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Searched
full:cluster_n
(Results
1 - 2
of
2
) sorted by null
/external/opencv3/samples/python2/
kmeans.py
19
cluster_n
= 5
variable
25
colors = np.zeros((1,
cluster_n
, 3), np.uint8)
27
colors[0,:,0] = np.arange(0, 180, 180.0/
cluster_n
)
32
points, _ = make_gaussians(
cluster_n
, img_size)
35
ret, labels, centers = cv2.kmeans(points,
cluster_n
, None, term_crit, 10, 0)
gaussian_mix.py
7
def make_gaussians(
cluster_n
, img_size):
10
for i in xrange(
cluster_n
):
30
cluster_n
= 5
variable
37
points, ref_distrs = make_gaussians(
cluster_n
, img_size)
40
em = cv2.EM(
cluster_n
, cv2.EM_COV_MAT_GENERIC)
Completed in 389 milliseconds