(): print(f"No metadata.csv in {split_dir}; skipping.") return 0 df = pd.read_csv(csv_path) # Normalize column access lower = {c.lower(): c for c in df.columns} ic = next((lower[c] for c in ("image", "file_name", "filename", "path") if c in lower), None) latc = next((lower[c] for c in ("latitude", "lat") if c in lower), None) lonc = next((lower[c] for c in ("longitude", "lon", "long") if c in lower), None) if ic is None or latc is None or lonc is None: print(f"Missing expected columns in {csv_path}: {df.columns.tolist()}") return 0 bad = 0 for i, row in df.iterrows(): img_rel = str(row[ic]) img_path = (split_dir / img_rel).resolve() if not img_path.exists(): print(f"[missing] {split_dir.name} row {i}: {img_rel}") bad += 1 continue lat = float(row[latc]) lon = float(row[lonc]) if not (-90.0 <= lat <= 90.0) or not (-180.0 <= lon <= 180.0): print(f"[range] {split_dir.name} row {i}: lat={lat}, lon={lon}") bad += 1 ok = len(df) - bad print(f"Split {split_dir.name}: {ok}/{len(df)} rows valid") return ok def main(): ap = argparse.ArgumentParser(description="Verify dataset metadata and paths for splits") ap.add_argument("--data-dir", type=Path, default=Path("data")) args = ap.parse_args() total_ok = 0 total = 0 for split in ("train", "validation", "test"): sd = args.data_dir / split if sd.exists(): ok = verify_split(sd) total_ok += ok csv_path = sd / "metadata.csv" if csv_path.exists(): import pandas as pd # local import total += len(pd.read_csv(csv_path)) if total: print(f"Overall: {total_ok}/{total} rows valid") if __name__ == "__main__": main()