Datasets:
File size: 4,143 Bytes
0fa28ad | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 | #!/usr/bin/env python3
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()
|