def imagenet_transform()

in data/dataset.py [0:0]

• 17 lines of code
• 4 McCabe index (conditional complexity)

def imagenet_transform(phase):
    mean, std = [0.485, 0.456, 0.406], [0.229, 0.224, 0.225]

    if phase == 'train':
        transform = transforms.Compose([
            transforms.RandomResizedCrop(224),
            transforms.RandomHorizontalFlip(),
            transforms.ToTensor(),
            transforms.Normalize(mean, std)
        ])
    elif phase == 'test' or phase == 'val':
        transform = transforms.Compose([
            transforms.Resize(256),
            transforms.CenterCrop(224),
            transforms.ToTensor(),
            transforms.Normalize(mean, std)
        ])

    return transform