如何使用 OpenCV python 读取 Data Matrix 代码

问：

我试图读取金属表面上的数据矩阵代码。数据矩阵代码是用激光焊接雕刻的。我尝试了带有图像预处理的pylibdmtx。

用激光雕刻在金属表面的矩阵码

这是我的代码和结果。不幸的是，我无法从预处理的图像中读取数据。

在此处输入图像描述

import cv2
import numpy as np

'''
1. Image Read
2. Image Process
  a. gray scale
  b. crop image
  c. EqualizeHist
  d. Thres Binaray 152
  e. Blur
  f. Threshod otsu
  g. bitwise not
   
3. Result image save
'''

# crop image
def crop_image(image, min_x, max_x, min_y, max_y):
    # Load the image

    # Get image dimensions
    height, width = image.shape[:2]
    print(height, width)

    # Calculate the crop sizes
    crop_left = int(min_x * width)
    crop_right = int((1 - max_x) * width)
    crop_top = int(min_y * height)
    crop_bottom = int((1 - max_y) * height)

    print(crop_left, crop_right)

    # Crop the image
    cropped_image = image[crop_top:crop_bottom, crop_left:crop_right]
    print(cropped_image.shape)

    # Return the cropped image
    return cropped_image


# cv2 createTrackbar
def empty(x):
    pass


cv2.namedWindow('Parameters')
cv2.resizeWindow('Parameters', width=600, height=400)
cv2.createTrackbar('min_x', 'Parameters', 38, 100, empty)  # crop x
cv2.createTrackbar('max_x', 'Parameters', 36, 100, empty)  # crop x
cv2.createTrackbar('min_y', 'Parameters', 43, 100, empty)  # crop x
cv2.createTrackbar('max_y', 'Parameters', 10, 100, empty)  # crop x
cv2.createTrackbar('threshold', 'Parameters', 136, 255, empty)  # threshold
cv2.createTrackbar('k_size_set', 'Parameters', 18, 20, empty)  # blur
cv2.createTrackbar('k_mat_set', 'Parameters', 2, 5, empty) #k_mat
cv2.createTrackbar('iter_d', 'Parameters', 2, 30, empty)  # 5
cv2.createTrackbar('iter_e', 'Parameters', 4, 30, empty)  # 5

img = cv2.imread('./image/live.png')
# Gray Scale
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# resize
img = cv2.resize(img, dsize=None, fx=0.5, fy=0.5)

# -----------------------------------------------
#
# -----------------------------------------------

while True:
    ## 00. Make a Copy
    img_copy = img.copy()
    img_black = np.zeros_like(img)

    # 1. Crop Image
    dx_min = cv2.getTrackbarPos('min_x', 'Parameters')
    dx_max = cv2.getTrackbarPos('max_x', 'Parameters')
    dy_min = cv2.getTrackbarPos('min_y', 'Parameters')
    dy_max = cv2.getTrackbarPos('max_y', 'Parameters')

    dx_min, dx_max = dx_min / 100, dx_max / 100
    dy_min, dy_max = dy_min / 100, dy_max / 100

    img_crop = crop_image(image=img_copy, min_x=dx_min, max_x=dx_max, min_y=dy_min, max_y=dy_max)

    # 3 Equalize hist
    img_hist = cv2.equalizeHist(img_crop)

    # 4. Thres Binaray 152
    thres = cv2.getTrackbarPos('threshold', 'Parameters')
    _, img_thresh = cv2.threshold(img_hist, thres, 255, cv2.THRESH_BINARY)

    # 5. Gaussian Blur
    kernel = cv2.getTrackbarPos('k_size_set', 'Parameters')
    kernel = (kernel * 2) + 1
    img_blur = cv2.GaussianBlur(img_thresh, (kernel, kernel), None)

    # 6. Threshod otsu
    _, img_thresh2 = cv2.threshold(img_blur, 0, 255, cv2.THRESH_OTSU)

    # 7kernel : dilate , erodeのkernelの定義に注意
    kernel2 = cv2.getTrackbarPos('k_mat_set', 'Parameters')
    kernel2 = (kernel2 * 2) + 1
    k_mat = np.ones((kernel2, kernel2), np.uint8)

    # 8. Dilate
    iter_dilate = cv2.getTrackbarPos('iter_d', 'Parameters')
    img_dilate = cv2.dilate(img_thresh2, kernel=k_mat, iterations=iter_dilate)

    # 9. Erode
    iter_erode = cv2.getTrackbarPos('iter_e', 'Parameters')
    img_erode = cv2.erode(img_dilate, kernel=k_mat, iterations=iter_erode)

    # Plotting
  
    cv2.imshow('result2' ,img_erode)

   
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cv2.imwrite('./image/result2.png', img_erode)
print('saved')
cv2.destroyAllWindows()

这是我的图像预处理程序：

1. 图像读取

2. 图像处理 A. 灰度 B. 裁剪图像 c. 均衡历史 d. Thres Binaray e. 模糊 f. Threshod otsu g. 按位不

3. 结果图像保存