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import os
import sys
import torch
import torch.utils.data as data
import numpy as np
from PIL import Image
import glob
import random
import cv2
random.seed(1143)
def populate_train_list(lowlight_images_path):
image_list_lowlight = glob.glob(lowlight_images_path + "*.jpg")
train_list = image_list_lowlight
random.shuffle(train_list)
return train_list
class lowlight_loader(data.Dataset):
def __init__(self, lowlight_images_path):
self.train_list = populate_train_list(lowlight_images_path)
self.size = 256
self.data_list = self.train_list
print("Total training examples:", len(self.train_list))
def __getitem__(self, index):
data_lowlight_path = self.data_list[index]
data_lowlight = Image.open(data_lowlight_path)
data_lowlight = data_lowlight.resize((self.size,self.size), Image.ANTIALIAS)
data_lowlight = (np.asarray(data_lowlight)/255.0)
data_lowlight = torch.from_numpy(data_lowlight).float()
return data_lowlight.permute(2,0,1)
def __len__(self):
return len(self.data_list)
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