#---------------------------------------------------------------
# make a codebook
x_train = pickle.load(open('./datasets/train_img.npy', 'rb'))
x_test = pickle.load(open('./datasets/test_img.npy', 'rb'))
y_train = pickle.load(open('./datasets/train_label.txt', 'rb'))
y_test = pickle.load(open('./datasets/test_label.txt', 'rb'))
strong_des = sift.dense_sift_each() # dense SIFT
# weak_des = sift.weak_des_whole() # original SIFT
codebook_path = './codebook/km_center_dense_200_caltech'
K_means.clustering(strong_des, codebook_path, n_cluster=200)
#---------------------------------------------------------------
# train, test에 해당하는 level 0, 1, 2의 PHOW(pyramid histogram of word)를 저장
codebooks = codebook.load_codebook(codebook_path)
tr_sl_0 = single_level(cal_train, 0, codebooks)
tr_sl_1 = single_level(cal_train, 1, codebooks)
tr_sl_2 = single_level(cal_train, 2, codebooks)
ts_sl_0 = single_level(cal_test, 0, codebooks)
ts_sl_1 = single_level(cal_test, 1, codebooks)
ts_sl_2 = single_level(cal_test, 2, codebooks)
tr_pyramid_L0 = tr_sl_0 # book 추가
