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QR code detection + decoding provider.
Uses OpenCV's built-in cv2.QRCodeDetector — no external deps.
Detects and decodes QR codes, returning the decoded text + bounding box.
Pure OpenCV — no model downloads, no external services.
"""
from __future__ import annotations
import cv2
import numpy as np
from config.settings import Settings, settings as _default_settings
from cores.vision import to_gray
from pipeline.feature_extraction import PipelineOutput
from providers.base import BaseProvider, ProviderCapability
class QRCodeProvider(BaseProvider):
name = "qr_code"
capability = ProviderCapability.OBJECT_DETECTION # reuse OBJECT_DETECTION capability
def __init__(self, settings: Settings | None = None) -> None:
super().__init__(settings=settings or _default_settings)
self._detector = cv2.QRCodeDetector()
def is_available(self) -> bool:
return hasattr(cv2, "QRCodeDetector")
def _run(self, pipeline_output: PipelineOutput) -> tuple[dict, dict]:
img: np.ndarray = pipeline_output.image
# QRCodeDetector.detectAndDecode returns:
# (decoded_text, points, straight_qrcode)
try:
data, points, _ = self._detector.detectAndDecode(img)
except Exception as e:
return {"error": str(e)}, {"objects": [], "model": "opencv_qr"}
objects: list[dict] = []
if points is not None and len(points) > 0:
# points shape: (4, 2) — four corners of the QR code
pts = points.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": "qr_code",
"confidence": 1.0,
"box": {"x": x1, "y": y1, "w": x2 - x1, "h": y2 - y1},
"decoded_text": data if data else "",
"is_qr_code": True,
})
raw = {
"num_objects": len(objects),
"model": "opencv_qr",
"decoded": bool(data),
}
normalized = {
"objects": objects,
"model": "opencv_qr",
}
return raw, normalized
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