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import cv2 | |
import numpy as np | |
from annotator.util import make_noise_disk | |
class ContentShuffleDetector: | |
def __call__(self, img, h=None, w=None, f=None): | |
H, W, C = img.shape | |
if h is None: | |
h = H | |
if w is None: | |
w = W | |
if f is None: | |
f = 256 | |
x = make_noise_disk(h, w, 1, f) * float(W - 1) | |
y = make_noise_disk(h, w, 1, f) * float(H - 1) | |
flow = np.concatenate([x, y], axis=2).astype(np.float32) | |
return cv2.remap(img, flow, None, cv2.INTER_LINEAR) | |