import numpy as np
from imageio import imread
from skimage.transform import resize as imresize

def preprocess_input(x, v2=True):
    x = x.astype('float32')
    x = x / 255.0
    if v2:
        x = x - 0.5
        x = x * 2.0
    return x


def _imread(image_name):
        return imread(image_name)


def _imresize(image_array, size):
        return imresize(image_array, size)


def to_categorical(integer_classes, num_classes=2):
    integer_classes = np.asarray(integer_classes, dtype='int')
    num_samples = integer_classes.shape[0]
    categorical = np.zeros((num_samples, num_classes))
    categorical[np.arange(num_samples), integer_classes] = 1
    return categorical