I've written some code, to crop an object (in this case the Data Matrix Code) from an image:
import numpy as np
import cv2
image = cv2.imread("datamatrixc.png")
img_gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
img_height, img_width = image.shape[:2]
WHITE = [255, 255, 255]
# Threshold filter
ret, thresh = cv2.threshold(img_gray, 127, 255, cv2.THRESH_BINARY_INV)
# Get Contours
_, contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
# Get Last element of the contours object
max = len(contours) - 1
cnt = contours[max]
# Get coordinates for the bounding box
x, y, w, h = cv2.boundingRect(cnt)
image_region = image[ int(((img_height / 2) - h) / 2) : int(((img_height / 2) - h) / 2 + h), int(x): int(x + w) ]
dmc = cv2.copyMakeBorder(image_region, 10, 10, 10, 10, cv2.BORDER_CONSTANT, value = WHITE)
cv2.imshow("Test", dmc)
cv2.waitKey(0)
cv2.destroyAllWindows()
The code works fine and I received as result:
However, the next image is a little more complicated. I receive the same result as in the previous image, but I have no idea how to detect the two other objects.
Is there an easier way every object showing in its window?
How about this?
import numpy as np
import cv2
image = cv2.imread("datamatrixc.png")
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
ret, bin_img = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)
kernel = np.ones((3,3),np.uint8)
closing = cv2.morphologyEx(bin_img, cv2.MORPH_CLOSE, kernel, iterations=4)
n_labels, labels, stats, centroids = cv2.connectedComponentsWithStats(bin_img)
size_thresh = 5000
for i in range(1, n_labels):
if stats[i, cv2.CC_STAT_AREA] >= size_thresh:
print(stats[i, cv2.CC_STAT_AREA])
x = stats[i, cv2.CC_STAT_LEFT]
y = stats[i, cv2.CC_STAT_TOP]
w = stats[i, cv2.CC_STAT_WIDTH]
h = stats[i, cv2.CC_STAT_HEIGHT]
cv2.imshow('img', image[y:y+h, x:x+w])
cv2.waitKey(0)