load.py

def load_dataset(path):
    data = load_files(path, shuffle=True)
    img_files = np.array(data['filenames'])
    img_targets = np_utils.to_categorical(np.array(data['target']), 3)
    return img_files, img_targets
  
train_files, train_labels = load_dataset('data/train')
valid_files, valid_labels = load_dataset('data/valid')

def load_dataset_no_shuffle(path):
    data = load_files(path, shuffle=False)
    img_files = np.array(data['filenames'])
    img_targets = np_utils.to_categorical(np.array(data['target']), 3)
    return img_files, img_targets
  

test_files , test_labels = load_dataset_no_shuffle('data/test')