| |
| import argparse |
| import json |
| import math |
| import sys |
| from pathlib import Path |
|
|
| from finixdoc_md_eval.omnidocbench_adapter import evaluate_md_dirs |
|
|
|
|
| def parse_args(): |
| parser = argparse.ArgumentParser( |
| description="Evaluate Markdown OCR/parsing results with text, reading-order, and table metrics." |
| ) |
| parser.add_argument("--gt_dir", required=True, help="Directory containing ground-truth .md files.") |
| parser.add_argument("--pred_dir", required=True, help="Directory containing prediction .md files.") |
| parser.add_argument( |
| "--output_json", |
| default="eval_result.json", |
| help="Path to write metric results. Default: eval_result.json", |
| ) |
| parser.add_argument( |
| "--allow_name_mismatch", |
| action="store_true", |
| help="Do not fail when gt/pred .md file names differ. Missing predictions are scored as empty.", |
| ) |
| return parser.parse_args() |
|
|
|
|
| def md_names(path): |
| return {p.name for p in Path(path).iterdir() if p.is_file() and p.suffix == ".md"} |
|
|
|
|
| def validate_inputs(gt_dir, pred_dir, allow_name_mismatch=False): |
| gt_path = Path(gt_dir) |
| pred_path = Path(pred_dir) |
| if not gt_path.is_dir(): |
| raise ValueError(f"GT directory does not exist: {gt_path}") |
| if not pred_path.is_dir(): |
| raise ValueError(f"Prediction directory does not exist: {pred_path}") |
|
|
| gt_files = md_names(gt_path) |
| pred_files = md_names(pred_path) |
| if not gt_files: |
| raise ValueError(f"No .md files found in GT directory: {gt_path}") |
| if not pred_files: |
| raise ValueError(f"No .md files found in prediction directory: {pred_path}") |
|
|
| missing = sorted(gt_files - pred_files) |
| extra = sorted(pred_files - gt_files) |
| if not allow_name_mismatch and (missing or extra): |
| message = [ |
| "GT and prediction .md file names must match.", |
| f"GT files: {len(gt_files)}", |
| f"Prediction files: {len(pred_files)}", |
| ] |
| if missing: |
| message.append(f"Missing predictions: {len(missing)}; first: {missing[0]}") |
| if extra: |
| message.append(f"Unexpected predictions: {len(extra)}; first: {extra[0]}") |
| raise ValueError(" ".join(message)) |
|
|
| return { |
| "gt_files": len(gt_files), |
| "pred_files": len(pred_files), |
| "missing_predictions": len(missing), |
| "unexpected_predictions": len(extra), |
| } |
|
|
|
|
| def rounded_metrics(metrics): |
| clean = {} |
| for key, value in metrics.items(): |
| if isinstance(value, float): |
| clean[key] = None if math.isnan(value) else round(value, 6) |
| else: |
| clean[key] = value |
| clean["score"] = clean["overall"] |
| return clean |
|
|
|
|
| def main(): |
| args = parse_args() |
| try: |
| input_summary = validate_inputs(args.gt_dir, args.pred_dir, args.allow_name_mismatch) |
| metrics = evaluate_md_dirs(args.gt_dir, args.pred_dir) |
| result = { |
| "success": True, |
| "metrics": rounded_metrics(metrics), |
| "inputs": input_summary, |
| } |
| output_path = Path(args.output_json) |
| output_path.parent.mkdir(parents=True, exist_ok=True) |
| output_path.write_text(json.dumps(result, ensure_ascii=False, indent=2), encoding="utf-8") |
|
|
| print("FinixDoc Markdown Evaluation") |
| print(f" samples: {metrics['num_samples']}") |
| print(f" text_block_Edit_dist: {metrics['text_block_Edit_dist']:.6f}") |
| print(f" reading_order_Edit_dist: {metrics['reading_order_Edit_dist']:.6f}") |
| print(f" table_TEDS: {metrics['table_TEDS']:.6f}") |
| print(f" overall: {metrics['overall']:.6f}") |
| print(f" result_json: {output_path}") |
| except Exception as exc: |
| result = { |
| "success": False, |
| "error": str(exc), |
| } |
| output_path = Path(args.output_json) |
| output_path.parent.mkdir(parents=True, exist_ok=True) |
| output_path.write_text(json.dumps(result, ensure_ascii=False, indent=2), encoding="utf-8") |
| print(f"Evaluation failed: {exc}", file=sys.stderr) |
| sys.exit(1) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
