def METHOD_NAME(self, input: Input, max_image_size=1024):
    assert len(input) == 2, 'input should be a list of two images'
    img1 = self.load_image(input[0])
    img1, scale1 = self.resize_image(img1, max_image_size)
    scaled_h1, scaled_w1 = img1.shape[:2]
    img2 = self.load_image(input[1])
    img2, scale2 = self.resize_image(img2, max_image_size)
    scaled_h2, scaled_w2 = img2.shape[:2]
    h_max, w_max = max(scaled_h1, scaled_h2), max(scaled_w1, scaled_w2)
    img1 = self.pad_image(img1, h_max, w_max)
    img2 = self.pad_image(img2, h_max, w_max)
    img1 = torch.from_numpy(img1)[None][None].cuda().float()
    img2 = torch.from_numpy(img2)[None][None].cuda().float()
    return {
        'image0':
        img1,
        'image1':
        img2,
        'preprocess_info':
        [scale1, scale2, scaled_h1, scaled_w1, scaled_h2, scaled_w2]
    }