4nhg
Public
1 year ago
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Info
4nhg
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Model: Artistic
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Size: 768 X 768 (0.59 MP)
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Used settings:
- Prompt: \begin{lstlisting} import numpy as np def incmatrix(genl1,genl2): m = len(genl1) n = len(genl2) M = None #to become the incidence matrix VT = np.zeros((n*m,1), int) #dummy variable #compute the bitwise xor matrix M1 = bitxormatrix(genl1) M2 = np.triu(bitxormatrix(genl2),1) for i in range(m-1): for j in range(i+1, m): [r,c] = np.where(M2 == M1[i,j]) for k in range(len(r)): VT[(i)*n + r[k]] = 2; VT[(i)*n + c[k]] = 1; VT[(j)*n + r[k]] = 2; VT[(j)*n + c[k]] = 1; if M is None: M = np.copy(VT) else: M = np.concatenate((M, VT), 1) VT = np.zeros((n*m,2), int) return M \end{lstlisting}
- Using base image: Yes (Effect strength - 60%)
- Base image resolution: Default
- Face enhance: No
- Upscale & Enhance: 0
- Aspect Ratio: landscape
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