python中的离散小波变换和逆离散小波变换TypeError

Question

我目前正在做一个图像处理项目。我是蟒蛇的新手。任何帮助将不胜感激。我正在使用离散小波变换将图像分解为带并修改系数。所以下面的代码给了我一个错误。 这是代码

`import cv2
import numpy as np
from PIL import Image
import numpy
from pywt import dwt2, idwt2
from random import Random
import random
import pywt

img = cv2.imread('xyy.png')
def im2double(im):
min_val = np.min(im.ravel())
max_val = np.max(im.ravel())
out = (im.astype('float') - min_val) / (max_val - min_val)
return out
k=2
cover_object=im2double(img)
Mc=np.shape(cover_object)
Nc=np.shape(cover_object)
print(Mc[0],Nc[1])
#watermark image
water = cv2.imread('1.png')
gray_image = cv2.cvtColor(water, cv2.COLOR_BGR2GRAY)
xy=cv2.imwrite('grayim.png',gray_image) 
messagee = cv2.imread('grayim.png')
file_name1=im2double(messagee)
print(file_name1)
a=np.shape(gray_image)
b=a[0]*a[1]
images_rss = gray_image.reshape([b, 1])/256
print(images_rss)
np.random.seed(0)
key=round(100*numpy.random.rand(1))
print(key)
cA, (cH, cV, cD) = dwt2(img, 'haar')
leng=len(images_rss)
#print(leng)
for kk in range(1,leng):
q = 2*(random.randint(512/2,512/2)-0.5)
pn_sequence_h=round(q,0)
w = 2*(random.randint(512/2,512/2)-0.5)
pn_sequence_v=round(w,0)
#print(pn_sequence_h)
if (file_name1(kk) == 0):
cH=cH+k*pn_sequence_h
cV=cV+k*pn_sequence_v
idwt2(cA,cH,cV,cD,'haar')[:Mc,:Nc]

下面是错误

Traceback (most recent call last):
File "stack.py", line 53, in <module>
if (file_name1(kk) == 0):
TypeError: 'numpy.ndarray' object is not callable

如何摆脱此错误？另外请告诉 DWT 和 IDWT 语法是否正确？

Answer 1

import cv2
import numpy as np
from PIL import Image
import numpy
from pywt import dwt2, idwt2
from random import Random
import random
import pywt

img = cv2.imread('xyy.png')
def im2double(im):
min_val = np.min(im.ravel())
max_val = np.max(im.ravel())
out = (im.astype('float') - min_val) / (max_val - min_val)
return out
k=2
cover_object=im2double(img)
Mc=np.shape(cover_object)
Nc=np.shape(cover_object)
print(Mc[0],Nc[1])
#watermark image
water = cv2.imread('1.png')
gray_image = cv2.cvtColor(water, cv2.COLOR_BGR2GRAY)
xy=cv2.imwrite('grayim.png',gray_image) 
messagee = cv2.imread('grayim.png')
file_name1=im2double(messagee)
print(file_name1)
a=np.shape(gray_image)
b=a[0]*a[1]
images_rss = gray_image.reshape([b, 1])/256
print(images_rss)
np.random.seed(0)
key=round(100*numpy.random.rand(1))
print(key)
cA, (cH, cV, cD) = dwt2(img, 'haar')
leng=len(images_rss)
#print(leng)
for kk in range(1,leng):
q = 2*(random.randint(512/2,512/2)-0.5)
pn_sequence_h=round(q,0)
w = 2*(random.randint(512/2,512/2)-0.5)
pn_sequence_v=round(w,0)
#print(pn_sequence_h)
if (file_name1[kk] == 0.0):
cH=cH+k*pn_sequence_h
cV=cV+k*pn_sequence_v
coeffs1 = (cA, (cH, cV, cD) )           
watermarked_image = np.array(pywt.idwt2(coeffs1, 'haar'),np.uint8);