from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("XLabs-AI/flux-ip-adapter") pipeline = StableDiffusionControlNetPipeline.from_pretrained( "fill-in-base-model", controlnet=controlnet ) import gradio as gr from filters import as_gray def process(input_image): output_image = as_gray(input_image) return output_image demo = gr.Interface( process, "image", "image", examples=["lion.jpg", "logo.png"], ) demo.launch() from skimage.color import rgb2gray def as_gray(image): return rgb2gray(image) # Same syntax as requirements.txt scikit-image