Scanning Barcode and QR Code Using Webcam, OpenCV and Python

Dynamsoft is the only company that provides enterprise-class Python Barcode and QR Code SDK for Windows, Linux, macOS, and Raspberry Pi OS. The SDK allows developer to quickly build robust command-line, web, and desktop applications that can scan barcodes and QR codes from a wide range of sources. In this article, we use Dynamsoft Barcode Reader, OpenCV, and webcam to create cross-platform desktop barcode and QR code scanner in Python.

Download SDK

• OpenCV

  Used for accessing the webcam and stitching images.
  

  pip install opencv-python

• Dynamsoft Barcode Reader

  Used for decoding barcodes and QR codes from images.
  

  pip install dbr

License Activation

Get a desktop license key from here to activate Dynamsoft Barcode Reader:

BarcodeReader.init_license("LICENSE-KEY")

Steps to Build Barcode and QR Code Scanner in Python

It is known that Python's GIL (Global Interpreter Lock) is a performance bottleneck for multi-threaded applications. Therefore, it is recommended to use Python's multiprocessing library to run barcode and QR code detection algorithm which is CPU-intensive. The sample code video_threaded.py demonstrates how to use Python's multiprocessing library.

Here are the steps to build our barcode and QR code scanner:

1. Import the necessary packages:
   

   import numpy as npimport cv2 as cvfrom multiprocessing.pool import ThreadPoolfrom collections import dequeimport dbrfrom dbr import *

2. Set the license key to activate and instantiate Dynamsoft Barcode Reader:
   

   BarcodeReader.init_license("LICENSE-KEY")reader = BarcodeReader()

3. Create a thread pool with the amount of processes you want to use:
   

   threadn = 1 # cv.getNumberOfCPUs()pool = ThreadPool(processes = threadn)barcodeTasks = deque()

   Note: If you use all CPU cores, the CPU usage will be high.

4. Create a task function to detect barcodes and QR codes from webcam video frames:
   

   def process_frame(frame):    results = None    try:        results = reader.decode_buffer(frame)    except BarcodeReaderError as bre:        print(bre)    return resultswhile True:    ret, frame = cap.read()    while len(barcodeTasks) > 0 and barcodeTasks[0].ready():        results = barcodeTasks.popleft().get()        if results != None:            for result in results:                points = result.localization_result.localization_points                cv.line(frame, points[0], points[1], (0,255,0), 2)                cv.line(frame, points[1], points[2], (0,255,0), 2)                cv.line(frame, points[2], points[3], (0,255,0), 2)                cv.line(frame, points[3], points[0], (0,255,0), 2)                cv.putText(frame, result.barcode_text, points[0], cv.FONT_HERSHEY_SIMPLEX, 0.5, (0,0,255))    if len(barcodeTasks) < threadn:        task = pool.apply_async(process_frame, (frame.copy(), ))        barcodeTasks.append(task)    cv.imshow('Barcode & QR Code Scanner', frame)    ch = cv.waitKey(1)    if ch == 27:        break

5. Run the barcode and QR code scanner:

   

Dynamsoft Barcode Reader can detect multiple barcodes and QR codes from a single image. However, the image quality affects the detection accuracy. As you can see in the above image, to capture all barcode and QR code, we need to increase the lens depth of field. In this way, the barcode and QR code may become too small to read. To solve this problem, we get camera closer to get high quality image for scanning, and then use OpenCV stitching API to stitch multiple barcode and QR code images into a panorama.

Stitching Multiple Barcode and QR Code Images into a Panorama

OpenCV repository contains a stitching.py file showing how to use the OpenCV stitcher API.

To implement panorama stitching:

1. Initialize a stitcher object:
   

   modes = (cv.Stitcher_PANORAMA, cv.Stitcher_SCANS)stitcher = cv.Stitcher.create(modes[1])stitcher.setPanoConfidenceThresh(0.5)

2. create a new task function for stitching images that contains barcode and QR code:
   

   panoramaPool = ThreadPool(processes = threadn)panoramaTask = deque()def stitch_frame(self, frame):    try:        results = self.reader.decode_buffer(frame)        if results != None:            for result in results:                points = result.localization_result.localization_points                cv.line(frame, points[0], points[1], (0,255,0), 2)                cv.line(frame, points[1], points[2], (0,255,0), 2)                cv.line(frame, points[2], points[3], (0,255,0), 2)                cv.line(frame, points[3], points[0], (0,255,0), 2)                cv.putText(frame, result.barcode_text, points[0], cv.FONT_HERSHEY_SIMPLEX, 0.5, (0,0,255))            self.panorama.append((frame, len(results)))            print('Stitching .............')            try:                all_images = [frame for frame, count in self.panorama]                status, image = self.stitcher.stitch(all_images)                if status != cv.Stitcher_OK:                    print("Can't stitch images, error code = %d" % status)                    return self.panorama[0][0]                else:                    # Stop stitching if the output image is out of control                    if image.shape[0] >= frame.shape[0] * 1.5:                        self.isPanoramaDone = True                        self.save_frame(all_images[0])                        print('Stitching is done.............')                        return None                    # Drop the stitched image if its quality is not good enough                    total = 0                    for frame, count in self.panorama:                        total += count                    count_stitch = self.count_barcodes(image)                    if count_stitch > total or count_stitch < self.panorama[0][1]:                        return self.panorama[0][0]                    # Wait for the next stitching and return the current stitched image                    self.panorama = [(image, count_stitch)]                    return image            except Exception as e:                print(e)                return None    except BarcodeReaderError as e:        print(e)        return None    return Nonewhile len(panoramaTask) > 0 and panoramaTask[0].ready():    image = panoramaTask.popleft().get()    if image is not None:        cv.imshow('panorama', image)if len(panoramaTask) < threadn:    task = panoramaPool.apply_async(self.stitch_frame, (frame_cp, ))    panoramaTask.append(task)

3. Run the code to get the panorama stitching result.

   

Source Code

https://github.com/yushulx/webcam-barcode-qrcode-reader-python