How to Generate and Read QR Code in Python

Learning how you can generate and read QR Code in Python using qrcode and OpenCV libraries.
  · 7 min read · Updated sep 2020 · Computer Vision


QR code is a type of matrix barcode that is machine readable optical label which contains information about the item to which it is attached. In practice, QR codes often contain data for a locator, identifier, or tracker that points to a website or application, etc.

In this tutorial, you will learn how to generate and read QR codes in Python using qrcode and OpenCV libraries.

Installing required dependencies:

pip3 install opencv-python qrcode numpy

Generate QR Code

First, let's start by generating QR codes, it is basically straight forward using qrcode library:

import qrcode
# example data
data = "https://www.thepythoncode.com"
# output file name
filename = "site.png"
# generate qr code
img = qrcode.make(data)
# save img to a file
img.save(filename)

This will generate a new image file in the current directory with the name of "site.png", which contains a QR code image of the data specified (in this case, this website URL), will look something like this:

Auto generated QR Code in Python

You can also use this library to have full control with QR code generation using the qrcode.QRCode() class, in which you can instantiate and specify the size, fill color, back color, and error correction, like so:

import qrcode
import numpy as np
# data to encode
data = "https://www.thepythoncode.com"
# instantiate QRCode object
qr = qrcode.QRCode(version=1, box_size=10, border=4)
# add data to the QR code
qr.add_data(data)
# compile the data into a QR code array
qr.make()
# print the image shape
print("The shape of the QR image:", np.array(qr.get_matrix()).shape)
# transfer the array into an actual image
img = qr.make_image(fill_color="white", back_color="black")
# save it to a file
img.save("site_inversed.png")

So in the creation of QRCode class, we specify the version parameter, which is an integer from 1 to 40 that controls the size of the QR code image (1 is small, 21x21 matrix, 40 is 185x185 matrix), but this will be overwritten when the data doesn't fit the size you specify. In our case, it will scale up to version 3 automatically.

box_size parameter controls how many pixels each box of the QR code is, whereas the border controls how many boxes thick the border should be.

We then add the data using qr.add_data() method, compiles it to an array using qr.make() method, and then make the actual image using qr.make_image() method. We specified white as the fill_color and black as the back_color, which is the exact opposite of the default QR code, check it out:

Custom QR Code generating using PythonAnd the shape of the image was indeed scaled up and wasn't 21x21:

The shape of the QR image: (37, 37)

Related: How to Make a Barcode Reader in Python.

Read QR Code

There are many tools that reads QR code. However, we will be using OpenCV for that, as it is popular and easy to integrate with the webcam or any video.

Alright, open up a new Python file and follow along with me, let's read the image that we just generated:

import cv2
# read the QRCODE image
img = cv2.imread("site.png")

Luckily for us, OpenCV already got QR code detector built in:

# initialize the cv2 QRCode detector
detector = cv2.QRCodeDetector()

We have the image and the detector, let's detect and decode that data:

# detect and decode
data, bbox, straight_qrcode = detector.detectAndDecode(img)

detectAndDecode() function takes an image as an input and decodes it to return a tuple of 3 values: the data decoded from the QR code, the output array of vertices of the found QR code quadrangle and the output image containing rectified and binarized QR code.

We just need data and bbox here, bbox will help us draw the quadrangle in the image and data will be printed to the console!

Let's do it:

# if there is a QR code
if bbox is not None:
    print(f"QRCode data:\n{data}")
    # display the image with lines
    # length of bounding box
    n_lines = len(bbox)
    for i in range(n_lines):
        # draw all lines
        point1 = tuple(bbox[i][0])
        point2 = tuple(bbox[(i+1) % n_lines][0])
        cv2.line(img, point1, point2, color=(255, 0, 0), thickness=2)

cv2.line() function draws a line segment connecting two points, we retrieve these points from bbox array that was decoded by detectAndDecode() previously. we specified a blue color ( (255, 0, 0) is blue as OpenCV uses BGR colors ) and thickness of 2.

Finally, let's show the image and quit when a key is pressed:

# display the result
cv2.imshow("img", img)
cv2.waitKey(0)
cv2.destroyAllWindows()

Once you run this, the decoded data is printed:

QRCode data:
https://www.thepythoncode.com

And the following image is shown:

The read QRCode using OpenCV in Python

As you can see, the blue lines are drawn in the exact QR code borders. Awesome, we are done with this script, try to run it with different data and see your own results !

Note that this is ideal for QR codes and not for barcodes, If you want to read barcodes, check this tutorial that is dedicated for that!

If you want to detect and decode QR codes live using your webcam (and I'm sure you do), here is a code for that:

import cv2
# initalize the cam
cap = cv2.VideoCapture(0)
# initialize the cv2 QRCode detector
detector = cv2.QRCodeDetector()
while True:
    _, img = cap.read()
    # detect and decode
    data, bbox, _ = detector.detectAndDecode(img)
    # check if there is a QRCode in the image
    if bbox is not None:
        # display the image with lines
        for i in range(len(bbox)):
            # draw all lines
            cv2.line(img, tuple(bbox[i][0]), tuple(bbox[(i+1) % len(bbox)][0]), color=(255, 0, 0), thickness=2)
        if data:
            print("[+] QR Code detected, data:", data)
    # display the result
    cv2.imshow("img", img)    
    if cv2.waitKey(1) == ord("q"):
        break
cap.release()
cv2.destroyAllWindows()

Awesome, we are done with this tutorial, you can now integrate this in your own applications!

Check qrcode's official documentation.

Finally, many of the Python concepts aren't discussed in detail here, if you feel you want to dig more to Python, I highly suggest you get one of these amazing courses:

Learn also: How to Use Steganography to Hide Secret Data in Images in Python.

Happy Coding ♥

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