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''' | |
* Copyright (c) 2023 Salesforce, Inc. | |
* All rights reserved. | |
* SPDX-License-Identifier: Apache License 2.0 | |
* For full license text, see LICENSE.txt file in the repo root or http://www.apache.org/licenses/ | |
* By Can Qin | |
* Modified from ControlNet repo: https://github.com/lllyasviel/ControlNet | |
* Copyright (c) 2023 Lvmin Zhang and Maneesh Agrawala | |
''' | |
import numpy as np | |
import cv2 | |
import os | |
annotator_ckpts_path = os.path.join(os.path.dirname(__file__), 'ckpts') | |
def HWC3(x): | |
assert x.dtype == np.uint8 | |
if x.ndim == 2: | |
x = x[:, :, None] | |
assert x.ndim == 3 | |
H, W, C = x.shape | |
assert C == 1 or C == 3 or C == 4 | |
if C == 3: | |
return x | |
if C == 1: | |
return np.concatenate([x, x, x], axis=2) | |
if C == 4: | |
color = x[:, :, 0:3].astype(np.float32) | |
alpha = x[:, :, 3:4].astype(np.float32) / 255.0 | |
y = color * alpha + 255.0 * (1.0 - alpha) | |
y = y.clip(0, 255).astype(np.uint8) | |
return y | |
def resize_image(input_image, resolution): | |
H, W, C = input_image.shape | |
H = float(H) | |
W = float(W) | |
k = float(resolution) / min(H, W) | |
H *= k | |
W *= k | |
H = int(np.round(H / 64.0)) * 64 | |
W = int(np.round(W / 64.0)) * 64 | |
img = cv2.resize(input_image, (W, H), interpolation=cv2.INTER_LANCZOS4 if k > 1 else cv2.INTER_AREA) | |
return img | |