python - 如何读取和解码印度 Aadhaar 卡图像上的安全二维码

Question

我正在尝试从 Aadhar 卡（印度）的图像中提取完整的 Aadhar 号码（12 位数字）

我可以用 QR 码识别该地区。为了提取信息——我一直在研究可以读取和解码印度 Aadhaar 卡上的安全二维码的 python 库。这两个库似乎对这个用例特别有用：

我无法在 Aadhaar 卡上使用它们来解码 Secure QR 码。此处提供有关安全 QR 码的信息。 请推荐可能的解决方案或其他一些方法来完成此任务

这是我使用这些库解码安全二维码的代码。 Python版本：3.8

from pyaadhaar.utils import Qr_img_to_text, isSecureQr
from pyaadhaar.deocde import AadhaarSecureQr
from pyaadhaar.deocde import AadhaarOldQr

qrData = Qr_img_to_text(sys.argv[1])
print(qrData)

if len(qrData) == 0:
    print(" No QR Code Detected !!")
else:
    isSecureQR = (isSecureQr(qrData[0]))
    if isSecureQR:
        print("Secure QR code")
        try:
            obj  = AadhaarSecureQr(qrData[0])
        except:
            print("Try aadhaar-py library")
            from aadhaar.qr import AadhaarSecureQR
            integer_scanned_from_qr = 123456
            # secure_qr = AadhaarSecureQR(integer_scanned_from_qr)
            secure_qr = AadhaarSecureQR(int(qrData[0]))
            decoded_secure_qr_data = secure_qr.extract_data()
            print(decoded_secure_qr_data)

以下是我在使用这些库时面临的问题：

pyaadhaar：安全二维码解码代码，尝试将base10字符串转换为字节，但失败。 注意：对于 Aadhaar 卡的旧 QR 码格式，pyaadhaar 库运行良好，此问题仅适用于 Secure QR 码。下面的堆栈跟踪：
```
File "/home/piyush/libs/py38/lib/python3.8/site-packages/pyaadhaar/deocde.py", line 23, in __init__
bytes_array = base10encodedstring.to_bytes(5000, 'big').lstrip(b'\x00')
```
AttributeError: 'str' object has no attribute 'to_bytes'
aadhaar-py：安全 QR 解码失败，因为它无法验证从 QR 码接收到的整数。下面的堆栈跟踪：

回溯（最后一次调用）：文件“/home/piyush/libs/py38/lib/python3.8/site-packages/aadhaar/qr.py”，第 55 行，在init self.decompressed_byte_array = zlib.decompress(self .byte_array, wbits=16+zlib.MAX_WBITS) zlib.error: Error -3 while decompressing data: wrong header check 在处理上述异常的过程中，又出现了一个异常：

回溯（最后一次调用）：文件“aadhaarQRCode.py”，第 52 行，在 secure_qr = AadhaarSecureQR(integer_scanned_from_qr) 文件“/home/piyush/libs/py38/lib/python3.8/site-packages/aadhaar/qr. py"，第 57 行，在init raise MalformedIntegerReceived('解压失败，请发送从二维码接收的有效整数') aadhaar.exceptions.MalformedIntegerReceived：解压失败，请发送从二维码接收的有效整数

score 5 · Accepted Answer

我想我已经确定了两个问题：

发布的示例图像的质量不够好。
发布的示例只是一个示例，而不是真正的“安全二维码”，而只是一个示例（isSecureQR返回false）。

将输入大小调整为 2 允许读取 QR 码：

读取、调整大小和保存为新图像：

import cv2    

image_file_name = 'image.png';

img = cv2.imread(image_file_name, cv2.IMREAD_GRAYSCALE)  # Read image as grayscale.
img2 = cv2.resize(img, (img.shape[1]*2, img.shape[0]*2), interpolation=cv2.INTER_LANCZOS4)  # Resize by x2 using LANCZOS4 interpolation method.

cv2.imwrite('image2.png', img2)

完整的代码示例：

import cv2
from pyaadhaar.utils import Qr_img_to_text, isSecureQr
from pyaadhaar.deocde import AadhaarSecureQr
from pyaadhaar.deocde import AadhaarOldQr

image_file_name = 'image.png';

img = cv2.imread(image_file_name, cv2.IMREAD_GRAYSCALE)  # Read image as grayscale.
img2 = cv2.resize(img, (img.shape[1]*2, img.shape[0]*2), interpolation=cv2.INTER_LANCZOS4)  # Resize by x2 using LANCZOS4 interpolation method.

