43 lines
1.2 KiB
Python
43 lines
1.2 KiB
Python
import cv2
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import numpy as np
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def canny_k(x, k=0.5):
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import cv2
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H, W, C = x.shape
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Hs, Ws = int(H * k), int(W * k)
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small = cv2.resize(x, (Ws, Hs), interpolation=cv2.INTER_AREA)
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return cv2.Canny(small, 100, 200).astype(np.float32) / 255.0
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def canny_pyramid(x):
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# For some reasons, SAI's Control-lora Canny seems to be trained on canny maps with non-standard resolutions.
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# Then we use pyramid to use all resolutions to avoid missing any structure in specific resolutions.
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ks = [0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0]
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cs = [canny_k(x, k) for k in ks]
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cur = None
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for c in cs:
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if cur is None:
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cur = c
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else:
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H, W = c.shape
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cur = cv2.resize(cur, (W, H), interpolation=cv2.INTER_LINEAR)
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cur = cur * 0.75 + c * 0.25
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cur *= 400.0
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return cur.clip(0, 255).astype(np.uint8)
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def cpds(x):
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import cv2
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# cv2.decolor is not "decolor", it is Cewu Lu's method
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# See http://www.cse.cuhk.edu.hk/leojia/projects/color2gray/index.html
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# See https://docs.opencv.org/3.0-beta/modules/photo/doc/decolor.html
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y = np.ascontiguousarray(x[:, :, ::-1].copy())
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y = cv2.decolor(y)[0]
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return y
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