I want to preprocess such an image dataset using an unsupervised wiener algorithm. But it doesn't work properly. when I run the code, it shows me a value attribute error. For convenience, my code is given below -
import cv2
import glob
from matplotlib import pyplot as plt
from skimage import io, restoration, img_as_float
import scipy.stats as st
import numpy as np
dataset = glob.glob('input/train/*.png')
directory = 'output/train/'
for img_id, img_path in enumerate(dataset):
img = img_as_float(io.imread(img_path))
def gkern(kernlen=21, nsig=2): #Returns a 2D Gaussian kernel.
lim = kernlen//2 + (kernlen % 2)/2
x = np.linspace(-lim, lim, kernlen+1)
kern1d = np.diff(st.norm.cdf(x))
kern2d = np.outer(kern1d, kern1d)
return kern2d/kern2d.sum()
psf = gkern(5,3) #Kernel length and sigma
deconvolved, _ = restoration.unsupervised_wiener(img, psf)
cl2 = cv2.resize(deconvolved, (512,512), interpolation = cv2.INTER_CUBIC)
plt.imsave(f"output/unsupervised_{img_id}.png", cl2, cmap='gray')
I am getting the error :
File "C:\Users\Junaed\.spyder-py3\unsupervised_wiener.py", line 33, in <module>
deconvolved, _ = restoration.unsupervised_wiener(img, psf)
ValueError: could not broadcast input array from shape (5,5) into shape (5,5,4)
How could I fix this issue, Can someone help me here?