loader = transforms.Compose([
transforms.Resize(imsize), # scale imported image on shortest length
transforms.ToTensor()
]) # transform it into a torch tensor
# Verify image path
style_path = input("Path to Style: ")
while not os.path.isfile(style_path):
style_path = input('E: Image not found. Path to Style: ')
# Verify content path
content_path = input("Path to Content: ")
while not os.path.isfile(content_path):
content_path = input('E: Image not found. Path to Content: ')
style_img = img_handler.image_loader(device, loader, style_path)
content_img = img_handler.image_loader(device, loader, content_path)
# TODO remove once image size class is implemented
assert style_img.size() == content_img.size(), \
"we need to import style and content imsages of the same size"
unloader = transforms.ToPILImage() # reconvert into PIL image
if plt_prvs:
plt.ion()
plt.figure()
img_handler.imshow(style_img, unloader, title='Style Image')
plt.figure()
img_handler.imshow(content_img, unloader, title='Content Image')
