14280746188

Committed 05 Apr 2025 09:50AM UTC coverage: 84.841% (-2.2%) from 87.002%

Build # 14280746188

Build Type

Pull #690

github

Committed by

web-flow

Commit Message

Merge d28da9558 into c7b17ed4a

Pull Request Pull Request #690: feature/add-qr-support

Run Details

318 of 410 new or added lines in 35 files covered. (77.56%)

5 existing lines in 2 files now uncovered.

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25.33

/normcap/detection/codes/detector.py

"""Barcode and QR Code detection."""

import logging
import os
from pathlib import Path
from typing import Optional

import cv2
import numpy as np
from PySide6 import QtGui

from normcap import resources
from normcap.detection.codes.models import CodeType, TextType

logger = logging.getLogger(__name__)

model_path = Path(resources.__file__).parent / "qr"


def _detect_barcodes_sr(mat: np.ndarray) -> list[str]:
    """Barcode detection using super resolution.

    Significantly slower but more accurate than w/o SR.
    """
    retval, bar_decoded, types, points = cv2.barcode.BarcodeDetector(
        str((model_path / "sr.prototxt").resolve()),
        str((model_path / "sr.caffemodel").resolve()),
    ).detectAndDecodeMulti(mat)
    return [s for s in bar_decoded if s]


def _detect_barcodes(mat: np.ndarray) -> list[str]:
    retval, bar_decoded, types, points = (
        cv2.barcode.BarcodeDetector().detectAndDecodeMulti(mat)
    )
    return [s for s in bar_decoded if s]


def _detect_qrcodes(mat: np.ndarray) -> list[str]:
    retval, qr_decoded, points, straight_qrcode = (
        cv2.QRCodeDetector().detectAndDecodeMulti(mat)
    )
    return [s for s in qr_decoded if s]


def _detect_qrcodes_wechat(mat: np.ndarray) -> list[str]:
    """Detect QR codes using WeChat's models.

    Similar accuracy to the default OpenCV model but faster on large images.
    """
    qr_decoded, image = cv2.wechat_qrcode.WeChatQRCode(
        str((model_path / "detect.prototxt").resolve()),
        str((model_path / "detect.caffemodel").resolve()),
        str((model_path / "sr.prototxt").resolve()),
        str((model_path / "sr.caffemodel").resolve()),
    ).detectAndDecode(mat)
    return [s for s in qr_decoded if s]


def _image_to_mat(image: QtGui.QImage) -> np.ndarray:
    ptr = image.constBits()
    arr = np.array(ptr).reshape(image.height(), image.width(), 4)
    return arr[:, :, :3]


def _get_text_type(text: str) -> TextType:
    if text.startswith("http"):
        return TextType.URL
    if text.startswith("tel:"):
        return TextType.PHONE_NUMBER
    if text.startswith("mailto:"):
        return TextType.MAIL
    if os.sep + os.sep in text:
        return TextType.PARAGRAPH
    if os.sep in text:
        return TextType.MULTI_LINE
    return TextType.SINGLE_LINE


def detect_codes(image: QtGui.QImage) -> Optional[tuple[str, TextType, CodeType]]:
    """Decode QR and barcodes from image.

    Args:
        image: Input image.

    Returns:
        URL(s), separated bye newline
    """
    logger.info("Detect Barcodes and QR Codes")

    # mat = _image_to_mat(image)
    mat = image

    barcodes = _detect_barcodes_sr(mat=mat)
    qr_codes = _detect_qrcodes_wechat(mat=mat)

    codes = barcodes + qr_codes

    if not codes:
        return None

    if barcodes and not qr_codes:
        code_type = CodeType.BARCODE
    elif qr_codes and not barcodes:
        code_type = CodeType.QR
    else:
        code_type = CodeType.QR_AND_BARCODE

    logger.info("Found %s codes", len(codes))

    if len(codes) == 1:
        text = codes[0]
        return text, _get_text_type(text), code_type

    return os.linesep.join(codes), TextType.MULTI_LINE, code_type


if __name__ == "__main__":
    import os
    from pathlib import Path
    from timeit import timeit

