ValueError: Input 0 of layer "generator" is incompatible with the layer about image-super-resolution HOT 1 OPEN

I have a sane problem, now fixed with this: if lr_img.shape[2] == 4:
# If it has four channels, remove the alpha channel (assumed to be the fourth channel)
lr_img = lr_img[:, :, :3]

full code:

 import numpy as np
from PIL import Image
from ISR.models import RRDN, rdn

# Load the image
img = Image.open('dd.png')
# Resize the image to match the expected input shape (e.g., 3 color channels)

# Convert the image to a NumPy array
lr_img = np.array(img)
if lr_img.shape[2] == 4:
    # If it has four channels, remove the alpha channel (assumed to be the fourth channel)
    lr_img = lr_img[:, :, :3]
# Load the pre-trained RDN model
# rdn = RDN(weights='noise-cancel')
rrdn = RRDN(weights='gans')



sr_img = rrdn.predict(lr_img)

# Convert the NumPy array back to an Image object
sr_img = Image.fromarray(sr_img)

# Save the super-resolved image
sr_img.save('output.png')

from image-super-resolution.