Enhance OCR configuration and integrate fuzzy matching for label parsing

app/label_parser.py

@@ -3,8 +3,12 @@ from __future__ import annotations
 import re
 from dataclasses import dataclass, asdict
 
+from app.fuzzy_match import best_fuzzy_match
+
 
 ORDER_RE = re.compile(r"\b(?P<order>\d{4}/\d{4}/(?:[1-9]|[1-9]\d))\b")
+DEFAULT_MODEL_MIN_SCORE = 0.72
+DEFAULT_COLOR_MIN_SCORE = 0.72
 
 
 @dataclass
@@ -13,8 +17,10 @@ class ParsedLabel:
     color_code: str | None
     product_model: str | None
     raw_text: str
+    color_score: float | None = None
+    product_model_score: float | None = None
 
-    def to_dict(self) -> dict[str, str | None]:
+    def to_dict(self) -> dict[str, str | float | None]:
         return asdict(self)
 
 
@@ -22,23 +28,24 @@ def normalize_ocr_text(text: str) -> str:
     return " ".join(text.replace("\n", " ").replace("\r", " ").split())
 
 
-def parse_label_text(text: str, known_colors: list[str], known_models: list[str]) -> ParsedLabel:
+def parse_label_text(
+    text: str,
+    known_colors: list[str],
+    known_models: list[str],
+    model_min_score: float = DEFAULT_MODEL_MIN_SCORE,
+    color_min_score: float = DEFAULT_COLOR_MIN_SCORE,
+) -> ParsedLabel:
     normalized = normalize_ocr_text(text)
     order_match = ORDER_RE.search(normalized)
 
-    normalized_upper = normalized.upper()
-    color_code = next(
-        (color for color in known_colors if color.upper() in normalized_upper),
-        None,
-    )
-    product_model = next(
-        (model for model in known_models if re.search(rf"\b{re.escape(model)}\b", normalized, re.I)),
-        None,
-    )
+    color_match = best_fuzzy_match(normalized, known_colors, color_min_score)
+    model_match = best_fuzzy_match(normalized, known_models, model_min_score)
 
     return ParsedLabel(
         order_number=order_match.group("order") if order_match else None,
-        color_code=color_code,
-        product_model=product_model,
+        color_code=color_match.value if color_match else None,
+        product_model=model_match.value if model_match else None,
         raw_text=normalized,
+        color_score=color_match.score if color_match else None,
+        product_model_score=model_match.score if model_match else None,
     )