import numpy as np

from time import time

import pdb

import skimage

import matplotlib.pyplot as plt

import data_util

DATA_DIR = 'converted'

files = data_util.get_image_files(DATA_DIR)

images = data_util.load_images(files)

MEAN = data_util.compute_mean(files)

STD = data_util.compute_std(files)

images_normalized = []

for img in images:

img = img - MEAN[:, np.newaxis, np.newaxis]

img = img / STD[:, np.newaxis, np.newaxis]

images_normalized.append(img)

images_normalized = np.array(images_normalized)

original_augmented = data_util.parallel_augment(images)

normalized_augmented = data_util.parallel_augment(images_normalized)

original = images[3]

normalized = images_normalized[3]

original = original.transpose(1, 2, 0)

normalized = normalized.transpose(1, 2, 0)

oa = original_augmented[3]

oa = oa.transpose(1, 2, 0)

na = normalized_augmented[3]

na = na.transpose(1, 2, 0)

fig = plt.figure()

a = fig.add_subplot(2, 2, 1)

plt.imshow(original)

a.set_title('original')

a = fig.add_subplot(2, 2, 2)

plt.imshow(normalized)

a.set_title('normalized')

a = fig.add_subplot(2, 2, 3)

plt.imshow(oa)

a.set_title('original_augmented')

a = fig.add_subplot(2, 2, 4)

plt.imshow(na)

a.set_title('normalized_augmenged')

plt.show()