无法使用 scikit 图像将 RGB 图像转换为灰度

Question

I have tried to convert an RGB image to Otsu binary image (gray scale) but that doesn't seem to work as I get the error as mentioned below.

from cv2 import cv2
import numpy as np
from skimage.color import rgb2gray
from skimage.filters import threshold_otsu
from skimage.io import imread
from skimage.morphology import skeletonize
from skimage.util import invert
import matplotlib.pyplot as plt

img = rgb2gray(imread('Ared.png'))
binary = img > threshold_otsu(img)
np.unique(binary)
skeleton = skeletonize(invert(binary))
cv2.imshow('original', img)
cv2.imshow('skeleton', skeleton)
cv2.waitKey(0)
cv2.destroyAllWindows()

Result in terminal

  img = rgb2gray(imread('Ared.png'))
Traceback (most recent call last):
  File "preprocessing.py", line 16, in <module>
    cv2.imshow('skeleton', skeleton)
TypeError: Expected Ptr<cv::UMat> for argument '%s'

Answer 1

Bad exception messages are bad...

cv2.imshow does not handle binary arrays. The acceptable types according to this answer are uint8 , uint16 , int , float , and double .

you should be able to convert the array to uint8 with:

skeleton.astype('u1')

This will leave you with values between 0 and 1 though, which is all very dark. If you the multiply the array by 255, the colors should be black and white as expected:

skeleton.astype('u1') * 255

full example with data image from skimage:

from cv2 import cv2
from skimage.filters import threshold_otsu
from skimage.morphology import skeletonize
from skimage.util import invert
from skimage.data import camera

img = camera()
binary = img > threshold_otsu(img)
skeleton = skeletonize(invert(binary))
cv2.imshow('original', img)
cv2.imshow('skeleton', skeleton.astype('u1')*255)
cv2.waitKey(0)
cv2.destroyAllWindows()

Answer 2

Your format is wrong. You need to change it to float32. That's a common error with opencv. You can change this line to convert it to float32 and it should work fine.

cv2.imshow('skeleton', np.float32(skeleton))