56 lines
1.5 KiB
Python
Executable File
56 lines
1.5 KiB
Python
Executable File
import os
|
|
from PIL import Image
|
|
|
|
import torch
|
|
|
|
def cid2filename(cid, prefix):
|
|
"""
|
|
Creates a training image path out of its CID name
|
|
|
|
Arguments
|
|
---------
|
|
cid : name of the image
|
|
prefix : root directory where images are saved
|
|
|
|
Returns
|
|
-------
|
|
filename : full image filename
|
|
"""
|
|
return os.path.join(prefix, cid[-2:], cid[-4:-2], cid[-6:-4], cid)
|
|
|
|
def pil_loader(path):
|
|
# open path as file to avoid ResourceWarning (https://github.com/python-pillow/Pillow/issues/835)
|
|
with open(path, 'rb') as f:
|
|
img = Image.open(f)
|
|
return img.convert('RGB')
|
|
|
|
def accimage_loader(path):
|
|
import accimage
|
|
try:
|
|
return accimage.Image(path)
|
|
except IOError:
|
|
# Potentially a decoding problem, fall back to PIL.Image
|
|
return pil_loader(path)
|
|
|
|
def default_loader(path):
|
|
from torchvision import get_image_backend
|
|
if get_image_backend() == 'accimage':
|
|
return accimage_loader(path)
|
|
else:
|
|
return pil_loader(path)
|
|
|
|
def imresize(img, imsize):
|
|
img.thumbnail((imsize, imsize), Image.ANTIALIAS)
|
|
return img
|
|
|
|
def flip(x, dim):
|
|
xsize = x.size()
|
|
dim = x.dim() + dim if dim < 0 else dim
|
|
x = x.view(-1, *xsize[dim:])
|
|
x = x.view(x.size(0), x.size(1), -1)[:, getattr(torch.arange(x.size(1)-1, -1, -1), ('cpu','cuda')[x.is_cuda])().long(), :]
|
|
return x.view(xsize)
|
|
|
|
def collate_tuples(batch):
|
|
if len(batch) == 1:
|
|
return [batch[0][0]], [batch[0][1]]
|
|
return [batch[i][0] for i in range(len(batch))], [batch[i][1] for i in range(len(batch))] |