def load_data(resize):
data_transforms = {
'train': transforms.Compose([
transforms.RandomSizedCrop(max(resize)),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
]),
'val': transforms.Compose([
#Higher scale-up for inception
transforms.Scale(int(max(resize)/224*256)),
transforms.CenterCrop(max(resize)),
transforms.ToTensor(),
transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
]),
}
data_dir = 'PlantVillage'
dsets = {x: datasets.ImageFolder(os.path.join(data_dir, x), data_transforms[x])
for x in ['train', 'val']}
dset_loaders = {x: torch.utils.data.DataLoader(dsets[x], batch_size=batch_size,
shuffle=True)
for x in ['train', 'val']}
dset_sizes = {x: len(dsets[x]) for x in ['train', 'val']}
dset_classes = dsets['train'].classes
return dset_loaders['train'], dset_loaders['val']
train.py 文件源码
python
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