给定一个输入图像,例如带有一些圆形物体(例如硬币)的 jpg,我想找到它们各自的直径。
感谢这个问题(How to find the diameter of objects using image processing in Python?) ,我知道如何识别物体,但我想测量我插入的图像的直径,而不是用方法随机生成。我该怎么做?
import numpy as np
from scipy import ndimage
from matplotlib import pyplot as plt
# generate some lowpass-filtered noise as a test image
gen = np.random.RandomState(0)
img = gen.poisson(2, size=(512, 512))
img = ndimage.gaussian_filter(img.astype(np.double), (30, 30))
img -= img.min()
img /= img.max()
# use a boolean condition to find where pixel values are > 0.75
blobs = img > 0.75
# label connected regions that satisfy this condition
labels, nlabels = ndimage.label(blobs)
# find their centres of mass. in this case I'm weighting by the pixel values in
# `img`, but you could also pass the boolean values in `blobs` to compute the
# unweighted centroids.
r, c = np.vstack(ndimage.center_of_mass(img, labels, np.arange(nlabels) + 1)).T
# find their distances from the top-left corner
d = np.sqrt(r*r + c*c)
# plot
fig, ax = plt.subplots(1, 2, sharex=True, sharey=True, figsize=(10, 5))
ax[0].imshow(img)
ax[1].hold(True)
ax[1].imshow(np.ma.masked_array(labels, ~blobs), cmap=plt.cm.rainbow)
for ri, ci, di in zip(r, c, d):
ax[1].annotate('', xy=(0, 0), xytext=(ci, ri),
arrowprops={'arrowstyle':'<-', 'shrinkA':0})
ax[1].annotate('d=%.1f' % di, xy=(ci, ri), xytext=(0, -5),
textcoords='offset points', ha='center', va='top',
fontsize='x-large')
for aa in ax.flat:
aa.set_axis_off()
fig.tight_layout()
plt.show()
我是新来的,所以我不知道如何玩得很好,这段代码生成的图像在我所在问题的链接中。