utils_inpaint.py

from typing import Tuple
import numpy as np
import torch

def resize_image_dimensions(
    original_resolution_wh: Tuple[int, int],
    maximum_dimension: int = 2048
) -> Tuple[int, int]:
    width, height = original_resolution_wh

    if width <= maximum_dimension and height <= maximum_dimension:
        width = width - (width % 32)
        height = height - (height % 32)
        return width, height

    if width > height:
        scaling_factor = maximum_dimension / width
    else:
        scaling_factor = maximum_dimension / height

    new_width = int(width * scaling_factor)
    new_height = int(height * scaling_factor)

    new_width = new_width - (new_width % 32)
    new_height = new_height - (new_height % 32)

    return new_width, new_height

def make_inpaint_condition(init_image, mask_image):
    init_image = np.array(init_image.convert("RGB")).astype(np.float32) / 255.0
    mask_image = np.array(mask_image.convert("L")).astype(np.float32) / 255.0

    assert init_image.shape[0:1] == mask_image.shape[0:1], "image and image_mask must have the same image size"
    init_image[mask_image > 0.5] = -1.0  # set as masked pixel
    init_image = np.expand_dims(init_image, 0).transpose(0, 3, 1, 2)
    init_image = torch.from_numpy(init_image)
    return init_image