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41 lines
1.2 KiB
Python
41 lines
1.2 KiB
Python
# Adapted from https://github.com/huggingface/controlnet_aux
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import cv2
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import numpy as np
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from PIL import Image
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from invokeai.backend.image_util.util import np_to_pil, pil_to_np
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def make_noise_disk(H, W, C, F):
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noise = np.random.uniform(low=0, high=1, size=((H // F) + 2, (W // F) + 2, C))
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noise = cv2.resize(noise, (W + 2 * F, H + 2 * F), interpolation=cv2.INTER_CUBIC)
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noise = noise[F : F + H, F : F + W]
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noise -= np.min(noise)
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noise /= np.max(noise)
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if C == 1:
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noise = noise[:, :, None]
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return noise
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def content_shuffle(input_image: Image.Image, scale_factor: int | None = None) -> Image.Image:
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"""Shuffles the content of an image using a disk noise pattern, similar to a 'liquify' effect."""
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np_img = pil_to_np(input_image)
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height, width, _channels = np_img.shape
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if scale_factor is None:
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scale_factor = 256
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x = make_noise_disk(height, width, 1, scale_factor) * float(width - 1)
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y = make_noise_disk(height, width, 1, scale_factor) * float(height - 1)
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flow = np.concatenate([x, y], axis=2).astype(np.float32)
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shuffled_img = cv2.remap(np_img, flow, None, cv2.INTER_LINEAR)
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output_img = np_to_pil(shuffled_img)
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return output_img
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