The Skeletonize function output wrong figure.

[Huizhong-Wu]

Description:

Hi, I tried to extract the skeleton figures of some artificial conducts using the original code posted on the web: https://scikit-image.org/docs/stable/auto_examples/edges/plot_skeleton.html#sphx-glr-download-auto-examples-edges-plot-skeleton-py
But there was always a wrong hint: ValueError: arrays must be of dtype byte, short, float32 or float64.

So, I transformed the image datatype into float as below. Unfortunately, the output skeleton figure is wrong. I post it at the end of the code. I thought maybe the ball.png cannot be recognized by the skeletonize function, since it was colorful and a screenshot. So, I tried the sample horse picture using the revised code. As you see, the skeleton of horse was still wrong.

Is there anyone could tell me how to get the wright skeleton picture using the Skeletonize function?

Thanks a lot.
Huizhong

Way to reproduce:

from skimage.morphology import skeletonize
from skimage import data
import matplotlib.pyplot as plt
from skimage.util import invert, img_as_float

Invert the ball image

path = 'C:/Users/63517/anaconda3/pkgs/scikit-image-0.20.0-py311h3513d60_0/Lib/site-packages/skimage/data/ball.png'
image = plt.imread(path)
img_f = img_as_float(image, force_copy=False)

perform skeletonization

skeleton = skeletonize(img_f)
ske = img_as_float(skeleton, force_copy=False)

display results

fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(8, 4), sharex=True, sharey=True)

ax = axes.ravel()

ax[0].imshow(img_f, cmap=plt.cm.gray)
ax[0].axis('off')
ax[0].set_title('original', fontsize=20)

ax[1].imshow(ske, cmap=plt.cm.gray)
ax[1].axis('off')
ax[1].set_title('skeleton', fontsize=20)

fig.tight_layout()
plt.show()

Version information:

No response

[soupault]

@Huizhong-Wu hi, thanks for reporting! Could you provide the versions of your scikit-image, scipy, and numpy?

[Huizhong-Wu]

@soupault hi, the version of my scikit-image is 0.23.2, the scipy is 1.11.4, and the numpy is 1.26.2

I converted the color picture into gray-scale, but it still doesn't work.

[Huizhong-Wu]

I also binarized the picture value, but the results were still not so good.