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from torchvision.transforms import transforms as tf | |
import torchvision.transforms.functional as F | |
class SquarePad: | |
def __init__(self, color): | |
self.col = color | |
def __call__(self, image): | |
max_wh = max(image.size) | |
p_left, p_top = [(max_wh - s) // 2 for s in image.size] | |
p_right, p_bottom = [ | |
max_wh - (s + pad) for s, pad in zip(image.size, [p_left, p_top]) | |
] | |
padding = (p_left, p_top, p_right, p_bottom) | |
return F.pad(image, padding, self.col, "constant") | |
def valid_tf(size): | |
return tf.Compose( | |
[ | |
SquarePad(255), | |
tf.Resize(size), | |
tf.ToTensor(), | |
tf.Normalize( | |
mean=(0.48145466, 0.4578275, 0.40821073), | |
std=(0.26862954, 0.26130258, 0.27577711), | |
), | |
] | |
) |