cv2.imwrite('image2.png', img2)

#qrData = Qr_img_to_text(image_file_name)
qrData = Qr_img_to_text('image2.png')

print(qrData[0])

if len(qrData) == 0:
    print(" No QR Code Detected !!")
else:
    isSecureQR = (isSecureQr(qrData[0]))

输出：

BEGIN:VCARD
VERSION:2.1
N:John Doe
TEL;HOME;VOICE:555-555-5555
TEL;WORK;VOICE:666-666-6666
EMAIL:email@example.com
ORG:TEC-IT
URL:http://www.example.com
END:VCARD

如您所见，信息是可读的。

我不知道错误消息的原因。
我正在使用 Python 3.6 和 Windows 10，并且没有错误。

更新：

我想我在这里找到了一个很好的 QR 样本：

您可以使用以下阶段来读取和解码 QR 码：

读取图像并转换为灰度：

 img = cv2.imread('QR-code.png')
 gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

使用pyzbar解码 QR 图像：

 from pyzbar.pyzbar import decode

 code = decode(gray)
 qrData = code[0].data

输出是：

qrData = b'2374971804270526477833002468783965837992554564899874087591661303561346432389832047870524302186901344489362368642972767716416349990805756094923115719687656090691368051627957878187788907419297818953295185555346288172578594637886352753543271000481717080003254556962148594350559820352806251787713278744047402230989238559317351232114240089849934148895256488140236015024800731753594740948640957680138566468247224859669467819596919398964809164399637893729212452791889199675715949918925838319591794702333094022248132120531152523331442741730158840977243402215102904932650832502847295644794421419704633765033761284508863534321317394686768650111457751139630853448637215423705157211510636160227953566227527799608082928846103264491539001327407775670834868948113753614112563650255058316849200536533335903554984254814901522086937767458409075617572843449110393213525925388131214952874629655799772119820372255291052673056372346072235458198199995637720424196884145247220163810790179386390283738429482893152518286247124911446073389185062482901364671389605727763080854673156754021728522287806275420847159574631844674460263574901590412679291518508010087116598357407343835408554094619585212373168435612645646129147973594416508676872819776522537778717985070402222824965034768103900739105784663244748432502180989441389718131079445941981681118258324511923246198334046020123727749408128519721102477302359413240175102907322619462289965085963377744024233678337951462006962521823224880199210318367946130004264196899778609815012001799773327514133268825910089483612283510244566484854597156100473055413090101948456959122378865704840756793122956663218517626099291311352417342899623681483097817511136427210593032393600010728324905512596767095096153856032112835755780472808814199620390836980020899858288860556611564167406292139646289142056168261133256777093245980048335918156712295254776487472431445495668303900536289283098315798552328294391152828182614909451410115516297083658174657554955228963550255866282688308751041517464999930825273776417639569977754844191402927594739069037851707477839207593911886893016618794870530622356073909077832279869798641545167528509966656120623184120128052588408742941658045827255866966100249857968956536613250770326334844204927432961924987891433020671754710428050564671868464658436926086493709176888821257183419013229795869757265111599482263223604228286513011751601176504567030118257385997460972803240338899836840030438830725520798480181575861397469056536579877274090338750406459700907704031830137890544492015701251066934352867527112361743047684237105216779177819594030160887368311805926405114938744235859610328064947158936962470654636736991567663705830950312548447653861922078087824048793236971354828540758657075837209006713701763902429652486225300535997260665898927924843608750347193892239342462507130025307878412116604096773706728162016134101751551184021079984480254041743057914746472840768175369369852937574401874295943063507273467384747124843744395375119899278823903202010381949145094804675442110869084589592876721655764753871572233276245590041302887094585204427900634246823674277680009401177473636685542700515621164233992970974893989913447733956146698563285998205950467321954304'

isSecureQR = (isSecureQr(qrData))返回True。

qrData使用pyaadhaar解码：

 secure_qr = AadhaarSecureQr(int(qrData))
 decoded_secure_qr_data = secure_qr.decodeddata()

