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我正在尝试将 WLS 过滤器应用于从图像中获得的亮度层

print("Applying wls filter on base image")
face_structure_layer, skin_detail_layer = wls_filter.wlsfilter_layer(lightness_layer,cmat)

但是当我运行这个时，会抛出这个错误 [TypeError: order must be str, not int][1]

这是我正在使用的 WLS 过滤器的代码

import cv2
import sys
import numpy as np

import matplotlib.pyplot as plt
from scipy.sparse import spdiags
from scipy.sparse.linalg import spsolve

def wlsfilter_layer(image_orig, cmat, beta=0.2 ,lambda_=0.2):

    image = image_orig.astype(np.float)/255.0
    image1 = image.flatten()
    s = image.shape()
    k = np.prod(s)

    gmat = cmat.copy()
    for y in range(s[0]):
        for x in range(s[1]):
            if not gmat[y][x]==1:
                gmat[y][x]=0

    gmat = cv2.GaussianBlur(gmat,(5,5),0)



    dy = np.diff(image, 1, 0)
    dx = np.diff(image, 1, 1)

    dy = -beta*lambda_ / ((np.absolute(dy) ** 1.2 + 0.0001))
    dx = -beta*lambda_ / ((np.absolute(dx) ** 1.2 + 0.0001))

    for y in range(s[0]-1):
        for x in range(s[1]-1):
            dy[y][x] = (gmat[y][x])*dy[y][x]
            dx[y][x] = (gmat[y][x])*dx[y][x]

    dy = np.vstack((dy, np.zeros(s[1], )))
    dx = np.hstack((dx, np.zeros(s[0], )[:, np.newaxis]))

    dy = dy.flatten(1)
    dx = dx.flatten(1)

    d = 1 - (dx + np.roll(dx, s[0]) + dy + np.roll(dy, 1))

    a = spdiags(np.vstack((dx, dy)), [-s[0], -1], k, k)
    a = a + a.T + spdiags(d, 0, k, k)

    temp = spsolve(a, image1).reshape(s[::-1])

    base = np.rollaxis(temp,1)
    detail = image - base

    return (base*255.0), (detail*255.0)

如果我单独运行 WLS 过滤器，它可以工作我使用不同类型的 np.flatten 检查，但它仍然抛出相同的错误 [1]：https ://i.stack.imgur.com/veAfo.jpg

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