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import numpy as np
import random
import math
from PIL import Image
from skimage.transform import resize
import skimage
import torch
import matplotlib.pyplot as plt
class CustomResize(object):
def __init__(self, trg_size):
self.trg_size = trg_size
def __call__(self, img):
resized_img = self.resize_image(img, self.trg_size)
return resized_img
def resize_image(self, img_array, trg_size):
res = resize(img_array, trg_size, mode='reflect', preserve_range=True, anti_aliasing=False)
# type check
if type(res) != np.ndarray:
raise "type error!"
# PIL image cannot handle 3D image, only return ndarray type, which ToTensor accepts
return res
class CustomToTensor(object):
def __init__(self):
pass
def __call__(self, pic):
if isinstance(pic, np.ndarray):
img = torch.from_numpy(pic.transpose((2, 0, 1)))
# backward compatibility
return img.float()
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