def cluster_images(data_batch, k, smart_init = False):
fo = open(data_batch, 'rb')
dict = cPickle.load(fo)
fo.close()
m = dict['data']
kmeans_out = kmeans_warm_up.kmeans(m, k, smart_init)
error = kmeans_out['error']
mu = kmeans_out['mu']
resp = kmeans_out['resp']
result = kmeans_out['dist']
# creates cluster directories and saves images
for i in range(k):
if not os.path.exists(str(i)):
os.makedirs(str(i))
get_image(mu[i], str(i) + "/0.png")
num_pts = m.shape[0]
for i in range(num_pts):
get_image(m[i], str(resp[i][0]) + "/" + str(np.min(result[i])) + ".png")
return error
from kmeans_warm_up import kmeans
def unpickle(file):
import cPickle
fo = open(file, 'rb')
dict = cPickle.load(fo)
fo.close()
return dict['data']
kmeans(unpickle('/home/aaron/Downloads/cifar-10-batches-py/data_batch_1'),5)