Upload dataloader.py

dataloader.py

@@ -0,0 +1,59 @@
+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)
+