I am trying to use pre trained VGG16 with SRGAN and grayscale images when I use the VGG16 in this way:

def build_vgg():
    input_shape = (256, 256, 3)
    # Load a pre-trained VGG19 model trained on 'Imagenet' dataset
    
    vgg = VGG19(weights="imagenet",include_top=False, 
     input_shape=input_shape)
    vgg.trainable = False
return Model(inputs=vgg.inputs, outputs=vgg.layers[10].output)

my model work without any problem and gave grayscale images but when trying to frees the layers of VGG16 and train some layes like this code:

def build_vgg():
    """
    Build the VGG network to extract image features
    """
    input_shape = (256, 256, 3)
    vgg = VGG19(weights='imagenet', include_top=False, input_shape=input_shape)
   
    # Set the layers to be frozen
    for layer in vgg.layers[:8]:
        layer.trainable = False

    # Set the layers to be trainable
    for layer in vgg.layers[8:]:
        layer.trainable = True

    output_layer = vgg.get_layer('block5_conv4').output
    input_layer = vgg.input
    print(vgg.summary())
    model = Model(input_layer, output_layer)
    return model

The generated images be like have blue filter and some time brown filter or all generated images in blue. why this happen and how can I fine tune the VGG16 with gray images??