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Barcode detection + decoding provider.
Uses OpenCV's cv2.barcode.BarcodeDetector (available since OpenCV 4.5.2).
Detects and decodes common 1D/2D barcodes (EAN, UPC, Code39, Code128, etc.).
Pure OpenCV — no external deps.
"""
from __future__ import annotations
import cv2
import numpy as np
from config.settings import Settings, settings as _default_settings
from pipeline.feature_extraction import PipelineOutput
from providers.base import BaseProvider, ProviderCapability
class BarcodeProvider(BaseProvider):
name = "barcode"
capability = ProviderCapability.OBJECT_DETECTION
def __init__(self, settings: Settings | None = None) -> None:
super().__init__(settings=settings or _default_settings)
self._detector = None
try:
self._detector = cv2.barcode.BarcodeDetector()
except AttributeError:
# OpenCV < 4.5.2 — barcode detector not available
pass
def is_available(self) -> bool:
return self._detector is not None
def _run(self, pipeline_output: PipelineOutput) -> tuple[dict, dict]:
if self._detector is None:
raise RuntimeError("BarcodeDetector not available (requires OpenCV >= 4.5.2)")
img: np.ndarray = pipeline_output.image
try:
ok, decoded_info, decoded_types, points = self._detector.detectAndDecode(img)
except Exception as e:
return {"error": str(e)}, {"objects": [], "model": "opencv_barcode"}
objects: list[dict] = []
if ok and points is not None and len(points) > 0:
for i, (info, btype) in enumerate(zip(decoded_info, decoded_types)):
if i < len(points):
pts = points[i].reshape(-1, 2)
x1, y1 = int(pts[:, 0].min()), int(pts[:, 1].min())
x2, y2 = int(pts[:, 0].max()), int(pts[:, 1].max())
objects.append({
"label": "barcode",
"confidence": 1.0,
"box": {"x": x1, "y": y1, "w": x2 - x1, "h": y2 - y1},
"decoded_text": info if info else "",
"barcode_type": btype if btype else "",
"is_barcode": True,
})
raw = {
"num_objects": len(objects),
"model": "opencv_barcode",
"decoded_count": sum(1 for o in objects if o["decoded_text"]),
}
normalized = {
"objects": objects,
"model": "opencv_barcode",
}
return raw, normalized
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