How to improve image quality before reading barcode

I am using zxing-cpp library for reading barcode from image.

import cv2
import zxingcpp

img = cv2.imread('test.jpg')
results = zxingcpp.read_barcodes(img)
for result in results:
    print('Found barcode:'
    f'\n Valid:    "{result.valid}"'
        f'\n Text:    "{result.text}"'
        f'\n Format:   {result.format}'
        f'\n Content:  {result.content_type}'
        f'\n Position: {result.position}')
if len(results) == 0:
    print("Could not find any barcode.")

However, this library is unable to scan this simple barcode from image.

How can I processes the image and improve quality of image in order to read the barcode?

I used the answer to this question as a guideline, and was still unsuccessful, therefore I am asking this question and seeking help?

With referencing this question and this question I simply increased brightness and contrast of your image. It seem worked for your image. However, you should know that just because this solution worked for this photo is not a guarantee that it will work for every photo you test.I just followed these steps because I found your photo a little dark and blurry. I think these steps can give you an idea about some of the requirements for barcode detection.

import cv2
import zxingcpp

def increase_brightness(img, value=30):
    hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
    h, s, v = cv2.split(hsv)

    lim = 255 - value
    v[v > lim] = 255
    v[v <= lim] += value

    final_hsv = cv2.merge((h, s, v))
    img = cv2.cvtColor(final_hsv, cv2.COLOR_HSV2BGR)
    return img

def increase_contrast(img, clip_limit=2.0, tile_grid_size=(8,8)):
    lab= cv2.cvtColor(img, cv2.COLOR_BGR2LAB)
    l_channel, a, b = cv2.split(lab)

    clahe = cv2.createCLAHE(clipLimit=clip_limit, tileGridSize=tile_grid_size)
    cl = clahe.apply(l_channel)
    limg = cv2.merge((cl,a,b))

    enhanced_img = cv2.cvtColor(limg, cv2.COLOR_LAB2BGR)
    return enhanced_img


img = cv2.imread('test.jpg')
cv2.namedWindow("original", cv2.WINDOW_NORMAL)
cv2.imshow("original", img)

img = increase_brightness(img, 30)
cv2.namedWindow("brightness_increased", cv2.WINDOW_NORMAL)
cv2.imshow("brightness_increased", img)

img = increase_contrast(img)
cv2.namedWindow("contrast_increased", cv2.WINDOW_NORMAL)
cv2.imshow("contrast_increased", img)

img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
cv2.namedWindow("grayscale", cv2.WINDOW_NORMAL)
cv2.imshow("grayscale", img)

results = zxingcpp.read_barcodes(img)
for result in results:
    print('Found barcode:'
    f'\n Valid:    "{result.valid}"'
        f'\n Text:    "{result.text}"'
        f'\n Format:   {result.format}'
        f'\n Content:  {result.content_type}'
        f'\n Position: {result.position}')
if len(results) == 0:
    print("Could not find any barcode.")

cv2.waitKey(0)

And the output is:

Found barcode:
 Valid:    "True"
 Text:    "4607023704821"
 Format:   BarcodeFormat.EAN13
 Content:  ContentType.Text
 Position: 198x549 720x549 720x561 198x561