import gradio as gr import os import requests import json from huggingface_hub import login from css_html_js import custom_css from about import ( CITATION_BUTTON_LABEL, CITATION_BUTTON_TEXT, EVALUATION_QUEUE_TEXT, INTRODUCTION_TEXT, LLM_BENCHMARKS_TEXT, TITLE, ) myip = "0.0.0.0" myport=80 is_spaces = True if "SPACE_ID" in os.environ else False is_shared_ui = False with gr.Blocks() as demo: gr.HTML(TITLE) gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text") with gr.Row() as advlearn: drop = gr.Dropdown(["Object-Church", "Object-Parachute", "Object-Garbage_Truck","Object-Tench", "Style-Van_Gogh","Concept-Nudity"], label="Unlearning undesirable") with gr.Column(): # gr.Markdown("Please upload your model id.") drop_model = gr.Dropdown(["Erased Stable Diffusion(ESD)", "Forget-me-not(FMN)", "Ablating concepts(AC)","Unified Concept Editing(UCE)", "Safe Latent Diffusion(SLD)"], label="Unlearned DMs") with gr.Column(): # gr.Markdown("Please upload your model id.") drop_text = gr.Dropdown(["Object-Church", "Object-Parachute", "Object-Garbage_Truck","Object-Tench", "Style-Van_Gogh","Concept-Nudity", "None"], label="AdvUnlearn Text Encoder") with gr.Row() as attack: text_input = gr.Textbox(label="Prompt") with gr.Row(): with gr.Column(min_width=260): img1 = gr.Image("images/cheetah.jpg",label="Image Generated without AdvUnlearn",width=260,show_share_button=False,show_download_button=False) with gr.Column(): start_button = gr.Button("AdvUnlearn",size='lg') with gr.Column(min_width=260): img2 = gr.Image("images/cheetah.jpg",label="Image Generated with AdvUnlearn",width=260,show_share_button=False,show_download_button=False) demo.launch()