I am translating a go program that uses leptonica library to a python script that uses openCV, and I cant find a way to translate the following:
img = pixReduceRankBinary2(img, 2, NULL);
img = pixReduceRankBinary2(img, 2, NULL);
img = pixCloseBrick(NULL, img, 2, 3);
is there an implementation of those functions in openCV?
CodePudding user response:
Here is one way to do that using Python/OpenCV/Skimage. Simply read the image and ensure it is binary. The use Skimage downscale_local_mean to downsample by 2 using 2x2 neighborhoods producing a factor of two smaller image whose values are the means of the 2x2 neighborhoods. Then threshold again in 25% increments to correspond to leptonica counts for their pixReduceRankBinary2 function.
Input (rice grains):
import cv2
import numpy as np
import skimage.transform
# read image
img = cv2.imread('rice_bw.png')
# convert to gray
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# threshold to binary
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY)[1]
# decimate by factor of 2 to mean values in 2x2 regions
decimate = skimage.transform.downscale_local_mean(thresh, (2,2))
# set count to 1,2,3 or 4
count=2
# convert count to percent of 255 in increments of 25%
count_thresh = 255 * (25/100) * count
# threshold again
result = cv2.threshold(decimate, count_thresh, 255, cv2.THRESH_BINARY)[1]
# write result to disk
cv2.imwrite("rice_bw_binary_decimate.png", result)
# show result
cv2.imshow("result", result)
cv2.waitKey(0)
cv2.destroyAllWindows()
Result for count=2: