Scipy Kmeans exits with TypeError

问题:

When running the code below, I'm getting a TypeError that says:

"File "_vq.pyx", line 342, in scipy.cluster._vq.update_cluster_means TypeError: type other than float or double not supported"

from PIL import Image
import scipy, scipy.misc, scipy.cluster

NUM_CLUSTERS = 5

im = Image.open('d:/temp/test.jpg')
ar = scipy.misc.fromimage(im)
shape = ar.shape
ar = ar.reshape(scipy.product(shape[:2]), shape[2])
codes, dist = scipy.cluster.vq.kmeans(ar, NUM_CLUSTERS)
vecs, dist = scipy.cluster.vq.vq(ar, codes)
counts, bins = scipy.histogram(vecs, len(codes))

peak = codes[scipy.argmax(counts)]
print 'Most frequent color: %s (#%s)' % (peak, ''.join(chr(c) for c in peak).encode('hex'))

I have no idea how to fix this.

Update:

Full traceback:

Traceback (most recent call last): File "...\temp.py", line 110, in <module> codes, dist = scipy.cluster.vq.kmeans2(ar, NUM_CLUSTERS) File "...\site-packages\scipy\cluster\vq.py", line 642, in kmeans2 new_code_book, has_members = _vq.update_cluster_means(data, label, nc) File "_vq.pyx", line 342, in scipy.cluster._vq.update_cluster_means TypeError: type other than float or double not supported

回答1:

Doing:

ar = ar.reshape(scipy.product(shape[:2]), shape[2])
print(ar.dtype)

you will see, that you call kmeans with data of type uint8.

As kmeans, in theory, is defined on a d-dimensional real vector, scipy also does not like it (as given in the error)!

So just do:

ar = ar.reshape(scipy.product(shape[:2]), shape[2]).astype(float)

Casting like that is making my example run until the print, which also needs to be changed to reflect the given types.