Incompatibility to pytorch: Some transformations return lists for singe Image

The pipeline is not compatible with pytorch because the operations return lists [ <PIL.Image.Image image mode=L size=28x28 at 0x7F4C6F113A90>] but expect as input: <PIL.Image.Image image mode=L size=28x28 at 0x7F4C6F113A90>

Here a minimalistic example, where I show what the MNIST dataloader does internally and why it fails…

import Augmentor
from torchvision import datasets, transforms
from torch.utils import data

loader = data.DataLoader(datasets.MNIST('./../data', download=True, transform=transforms.Compose([transforms.ToTensor()])))

p1 = Augmentor.Pipeline()
p1.zoom(probability=1, min_factor=1.1, max_factor=1.5)
p1 = p1.torch_transform()

p2 = Augmentor.Pipeline()
p2.shear(probability=1, max_shear_left=5, max_shear_right=5)
p2 = p2.torch_transform()
# test it
for i, (batch, label) in enumerate(loader):
    batch = transforms.ToPILImage()(batch[0])
    batch = p1(batch)  
    print(batch)           # prints [<PIL.Image.Image image mode=L size=28x28 at 0x7F4BE1BF9470>]
    batch = p2(batch)      # expects list --> fails, works if I do p2(batch[0])
    print('batch', batch)
    break

[lukas-schott]

workaround:

def from_list(x):
    if isinstance(x, list):
        return x[0]
    else:
        return x


loader = data.DataLoader(datasets.MNIST('./../data', download=True, transform=transforms.Compose([
                p1, from_list, p2, from_list, transforms.ToTensor()])))

[genghisun]

Hi~ Is this problem fixed?