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b510add | 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 | """Post-traitement métier des lectures du CRNN : normalisation numérique,
calcul du montant/litres manquant, vérification de cohérence.
Contrairement au pipeline OCR générique (qui doit deviner quel nombre
correspond à quel champ par proximité de libellé ou par magnitude), le CRNN
étiquette déjà chaque ligne lue ("prix" = montant, "volume" = litres,
"prix_litre" = prix unitaire affiché) grâce au découpage positionnel — il
n'y a donc pas d'ambiguïté champ/valeur à résoudre ici.
"""
from typing import Any, Dict, List, Optional
import re
from .config import RuleConfig, load_config
NUMBER_RE = re.compile(r"[-+]?[0-9]+[\.,]?[0-9]*")
def _norm_number(s: str) -> Optional[float]:
"""Normalise un nombre lu par le CRNN (virgule/point, espaces) en float."""
if not s:
return None
s = s.strip().replace(" ", "").replace("\xa0", "")
m = NUMBER_RE.search(s)
if not m:
return None
s = m.group(0)
if "," in s and "." in s:
s = s.replace(",", "")
elif s.count(",") == 1 and s.count(".") == 0:
s = s.replace(",", ".")
try:
return float(s)
except ValueError:
return None
def evaluate_consistency(liters: Optional[float], amount: Optional[float],
price: Optional[float], tol: Optional[float] = None,
cfg: Optional[RuleConfig] = None) -> Dict[str, Any]:
"""Vérifie montant == litres x prix (§5.5/§10 du cahier des charges)."""
if cfg is None:
cfg = load_config()
if tol is None:
tol = cfg.consistency_tolerance
out = {"is_consistent": None, "calculated_amount": None, "calculated_liters": None}
if liters is not None and price is not None:
calc_amt = liters * price
out["calculated_amount"] = round(calc_amt, 2)
if amount is not None:
out["is_consistent"] = abs(amount - calc_amt) / max(1.0, calc_amt) <= tol
if amount is not None and price is not None and liters is None:
calc_l = amount / price if price != 0 else None
out["calculated_liters"] = round(calc_l, 2) if calc_l is not None else None
return out
def process(recognized_fields: List[Dict[str, Any]],
fuel_price: Optional[float] = None,
cfg: Optional[RuleConfig] = None) -> Dict[str, Any]:
"""Convertit les lignes lues par le CRNN en résultat métier structuré.
Args:
recognized_fields: sortie de `recognizer.recognize_screen` :
liste de {'field': 'prix'|'volume'|'prix_litre', 'text', 'confidence'}
fuel_price: prix du litre configuré côté YELY (fait toujours autorité
sur un prix lu à l'écran — règle métier n°1 du cahier des charges).
"""
if cfg is None:
cfg = load_config()
by_field = {f["field"]: f for f in recognized_fields if f.get("field")}
amount_val = _norm_number(by_field.get("prix", {}).get("text", ""))
liters_val = _norm_number(by_field.get("volume", {}).get("text", ""))
screen_price_val = _norm_number(by_field.get("prix_litre", {}).get("text", ""))
# Le prix configuré côté YELY fait autorité ; le prix lu à l'écran n'est
# utilisé que si l'appelant n'en a fourni aucun.
price_val = fuel_price if fuel_price is not None else screen_price_val
evalr = evaluate_consistency(liters_val, amount_val, price_val, cfg=cfg)
confidences = [f["confidence"] for f in recognized_fields if f.get("confidence") is not None]
ocr_confidence = (sum(confidences) / len(confidences)) if confidences else None
raw_numbers = [(f["text"], v) for f, v in (
(by_field.get("prix", {}), amount_val),
(by_field.get("volume", {}), liters_val),
(by_field.get("prix_litre", {}), screen_price_val),
) if v is not None]
return {
"detected_liters": liters_val,
"detected_amount": amount_val,
"fuel_price": price_val,
"calculated_amount": evalr["calculated_amount"],
"calculated_liters": evalr["calculated_liters"],
"is_consistent": evalr["is_consistent"],
"ocr_confidence": round(ocr_confidence, 2) if ocr_confidence is not None else None,
"field_confidences": {
"liters": by_field.get("volume", {}).get("confidence"),
"amount": by_field.get("prix", {}).get("confidence"),
"price": by_field.get("prix_litre", {}).get("confidence"),
},
"raw_numbers": raw_numbers,
}
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