    reps = 10

    image_file = (
        Path(__file__).parent.parent.parent
        / "tests"
        / "integration"
        / "testcases"
        / "13_qr_code_with_text.png"
    )
    image = QtGui.QImage(str(image_file.resolve()))
    mat = _image_to_mat(image)

    time_mat = timeit(lambda: _image_to_mat(image), globals=globals(), number=reps)
    time_qr = timeit(lambda: _detect_qrcodes(mat), globals=globals(), number=reps)
    time_qr_we = timeit(
        lambda: _detect_qrcodes_wechat(mat), globals=globals(), number=reps
    )
    time_bar = timeit(lambda: _detect_barcodes(mat), globals=globals(), number=reps)
    time_bar_sr = timeit(
        lambda: _detect_barcodes_sr(mat), globals=globals(), number=reps
    )

    qr_codes = _detect_qrcodes(mat)
    qr_codes_we = _detect_qrcodes_wechat(mat)
    barcodes_sr = _detect_barcodes_sr(mat)
    barcodes = _detect_barcodes(mat)

    print(  # noqa: T201
        f"{time_mat / reps:.7f} (convert to mat)\n"
        f"{time_qr / reps:.7f} ({len(qr_codes)} QR)\n"
        f"{time_qr_we / reps:.7f} ({len(qr_codes_we)} QR WeChat)\n"
        f"{time_bar / reps:.7f} ({len(barcodes_sr)} Barcodes)\n"
        f"{time_bar_sr / reps:.7f} ({len(barcodes_sr)} Barcodes SR)\n"
    )

