def load_data_transformers(resize_reso=512, crop_reso=448, swap_num=[7, 7]): center_resize = 600 Normalize = transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]) data_transforms = { 'swap': transforms.Compose([ transforms.Randomswap((swap_num[0], swap_num[1])), ]), 'common_aug': transforms.Compose([ transforms.Resize((resize_reso, resize_reso)), transforms.RandomRotation(degrees=15), transforms.RandomCrop((crop_reso,crop_reso)), transforms.RandomHorizontalFlip(), ]), 'train_totensor': transforms.Compose([ transforms.Resize((crop_reso, crop_reso)), # ImageNetPolicy(), transforms.ToTensor(), transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]), ]), 'val_totensor': transforms.Compose([ transforms.Resize((crop_reso, crop_reso)), transforms.ToTensor(), transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]), ]), 'test_totensor': transforms.Compose([ transforms.Resize((resize_reso, resize_reso)), transforms.CenterCrop((crop_reso, crop_reso)), transforms.ToTensor(), transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]), ]), 'None': None, } return data_transforms
def load_data_transformers(resize_reso=512, crop_reso=448, swap_num=[7, 7]): center_resize = 600 Normalize = transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]) data_transforms = { 'swap': transforms.Compose([ transforms.Resize((resize_reso, resize_reso)), transforms.RandomRotation(degrees=15), transforms.RandomCrop((crop_reso, crop_reso)), transforms.RandomHorizontalFlip(), transforms.Randomswap((swap_num[0], swap_num[1])), ]), 'food_swap': transforms.Compose([ transforms.Resize((resize_reso, resize_reso)), transforms.RandomRotation(degrees=90), #transforms.RandomCrop((crop_reso, crop_reso)), transforms.RandomHorizontalFlip(), transforms.RandomVerticalFlip(), transforms.RandomResizedCrop(size=crop_reso, scale=(0.75, 1)), transforms.Randomswap((swap_num[0], swap_num[1])), ]), 'food_unswap': transforms.Compose([ transforms.Resize((resize_reso, resize_reso)), transforms.RandomRotation(degrees=90), #transforms.RandomCrop((crop_reso, crop_reso)), transforms.RandomHorizontalFlip(), transforms.RandomVerticalFlip(), transforms.RandomResizedCrop(size=crop_reso, scale=(0.75, 1)), ]), 'unswap': transforms.Compose([ transforms.Resize((resize_reso, resize_reso)), transforms.RandomRotation(degrees=15), transforms.RandomCrop((crop_reso, crop_reso)), transforms.RandomHorizontalFlip(), ]), 'train_totensor': transforms.Compose([ transforms.Resize((crop_reso, crop_reso)), #ImageNetPolicy(), transforms.ToTensor(), transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]), ]), 'val_totensor': transforms.Compose([ transforms.Resize((crop_reso, crop_reso)), transforms.ToTensor(), transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]), ]), 'test_totensor': transforms.Compose([ transforms.Resize((resize_reso, resize_reso)), transforms.CenterCrop((crop_reso, crop_reso)), transforms.ToTensor(), transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]), ]), 'None': None, 'Centered_swap': transforms.Compose([ transforms.CenterCrop((center_resize, center_resize)), transforms.Resize((resize_reso, resize_reso)), transforms.RandomRotation(degrees=15), transforms.RandomCrop((crop_reso, crop_reso)), transforms.RandomHorizontalFlip(), transforms.Randomswap((swap_num[0], swap_num[1])), ]), 'Centered_unswap': transforms.Compose([ transforms.CenterCrop((center_resize, center_resize)), transforms.Resize((resize_reso, resize_reso)), transforms.RandomRotation(degrees=15), transforms.RandomCrop((crop_reso, crop_reso)), transforms.RandomHorizontalFlip(), ]), 'Tencrop': transforms.Compose([ transforms.Resize((resize_reso, resize_reso)), transforms.TenCrop((crop_reso, crop_reso)), transforms.Lambda(lambda crops: torch.stack( [transforms.ToTensor()(crop) for crop in crops])), ]) } return data_transforms
print('train images:', train_pd.shape) print('test images:', test_pd.shape) print('num classes:', cfg['numcls']) print('Set transform') cfg['swap_num'] = 7 data_transforms = { 'swap': transforms.Compose([ transforms.Resize((512, 512)), transforms.RandomRotation(degrees=15), transforms.RandomCrop((448, 448)), transforms.RandomHorizontalFlip(), transforms.Randomswap((cfg['swap_num'], cfg['swap_num'])), ]), 'unswap': transforms.Compose([ transforms.Resize((512, 512)), transforms.RandomRotation(degrees=15), transforms.RandomCrop((448, 448)), transforms.RandomHorizontalFlip(), ]), 'totensor': transforms.Compose([ transforms.Resize((448, 448)), transforms.ToTensor(), transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]), ]), 'None':