# EE4 Selected Topics From Computer Vision Coursework
# Vasil Zlatanov, Nunzio Pucci

CLUSTER_CNT = 1337
KMEAN_PART = 33

import numpy as np
import matplotlib.pyplot as plt

from sklearn.cluster import KMeans

train = []
test = []

train_part = np.hstack(train[0:KMEAN_PART])

kmeans = KMeans(n_clusters=CLUSTER_CNT, random_state=0).fit(train_part)

codewords = []
i = 0

for image in train:
    codewords.append(np.bincount(kmeans.predict(image)
    print codewords[i].shape