1	"""Barcode and QR Code detection."""
2
3	import logging	4✔
4	import os	4✔
5	from pathlib import Path	4✔
6	from typing import Optional	4✔
7
8	import cv2	4✔
9	import numpy as np	4✔
10	from PySide6 import QtGui	4✔
11
12	from normcap import resources	4✔
13	from normcap.detection.codes.models import CodeType, TextType	4✔
14
15	logger = logging.getLogger(__name__)	4✔
16
17	model_path = Path(resources.__file__).parent / "qr"	4✔
18
19
20	def _detect_barcodes_sr(mat: np.ndarray) -> list[str]:	4✔
21	"""Barcode detection using super resolution.
22
23	Significantly slower but more accurate than w/o SR.
24	"""
NEW 25	retval, bar_decoded, types, points = cv2.barcode.BarcodeDetector(	×
26	str((model_path / "sr.prototxt").resolve()),
27	str((model_path / "sr.caffemodel").resolve()),
28	).detectAndDecodeMulti(mat)
NEW 29	return [s for s in bar_decoded if s]	×
30
31
32	def _detect_barcodes(mat: np.ndarray) -> list[str]:	4✔
NEW 33	retval, bar_decoded, types, points = (	×
34	cv2.barcode.BarcodeDetector().detectAndDecodeMulti(mat)
35	)
NEW 36	return [s for s in bar_decoded if s]	×
37
38
39	def _detect_qrcodes(mat: np.ndarray) -> list[str]:	4✔
NEW 40	retval, qr_decoded, points, straight_qrcode = (	×
41	cv2.QRCodeDetector().detectAndDecodeMulti(mat)
42	)
NEW 43	return [s for s in qr_decoded if s]	×
44
45
46	def _detect_qrcodes_wechat(mat: np.ndarray) -> list[str]:	4✔
47	"""Detect QR codes using WeChat's models.
48
49	Similar accuracy to the default OpenCV model but faster on large images.
50	"""
NEW 51	qr_decoded, image = cv2.wechat_qrcode.WeChatQRCode(	×
52	str((model_path / "detect.prototxt").resolve()),
53	str((model_path / "detect.caffemodel").resolve()),
54	str((model_path / "sr.prototxt").resolve()),
55	str((model_path / "sr.caffemodel").resolve()),
56	).detectAndDecode(mat)
NEW 57	return [s for s in qr_decoded if s]	×
58
59
60	def _image_to_mat(image: QtGui.QImage) -> np.ndarray:	4✔
NEW 61	ptr = image.constBits()	×
NEW 62	arr = np.array(ptr).reshape(image.height(), image.width(), 4)	×
NEW 63	return arr[:, :, :3]	×
64
65
66	def _get_text_type(text: str) -> TextType:	4✔
NEW 67	if text.startswith("http"):	×
NEW 68	return TextType.URL	×
NEW 69	if text.startswith("tel:"):	×
NEW 70	return TextType.PHONE_NUMBER	×
NEW 71	if text.startswith("mailto:"):	×
NEW 72	return TextType.MAIL	×
NEW 73	if os.sep + os.sep in text:	×
NEW 74	return TextType.PARAGRAPH	×
NEW 75	if os.sep in text:	×
NEW 76	return TextType.MULTI_LINE	×
NEW 77	return TextType.SINGLE_LINE	×
78
79
80	def detect_codes(image: QtGui.QImage) -> Optional[tuple[str, TextType, CodeType]]:	4✔
81	"""Decode QR and barcodes from image.
82
83	Args:
84	image: Input image.
85
86	Returns:
87	URL(s), separated bye newline
88	"""
NEW 89	logger.info("Detect Barcodes and QR Codes")	×
90
91	# mat = _image_to_mat(image)
NEW 92	mat = image	×
93
NEW 94	barcodes = _detect_barcodes_sr(mat=mat)	×
NEW 95	qr_codes = _detect_qrcodes_wechat(mat=mat)	×
96
NEW 97	codes = barcodes + qr_codes	×
98
NEW 99	if not codes:	×
NEW 100	return None	×
101
NEW 102	if barcodes and not qr_codes:	×
NEW 103	code_type = CodeType.BARCODE	×
NEW 104	elif qr_codes and not barcodes:	×
NEW 105	code_type = CodeType.QR	×
106	else:
NEW 107	code_type = CodeType.QR_AND_BARCODE	×
108
NEW 109	logger.info("Found %s codes", len(codes))	×
110
NEW 111	if len(codes) == 1:	×
NEW 112	text = codes[0]	×
NEW 113	return text, _get_text_type(text), code_type	×
114
NEW 115	return os.linesep.join(codes), TextType.MULTI_LINE, code_type	×
116
117
118	if __name__ == "__main__":	4✔
NEW 119	import os	×
NEW 120	from pathlib import Path	×
NEW 121	from timeit import timeit	×
122
NEW 123	reps = 10	×
124
NEW 125	image_file = (	×
126	Path(__file__).parent.parent.parent
127	/ "tests"
128	/ "integration"
129	/ "testcases"
130	/ "13_qr_code_with_text.png"
131	)
NEW 132	image = QtGui.QImage(str(image_file.resolve()))	×
NEW 133	mat = _image_to_mat(image)	×
134
NEW 135	time_mat = timeit(lambda: _image_to_mat(image), globals=globals(), number=reps)	×
NEW 136	time_qr = timeit(lambda: _detect_qrcodes(mat), globals=globals(), number=reps)	×
NEW 137	time_qr_we = timeit(	×
138	lambda: _detect_qrcodes_wechat(mat), globals=globals(), number=reps
139	)
NEW 140	time_bar = timeit(lambda: _detect_barcodes(mat), globals=globals(), number=reps)	×
NEW 141	time_bar_sr = timeit(	×
142	lambda: _detect_barcodes_sr(mat), globals=globals(), number=reps
143	)
144
NEW 145	qr_codes = _detect_qrcodes(mat)	×
NEW 146	qr_codes_we = _detect_qrcodes_wechat(mat)	×
NEW 147	barcodes_sr = _detect_barcodes_sr(mat)	×
NEW 148	barcodes = _detect_barcodes(mat)	×
149
NEW 150	print( # noqa: T201	×
151	f"{time_mat / reps:.7f} (convert to mat)\n"
152	f"{time_qr / reps:.7f} ({len(qr_codes)} QR)\n"
153	f"{time_qr_we / reps:.7f} ({len(qr_codes_we)} QR WeChat)\n"
154	f"{time_bar / reps:.7f} ({len(barcodes_sr)} Barcodes)\n"
155	f"{time_bar_sr / reps:.7f} ({len(barcodes_sr)} Barcodes SR)\n"
156	)

dynobo / normcap / 14280746188

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