Spaces:
Running
Running
| import timm | |
| import torchvision | |
| data_config = {'input_size': (3, 384, 384), | |
| 'interpolation': 'bicubic', | |
| 'mean': (0.48145466, 0.4578275, 0.40821073), | |
| 'std': (0.26862954, 0.26130258, 0.27577711), | |
| 'crop_pct': 1.0, | |
| 'crop_mode': 'squash'} | |
| transform_synthetic = timm.data.create_transform(**data_config, is_training=False) | |
| transform_200M = torchvision.transforms.Compose([ | |
| torchvision.transforms.Resize((640, 640)), | |
| torchvision.transforms.ToTensor(), | |
| torchvision.transforms.Normalize(mean=[0.485, 0.456, 0.406], | |
| std=[0.229, 0.224, 0.225]), | |
| ]) | |
| transform_5M = torchvision.transforms.Compose([ | |
| torchvision.transforms.Resize((224, 224)), | |
| torchvision.transforms.ToTensor(), | |
| torchvision.transforms.Normalize(mean=[0.485, 0.456, 0.406], | |
| std=[0.229, 0.224, 0.225]), | |
| ]) |