Commit 2d55b9d5 authored by Soumith Chintala's avatar Soumith Chintala Committed by GitHub
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Merge pull request #10 from pytorch/cifarfix

making cifar data loader also return PIL Image
parents 98b9aa54 05bcb18e
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...@@ -78,6 +78,10 @@ class CIFAR10(data.Dataset): ...@@ -78,6 +78,10 @@ class CIFAR10(data.Dataset):
else: else:
img, target = self.test_data[index], self.test_labels[index] img, target = self.test_data[index], self.test_labels[index]
# doing this so that it is consistent with all other datasets
# to return a PIL Image
img = Image.fromarray(np.transpose(img, (1,2,0)))
if self.transform is not None: if self.transform is not None:
img = self.transform(img) img = self.transform(img)
......
import torch
import math
def make_grid(tensor, nrow=8, padding=2): def make_grid(tensor, nrow=8, padding=2):
""" """
Given a 4D mini-batch Tensor of shape (B x C x H x W), Given a 4D mini-batch Tensor of shape (B x C x H x W),
or a list of images all of the same size,
makes a grid of images makes a grid of images
""" """
import math tensorlist = None
if isinstance(tensor, list):
tensorlist = tensor
numImages = len(tensorlist)
size = torch.Size(torch.Size([long(numImages)]) + tensorlist[0].size())
tensor = tensorlist[0].new(size)
for i in range(numImages):
tensor[i].copy_(tensorlist[i])
if tensor.dim() == 3: # single image if tensor.dim() == 3: # single image
return tensor return tensor
# make the mini-batch of images into a grid # make the mini-batch of images into a grid
......
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