matthias
aae57d7a2b
date/time, price per litre, litres, discount, total) from German fuel receipt photos: grayscale + mild bilateral filter + contrast stretch, Tesseract OCR, then LLM structuring via a small local model (Qwen 2.5, served by Ollama). Each step is independently runnable and inspectable through numbered scripts against a shared tooling container.
95 lines
3.1 KiB
Python
95 lines
3.1 KiB
Python
#!/usr/bin/env python3
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"""Test-only tool: compare a directory of extracted.json results (produced
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by running 1_preprocess_image.sh/2_ocr_image.sh/3_extract_data.sh over a
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set of receipts) against the ground-truth spreadsheet, matching rows by
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date and reporting per-field accuracy."""
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import argparse
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import glob
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import json
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import os
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from odf.opendocument import load
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from odf.table import Table, TableRow, TableCell
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from odf.text import P
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def load_ground_truth(ods_path: str) -> dict:
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doc = load(ods_path)
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table = doc.spreadsheet.getElementsByType(Table)[0]
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rows = table.getElementsByType(TableRow)
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gt = {}
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for r in rows[1:]:
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cells = r.getElementsByType(TableCell)
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vals = []
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for c in cells:
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ps = c.getElementsByType(P)
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vals.append(" ".join(str(p) for p in ps))
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if not vals or not vals[0]:
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continue
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date = vals[0]
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try:
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gt[date] = {
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"time": vals[1],
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"price_per_litre": float(vals[2].replace(",", ".")) if vals[2] else None,
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"litres": float(vals[3].replace(",", ".")) if vals[3] else None,
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"discount": float(vals[4].replace("€", "").replace(",", ".").strip()) if vals[4] else None,
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"total_price": float(vals[5].replace("€", "").replace(",", ".").strip()) if vals[5] else None,
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}
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except (ValueError, IndexError):
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continue
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return gt
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def close(a, b, tol=0.05):
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if a is None or b is None:
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return a is None and b is None
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return abs(abs(a) - abs(b)) <= tol
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("-gt", dest="ods_path", required=True, help="path to ground-truth .ods")
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parser.add_argument("-results", dest="results_dir", required=True,
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help="directory containing one subdirectory per receipt, each with an extracted.json")
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args = parser.parse_args()
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gt = load_ground_truth(args.ods_path)
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fields = ["price_per_litre", "litres", "discount", "total_price"]
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field_ok = {k: 0 for k in fields}
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field_total = {k: 0 for k in fields}
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matched = 0
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total = 0
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for json_path in sorted(glob.glob(os.path.join(args.results_dir, "*", "extracted.json"))):
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receipt = os.path.basename(os.path.dirname(json_path))
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total += 1
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with open(json_path, "r", encoding="utf-8") as f:
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data = json.load(f)
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truth = gt.get(data.get("date"))
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if not truth:
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print(f"{receipt}: NO DATE MATCH (extracted date={data.get('date')!r})")
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continue
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matched += 1
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bad = []
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for k in fields:
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field_total[k] += 1
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ok = close(data.get(k), truth[k])
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if ok:
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field_ok[k] += 1
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else:
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bad.append(k)
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status = "OK" if not bad else f"WRONG FIELDS {bad}"
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print(f"{receipt}: {status}")
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print("\n=== SUMMARY ===")
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print(f"Receipts matched to ground truth: {matched}/{total}")
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for k in fields:
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print(f" {k}: {field_ok[k]}/{field_total[k]} correct")
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if __name__ == "__main__":
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main()
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