完整的代码示例：

import cv2
from pyzbar.pyzbar import decode
from pyaadhaar.utils import isSecureQr
from pyaadhaar.deocde import AadhaarSecureQr

img = cv2.imread('QR-code.png')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

code = decode(gray)
qrData = code[0].data

isSecureQR = (isSecureQr(qrData))

if isSecureQR:
    secure_qr = AadhaarSecureQr(int(qrData))
    decoded_secure_qr_data = secure_qr.decodeddata()
    print(decoded_secure_qr_data)

输出：

{'email_mobile_status': '3', 'referenceid': '269720190308114407437', 'name': 'Sumit Kumar', 'dob': '01-01-1984', 'gender': 'M', 'careof': 'C/O Ishwar Chand', 'district': 'East Delhi', 'landmark': '', 'house': 'B-31, 3rd Floor', 'location': '', 'pincode': '110051', 'postoffice': 'Krishna Nagar', 'state': 'Delhi', 'street': 'Radhey Shyam Park Extension', 'subdistrict': 'Gandhi Nagar', 'vtc': 'Krishna Nagar', 'adhaar_last_4_digit': '2697', 'adhaar_last_digit': '7', 'email': 'yes', 'mobile': 'yes'}

您的原始代码也适用于上图：

from pyaadhaar.utils import Qr_img_to_text, isSecureQr

qrData = Qr_img_to_text('QR-code.png')

isSecureQR = (isSecureQr(qrData[0]))

if isSecureQR:
    secure_qr = AadhaarSecureQr(int(qrData[0]))
    decoded_secure_qr_data = secure_qr.decodeddata()
    print(decoded_secure_qr_data)

score 1 · Accepted Answer

感谢您发布问题。我是aadhaar-py的作者，代码抛出异常是因为传给lib的数据无法解析。它必须是某种类型才能使其可解析。示例请参考以下链接：https ://uidai.gov.in/te/ecosystem-te/authentication-devices-documents-te/qr-code-reader-te.html

如果您扫描页面上的二维码并将收到的数据传递给 lib，您将收到提取的数据。PS：Lib 已经用新的 API 进行了修改。一定要检查出来:) https://pypi.org/project/aadhaar-py/

score 0 · Accepted Answer

对于需要在实际解码之前提取干净的 QR 码 ROI 的任何人，这里有一种使用阈值、形态学运算和轮廓过滤来提取 QR 码的简单方法。

获取二值图像。 加载图像，灰度，高斯模糊，大津阈值
连接各个 QR 轮廓。创建一个矩形结构内核，然后使用cv2.getStructuringElement()执行形态学运算cv2.MORPH_CLOSE。
筛选 QR 码。 使用轮廓近似、轮廓面积和纵横比查找轮廓和过滤器。

这是图像处理管道

加载图像，灰度，高斯模糊，然后Otsu的阈值得到二值图像

现在我们创建一个矩形内核并变形关闭以将二维码组合成一个轮廓

我们使用轮廓面积、轮廓近似和纵横比来找到 QR 码的轮廓和过滤器。检测到的二维码以绿色突出显示

提取的投资回报率

代码

import cv2
import numpy as np

# Load imgae, grayscale, Gaussian blur, Otsu's threshold
image = cv2.imread('1.png')
original = image.copy()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (7,7), 0)
thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]

# Morph close
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5,5))
close = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel, iterations=1)

# Find contours and filter for QR code using contour area, approximation, and aspect ratio
cnts = cv2.findContours(close, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
    peri = cv2.arcLength(c, True)
    approx = cv2.approxPolyDP(c, 0.04 * peri, True)
    x,y,w,h = cv2.boundingRect(approx)
    area = cv2.contourArea(c)
    ar = w / float(h)
    if len(approx) == 4 and area > 1000 and (ar > .85 and ar < 1.3):
        cv2.rectangle(image, (x, y), (x + w, y + h), (36,255,12), 3)
        ROI = original[y:y+h, x:x+w]
        # cv2.imwrite('ROI.png', ROI)

# Display
cv2.imshow('thresh', thresh)
cv2.imshow('close', close)
cv2.imshow('image', image)
cv2.imshow('ROI', ROI)

# Save images
# cv2.imwrite('thresh.png', thresh)
# cv2.imwrite('close.png', close)
# cv2.imwrite('image.png', image)
# cv2.imwrite('ROI.png', ROI)
cv2.waitKey()

python - 如何读取和解码印度 Aadhaar 卡图像上的安全二维码

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