example
. 这应该显示图像处理结果。
from scipy import ndimage as ndi
import matplotlib.pyplot as plt
from scipy import misc
import numpy as np
import cv2
from skimage.morphology import watershed, disk
from skimage import data
from skimage.filters import rank
from skimage.util import img_as_ubyte
from skimage import io; io.use_plugin('matplotlib')
image = img_as_ubyte('imagepath.jpg')
denoised = rank.median(image, disk(2))
markers = rank.gradient(denoised, disk(5)) < 10
markers = ndi.label(markers)[0]
gradient = rank.gradient(denoised, disk(2))
labels = watershed(gradient, markers)
fig, axes = plt.subplots(nrows=2, ncols=2, figsize=(8, 8),
sharex=True, sharey=True)
ax = axes.ravel()
ax[0].imshow(image, cmap=plt.cm.gray, interpolation='nearest')
ax[0].set_title("Original")
ax[1].imshow(gradient, cmap=plt.cm.nipy_spectral, interpolation='nearest')
ax[1].set_title("Local Gradient")
ax[2].imshow(markers, cmap=plt.cm.nipy_spectral, interpolation='nearest')
ax[2].set_title("Markers")
ax[3].imshow(image, cmap=plt.cm.gray, interpolation='nearest')
ax[3].imshow(labels, cmap=plt.cm.nipy_spectral, interpolation='nearest', alpha=.7)
ax[3].set_title("Segmented")
for a in ax:
a.axis('off')
fig.tight_layout()
plt.show()
我得到以下错误。
Traceback (most recent call last):
File "/home/workspace/calculate_watershed.py", line 15, in <module>
image = img_as_ubyte('koralle0.jpg')
File "/home/workspace/venv/lib/python3.5/site-packages/skimage/util/dtype.py", line 409, in img_as_ubyte
return convert(image, np.uint8, force_copy)
File "/home/workspace/venv/lib/python3.5/site-packages/skimage/util/dtype.py", line 113, in convert
.format(dtypeobj_in, dtypeobj_out))
ValueError: Can not convert from <U12 to uint8.
图像的路径是有值的。你知道怎么解决这个问题吗?提前谢谢