unet_keras | unet_keras use image Semantic segmentation | Machine Learning library

1. You have to use tensorflow-2 instead of keras.

2. You can't add anything in the loss function and expect it to work, it must be differentiable. You may not need to add preprocessing_input of vgg16 inside the loss, your output from the model shouldn't be perfect images (with range 0-255), they should be already normalized tensors (due to some activations like sigmoid). (Make sure, the VGG16 you're using was also trained with same normalization scheme (0-1) range, as the output from the network will probably pass through an activation function like sigmoid, your output will most likely be in the range(0-1))

Here's a simple model with the loss function of yours: