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Yeva commited on
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dcf74a3
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verified ·
1 Parent(s): d0f7af7

Preserve nested prediction directories for page_ids containing "/"

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page_id can contain "/" (e.g. this dataset uses <source>/<page>), which prepare/run/convert scripts preserve as nested prediction directories. Use rglob instead of glob and mirror the relative path in the output dir, instead of flattening to the basename, so evaluate_from_hf.py can look predictions up by predictions_dir / f"{page_id}.csv".

evaluation_kit/convert_predictions_to_evaluation_csv.py CHANGED
@@ -106,20 +106,27 @@ def main() -> None:
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  args = parse_args()
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  args.output_dir.mkdir(parents=True, exist_ok=True)
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- prediction_files = sorted(args.predictions_dir.glob("*.json"))
 
 
 
 
 
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  if not prediction_files:
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  raise FileNotFoundError(f"No JSON files found in {args.predictions_dir}")
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  written = 0
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  skipped = 0
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  for pred_path in prediction_files:
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- output_path = args.output_dir / pred_path.with_suffix(".csv").name
 
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  if output_path.exists() and not args.overwrite:
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  skipped += 1
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  continue
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  predictions = load_predictions(pred_path)
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  rows = to_csv_rows(predictions, path=pred_path)
 
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  write_csv(rows, output_path)
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  written += 1
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  args = parse_args()
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  args.output_dir.mkdir(parents=True, exist_ok=True)
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+ # rglob (not glob): page_id can itself contain "/" (e.g. RLALT/ACoPPer uses
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+ # "<source>/<page>"), which prepare/run/convert scripts preserve as nested
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+ # prediction directories. evaluate_from_hf.py looks up predictions by
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+ # `predictions_dir / f"{page_id}.csv"`, i.e. it expects that same nested
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+ # layout to be mirrored here rather than flattened.
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+ prediction_files = sorted(args.predictions_dir.rglob("*.json"))
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  if not prediction_files:
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  raise FileNotFoundError(f"No JSON files found in {args.predictions_dir}")
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  written = 0
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  skipped = 0
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  for pred_path in prediction_files:
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+ relative_path = pred_path.relative_to(args.predictions_dir).with_suffix(".csv")
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+ output_path = args.output_dir / relative_path
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  if output_path.exists() and not args.overwrite:
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  skipped += 1
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  continue
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  predictions = load_predictions(pred_path)
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  rows = to_csv_rows(predictions, path=pred_path)
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+ output_path.parent.mkdir(parents=True, exist_ok=True)
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  write_csv(rows, output_path)
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  written += 1
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