def transform(self, transform):
if isinstance(transform, collections.abc.MutableSequence):
transform = torchvision.Compose(transform)
self._transform = transform
self.val = val
self.sum += val * n
self.count += n
self.avg = self.sum / self.count
8. Image Dataset Loader:
torchvision.datasets.ImageFolder(root, transform=None, target_transform=None, loader=<function default_loader>)
>>> import torchvision.datasets as datasets
>>> import torchvision as transforms
>>> transform = transforms.Compose([
transforms.Resize(args.image_size),
transforms.CenterCrop(args.image_size),
transforms.ToTensor(),
transforms.Lambda(lambda x: x.mul(255))
])
>>> dataset = datasets.ImageFolder(dataset_path, transform)
# A generic data loader where the images are arranged in this way:
# root/dog/xxx.png
# root/dog/xxy.png
# root/dog/xxz.png
# root/cat/123.png
# root/cat/nsdf3.png
# root/cat/asd932_.png