如何读取和解码印度 Aadhaar 卡图像上的安全二维码
How to read & decode Secure QR code on Indian Aadhaar Card image
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）
我可以用二维码识别地区。要提取信息 - 我一直在研究 python 库，这些库读取和解码印度 Aadhaar 卡上的安全二维码。
这两个库似乎对这个用例特别有用：
我无法在 Aadhaar 卡上使用它们解码安全二维码。 Information on Secure QR code is available here.
请推荐可能的解决方案或一些其他方法来完成此任务
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遇到的问题：
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，此问题仅发生在安全 QR 码上。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 码收到的整数。下面的堆栈跟踪：
Traceback (most recent call last):
File "/home/piyush/libs/py38/lib/python3.8/site-packages/aadhaar/qr.py", line 55, in init
self.decompressed_byte_array = zlib.decompress(self.byte_array, wbits=16+zlib.MAX_WBITS)
zlib.error: Error -3 while decompressing data: incorrect header check
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "aadhaarQRCode.py", line 52, in
secure_qr = AadhaarSecureQR(integer_scanned_from_qr)
File "/home/piyush/libs/py38/lib/python3.8/site-packages/aadhaar/qr.py", line 57, in init
raise MalformedIntegerReceived('Decompression failed, please send a valid integer received from QR code')
aadhaar.exceptions.MalformedIntegerReceived: Decompression failed, please send a valid integer received from QR code
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、形态学操作和轮廓过滤来提取 QR 码的简单方法。
获取二进制图像。 Load image, grayscale, Gaussian blur, Otsu's threshold
连接各个 QR 轮廓。 使用 cv2.getStructuringElement() then perform morphological operations 和 cv2.MORPH_CLOSE 创建矩形结构内核。
二维码过滤。 Find contours
并使用 contour approximation, contour area, and aspect ratio.
进行过滤
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接近以将 QR 码组合成一个轮廓
我们使用轮廓区域、轮廓近似和纵横比为 QR 码找到轮廓和过滤器。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()
我想我已经确定了两个问题：
- 发布的示例图片质量不够好。
- 张贴的样本只是一个例子，不是真正的“安全二维码”，只是一个例子（
isSecureQR returns false）。
将输入的大小调整为 2 倍允许读取 QR 码：
正在读取、调整大小并另存为新图像：
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，没有错误。
更新：
我想我找到了一个很好的 QR 样本 here:
您可以使用以下步骤来读取和解码二维码：
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
输出为：
qrData = b'2374971804270526477833002468783965837992554564899874087591661303561346432389832047870524302186901344489362368642972767716416349990805756094923115719687656090691368051627957878187788907419297818953295185555346288172578594637886352753543271000481717080003254556962148594350559820352806251787713278744047402230989238559317351232114240089849934148895256488140236015024800731753594740948640957680138566468247224859669467819596919398964809164399637893729212452791889199675715949918925838319591794702333094022248132120531152523331442741730158840977243402215102904932650832502847295644794421419704633765033761284508863534321317394686768650111457751139630853448637215423705157211510636160227953566227527799608082928846103264491539001327407775670834868948113753614112563650255058316849200536533335903554984254814901522086937767458409075617572843449110393213525925388131214952874629655799772119820372255291052673056372346072235458198199995637720424196884145247220163810790179386390283738429482893152518286247124911446073389185062482901364671389605727763080854673156754021728522287806275420847159574631844674460263574901590412679291518508010087116598357407343835408554094619585212373168435612645646129147973594416508676872819776522537778717985070402222824965034768103900739105784663244748432502180989441389718131079445941981681118258324511923246198334046020123727749408128519721102477302359413240175102907322619462289965085963377744024233678337951462006962521823224880199210318367946130004264196899778609815012001799773327514133268825910089483612283510244566484854597156100473055413090101948456959122378865704840756793122956663218517626099291311352417342899623681483097817511136427210593032393600010728324905512596767095096153856032112835755780472808814199620390836980020899858288860556611564167406292139646289142056168261133256777093245980048335918156712295254776487472431445495668303900536289283098315798552328294391152828182614909451410115516297083658174657554955228963550255866282688308751041517464999930825273776417639569977754844191402927594739069037851707477839207593911886893016618794870530622356073909077832279869798641545167528509966656120623184120128052588408742941658045827255866966100249857968956536613250770326334844204927432961924987891433020671754710428050564671868464658436926086493709176888821257183419013229795869757265111599482263223604228286513011751601176504567030118257385997460972803240338899836840030438830725520798480181575861397469056536579877274090338750406459700907704031830137890544492015701251066934352867527112361743047684237105216779177819594030160887368311805926405114938744235859610328064947158936962470654636736991567663705830950312548447653861922078087824048793236971354828540758657075837209006713701763902429652486225300535997260665898927924843608750347193892239342462507130025307878412116604096773706728162016134101751551184021079984480254041743057914746472840768175369369852937574401874295943063507273467384747124843744395375119899278823903202010381949145094804675442110869084589592876721655764753871572233276245590041302887094585204427900634246823674277680009401177473636685542700515621164233992970974893989913447733956146698563285998205950467321954304'
isSecureQR = (isSecureQr(qrData)) returns True.
