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import random
import cv2
import numpy as np
import torch
from PIL import Image
def crop_4_patches(image):
crop_size = int(image.size[0]/2)
return (image.crop((0, 0, crop_size, crop_size)), image.crop((0, crop_size, crop_size, 2*crop_size)),
image.crop((crop_size, 0, 2*crop_size, crop_size)), image.crop((crop_size, crop_size, 2*crop_size, 2*crop_size)))
def pre_processing(image, transform):
high_level = []
middle_level = []
low_level = []
crops_4 = crop_4_patches(image)
for c_4 in crops_4:
crops_8 = crop_4_patches(c_4)
high_level.append(transform(crops_8[0]))
high_level.append(transform(crops_8[3]))
for c_8 in [crops_8[1], crops_8[2]]:
crops_16 = crop_4_patches(c_8)
middle_level.append(transform(crops_16[0]))
middle_level.append(transform(crops_16[3]))
for c_16 in [crops_16[1], crops_16[2]]:
crops_32 = crop_4_patches(c_16)
low_level.append(transform(crops_32[0]))
low_level.append(transform(crops_32[3]))
return torch.stack(high_level), torch.stack(middle_level), torch.stack(low_level)
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