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from torchvision import transforms | |
def get_transform(type='clip', keep_ratio=True, image_size=224): | |
if type == 'clip': | |
transform = [] | |
if keep_ratio: | |
transform.extend([ | |
transforms.Resize(image_size), | |
transforms.CenterCrop(image_size), | |
]) | |
else: | |
transform.append(transforms.Resize((image_size, image_size))) | |
transform.extend([ | |
transforms.ToTensor(), | |
transforms.Normalize(mean=(0.48145466, 0.4578275, 0.40821073), std=(0.26862954, 0.26130258, 0.27577711)) | |
]) | |
return transforms.Compose(transform) | |
elif type == 'clipa': | |
transform = [] | |
if keep_ratio: | |
transform.extend([ | |
transforms.Resize(image_size), | |
transforms.CenterCrop(image_size), | |
]) | |
else: | |
transform.append(transforms.Resize((image_size, image_size))) | |
transform.extend( | |
[transforms.ToTensor(), transforms.Normalize(mean=(0.485, 0.456, 0.406), std=(0.229, 0.224, 0.225))]) | |
return transforms.Compose(transform) | |
elif type == 'sd': | |
transform = [] | |
if keep_ratio: | |
transform.extend([ | |
transforms.Resize(image_size, interpolation=transforms.InterpolationMode.BICUBIC), | |
transforms.CenterCrop(image_size), | |
]) | |
else: | |
transform.append( | |
transforms.Resize((image_size, image_size), interpolation=transforms.InterpolationMode.BICUBIC)) | |
transform.extend([transforms.ToTensor(), transforms.Normalize([0.5], [0.5])]) | |
return transforms.Compose(transform) | |
else: | |
raise NotImplementedError | |