import scipy.io as scio
import numpy as np
def load_ft(data_dir, feature_name='GVCNN'):
data = scio.loadmat(data_dir)
lbls = data['Y'].astype(np.long)
if lbls.min() == 1:
lbls = lbls - 1
idx = data['indices'].item()
if feature_name == 'MVCNN':
fts = data['X'][0].item().astype(np.float32)
elif feature_name == 'GVCNN':
fts = data['X'][1].item().astype(np.float32)
else:
print(f'wrong feature name{feature_name}!')
raise IOError
idx_train = np.where(idx == 1)[0]
idx_test = np.where(idx == 0)[0]
return fts, lbls, idx_train, idx_test
