Image-to-Image Translation Using Conditional DCGANs

create_dataloader.py

class get_dataset(torch.utils.data.Dataset):
  def __init__(self,name='edges2shoes',type_='train',transform=None):
    self.dir_=name+'/'+name+'/'+type_
    self.img_list=sorted(os.listdir(self.dir_))
    self.transform=transform
  def __len__(self):
    return len(self.img_list)
  def __getitem__(self,idx):
    both=plt.imread(self.dir_+'/'+self.img_list[idx]).astype('uint8')
    x=both[:,:both.shape[1]//2,:]
    y=both[:,both.shape[1]//2:,:]
    x,y=self.transform(Image.fromarray(x)),self.transform(Image.fromarray(y))
    return x,y   

img_size=128
batch_size=32

my_transform=transforms.Compose([transforms.Resize((img_size,img_size)),transforms.ToTensor()])
dataset_edges2shoes=get_dataset(name='edges2shoes',type_='val',transform=my_transform)

dataloader=torch.utils.data.DataLoader(dataset_edges2shoes,batch_size=batch_size,shuffle=True,drop_last=True)