print("Number of images: {}".format(len(X)))
# start = time()
# result = data.batch_perturb_and_augment(X, 500, 500, aug_params=aug_params, sigma=0.5)
# end = time()
# print("Processing without parallelization took {} seconds".format(end - start))
#start = time()
#result = data.parallel_perturb_and_augment(X, 500, 500, aug_params=aug_params, sigma=0.5)
#result = data.parallel_perturb_and_augment(X, 500, 500)
#end = time()
#print("Processing with parallelization took {} seconds".format(end - start))
start = time()
result = data_util.parallel_augment(X)
end = time()
print("Processing with parallelization (different version) took {} seconds".
format(end - start))
original_image = X[12]
original_image = original_image.transpose(1, 2, 0)
augmented_image = result[12]
augmented_image = augmented_image.transpose(1, 2, 0)
fig = plt.figure()
a = fig.add_subplot(1, 2, 1)
plt.imshow(original_image)
a.set_title('Before')
a = fig.add_subplot(1, 2, 2)
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')