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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, W 중 짧은 쪽을 resolution과 맞춤 | |
if H > W: | |
k = resolution / W | |
W = resolution | |
H = int(H * k) | |
else: | |
k = resolution / H | |
H = resolution | |
W = int(W * k) | |
input_image = cv2.resize(input_image, (W, H), interpolation=cv2.INTER_CUBIC) | |
# resolution으로 center crop | |
start_w = (W - resolution) // 2 | |
start_h = (H - resolution) // 2 | |
img = input_image[start_h:start_h + resolution, start_w:start_w + resolution] | |
return img | |