使用pyaadhaar解码qrData:
secure_qr = AadhaarSecureQr(int(qrData))
decoded_secure_qr_data = secure_qr.decodeddata()
完整代码示例：
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)
感谢您提出问题。
我是 aadhaar-py 的作者，代码引发异常，因为无法解析传递给 lib 的数据。它必须是某种类型才能被解析。请参考以下 link 示例：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库，您将收到提取的数据。
P.S.: 库已经用新的 API 进行了改进。一定要检查一下:)
https://pypi.org/project/aadhaar-py/
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）
我可以用二维码识别地区。要提取信息 - 我一直在研究 python 库，这些库读取和解码印度 Aadhaar 卡上的安全二维码。 这两个库似乎对这个用例特别有用：
我无法在 Aadhaar 卡上使用它们解码安全二维码。 Information on Secure QR code is available here. 请推荐可能的解决方案或一些其他方法来完成此任务
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遇到的问题：
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，此问题仅发生在安全 QR 码上。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 码收到的整数。下面的堆栈跟踪：
Traceback (most recent call last): File "/home/piyush/libs/py38/lib/python3.8/site-packages/aadhaar/qr.py", line 55, in init self.decompressed_byte_array = zlib.decompress(self.byte_array, wbits=16+zlib.MAX_WBITS) zlib.error: Error -3 while decompressing data: incorrect header check During handling of the above exception, another exception occurred:
Traceback (most recent call last): File "aadhaarQRCode.py", line 52, in secure_qr = AadhaarSecureQR(integer_scanned_from_qr) File "/home/piyush/libs/py38/lib/python3.8/site-packages/aadhaar/qr.py", line 57, in init raise MalformedIntegerReceived('Decompression failed, please send a valid integer received from QR code') aadhaar.exceptions.MalformedIntegerReceived: Decompression failed, please send a valid integer received from QR code
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、形态学操作和轮廓过滤来提取 QR 码的简单方法。
获取二进制图像。 Load image, grayscale, Gaussian blur, Otsu's threshold
连接各个 QR 轮廓。 使用
cv2.getStructuringElement()then perform morphological operations 和cv2.MORPH_CLOSE创建矩形结构内核。二维码过滤。 Find contours 并使用 contour approximation, contour area, and aspect ratio.
进行过滤
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接近以将 QR 码组合成一个轮廓
我们使用轮廓区域、轮廓近似和纵横比为 QR 码找到轮廓和过滤器。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()
我想我已经确定了两个问题：
- 发布的示例图片质量不够好。
- 张贴的样本只是一个例子，不是真正的“安全二维码”，只是一个例子（
isSecureQRreturnsfalse）。
将输入的大小调整为 2 倍允许读取 QR 码：
正在读取、调整大小并另存为新图像：
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，没有错误。
更新：
我想我找到了一个很好的 QR 样本 here:
您可以使用以下步骤来读取和解码二维码：
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
输出为：
qrData = b'2374971804270526477833002468783965837992554564899874087591661303561346432389832047870524302186901344489362368642972767716416349990805756094923115719687656090691368051627957878187788907419297818953295185555346288172578594637886352753543271000481717080003254556962148594350559820352806251787713278744047402230989238559317351232114240089849934148895256488140236015024800731753594740948640957680138566468247224859669467819596919398964809164399637893729212452791889199675715949918925838319591794702333094022248132120531152523331442741730158840977243402215102904932650832502847295644794421419704633765033761284508863534321317394686768650111457751139630853448637215423705157211510636160227953566227527799608082928846103264491539001327407775670834868948113753614112563650255058316849200536533335903554984254814901522086937767458409075617572843449110393213525925388131214952874629655799772119820372255291052673056372346072235458198199995637720424196884145247220163810790179386390283738429482893152518286247124911446073389185062482901364671389605727763080854673156754021728522287806275420847159574631844674460263574901590412679291518508010087116598357407343835408554094619585212373168435612645646129147973594416508676872819776522537778717985070402222824965034768103900739105784663244748432502180989441389718131079445941981681118258324511923246198334046020123727749408128519721102477302359413240175102907322619462289965085963377744024233678337951462006962521823224880199210318367946130004264196899778609815012001799773327514133268825910089483612283510244566484854597156100473055413090101948456959122378865704840756793122956663218517626099291311352417342899623681483097817511136427210593032393600010728324905512596767095096153856032112835755780472808814199620390836980020899858288860556611564167406292139646289142056168261133256777093245980048335918156712295254776487472431445495668303900536289283098315798552328294391152828182614909451410115516297083658174657554955228963550255866282688308751041517464999930825273776417639569977754844191402927594739069037851707477839207593911886893016618794870530622356073909077832279869798641545167528509966656120623184120128052588408742941658045827255866966100249857968956536613250770326334844204927432961924987891433020671754710428050564671868464658436926086493709176888821257183419013229795869757265111599482263223604228286513011751601176504567030118257385997460972803240338899836840030438830725520798480181575861397469056536579877274090338750406459700907704031830137890544492015701251066934352867527112361743047684237105216779177819594030160887368311805926405114938744235859610328064947158936962470654636736991567663705830950312548447653861922078087824048793236971354828540758657075837209006713701763902429652486225300535997260665898927924843608750347193892239342462507130025307878412116604096773706728162016134101751551184021079984480254041743057914746472840768175369369852937574401874295943063507273467384747124843744395375119899278823903202010381949145094804675442110869084589592876721655764753871572233276245590041302887094585204427900634246823674277680009401177473636685542700515621164233992970974893989913447733956146698563285998205950467321954304'
isSecureQR = (isSecureQr(qrData)) returns True.
使用pyaadhaar解码
qrData:secure_qr = AadhaarSecureQr(int(qrData)) decoded_secure_qr_data = secure_qr.decodeddata()
完整代码示例：
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)
感谢您提出问题。 我是 aadhaar-py 的作者，代码引发异常，因为无法解析传递给 lib 的数据。它必须是某种类型才能被解析。请参考以下 link 示例：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库，您将收到提取的数据。 P.S.: 库已经用新的 API 进行了改进。一定要检查一下:) https://pypi.org/project/aadhaar-py/