opencv错误：输入参数的大小不匹配

我正在使用金字塔进行图像混合...... 我收到 opencv 错误.. 我正在关注官方 opencv 教程。http://docs.opencv.org/3.0-beta/doc/py_tutorials/py_tutorials.html http://docs.opencv.org/3.0-beta/doc/py_tutorials/py_tutorials.html

import cv2
import numpy as np,sys

A = cv2.imread('/home/grayhat/apple.jpg')
B = cv2.imread('/home/grayhat/orange.jpg')

# generate Gaussian pyramid for A
G = A.copy()
gpA = [G]
for i in xrange(6):
    G = cv2.pyrDown(G)
    gpA.append(G)

# generate Gaussian pyramid for B
G = B.copy()
gpB = [G]
for i in xrange(6):
    G = cv2.pyrDown(G)
    gpB.append(G)

# generate Laplacian Pyramid for A
lpA = [gpA[5]]
for i in xrange(5,0,-1):
   GE = cv2.pyrUp(gpA[i])
   L = cv2.subtract(gpA[i-1],GE)
   lpA.append(L)

# generate Laplacian Pyramid for B
lpB = [gpB[5]]
for i in xrange(5,0,-1):
    GE = cv2.pyrUp(gpB[i])
    L = cv2.subtract(gpB[i-1],GE)
    lpB.append(L)

# Now add left and right halves of images in each level
LS = []
for la,lb in zip(lpA,lpB):
    rows,cols,dpt = la.shape
    ls = np.hstack((la[:,0:cols/2], lb[:,cols/2:]))
    LS.append(ls)

# now reconstruct
ls_ = LS[0]
for i in xrange(1,6):
    ls_ = cv2.pyrUp(ls_)
    ls_ = cv2.add(ls_, LS[i])

# image with direct connecting each half
real = np.hstack((A[:,:cols/2],B[:,cols/2:]))

cv2.imwrite('Pyramid_blending2.jpg',ls_)
cv2.imwrite('Direct_blending.jpg',real)

以下是错误：-

OpenCV Error: Sizes of input arguments do not match (The operation is neither 'array op array' (where arrays have the same size and the same number of channels), nor 'array op scalar', nor 'scalar op array') in arithm_op, file /build/buildd/opencv-2.4.8+dfsg1/modules/core/src/arithm.cpp, line 1287
Traceback (most recent call last):
  File "programs/test11.py", line 25, in <module>
    L = cv2.subtract(gpA[i-1],GE)
cv2.error: /build/buildd/opencv-2.4.8+dfsg1/modules/core/src/arithm.cpp:1287: error: (-209) The operation is neither 'array op array' (where arrays have the same size and the same number of channels), nor 'array op scalar', nor 'scalar op array' in function arithm_op

看来您没有在这里正确生成高斯金字塔：

# generate Gaussian pyramid for A
G = A.copy()
gpA = [G]
for i in xrange(6):
    G = cv2.pyrDown(G)
    gpA.append(G)

根据 OpenCV 文档CV2.pyrDown http://docs.opencv.org/3.0-beta/modules/imgproc/doc/filtering.html#pyrdown，如果您不指定dstsize，它将默认为((src.cols+1)/2, (src.rows+1)/2)。但是，你总是在原始数据上进行下采样G复制。 如果我理解正确，我认为你必须将它应用到最后一个下采样图像上：

# generate Gaussian pyramid for A
G = A.copy()
gpA = [G]
for i in xrange(6):
    G = cv2.pyrDown(gpA[i])
    gpA.append(G)

显然，这同样适用于你的B金字塔.

现在，如果您的图像具有偶数形状但不具有奇数形状，则您的脚本将起作用，因为如何cv2.pyrDown计算默认大小。在这种情况下，你必须给予cv2.pyrUp正确的dstsize参数根据您用来执行操作的图像cv2.substract (or cv2.add).

# generate Laplacian Pyramid for A
lpA = [gpA[5]]
for i in xrange(5,0,-1):
    size = (gpA[i-1].shape[1], gpA[i-1].shape[0])
    GE = cv2.pyrUp(gpA[i], dstsize = size)
    L = cv2.subtract(gpA[i-1],GE)
    lpA.append(L)

# generate Laplacian Pyramid for B
lpB = [gpB[5]]
for i in xrange(5,0,-1):
    size = (gpB[i-1].shape[1], gpB[i-1].shape[0])
    GE = cv2.pyrUp(gpB[i], dstsize = size)
    L = cv2.subtract(gpB[i-1],GE)
    lpB.append(L)

那么，这一点也适用于重建部分：

# now reconstruct
ls_ = LS[0]
for i in xrange(1,6):
    size = (LS[i].shape[1], LS[i].shape[0])
    ls_ = cv2.pyrUp(ls_, dstsize = size)
    ls_ = cv2.add(ls_, LS[i])