import gradio as gr import gradio as gr import os import requests import json from huggingface_hub import login # myip = os.environ["0.0.0.0"] # myport = os.environ["80"] myip = "0.0.0.0" myport=80 is_spaces = True if "SPACE_ID" in os.environ else False is_shared_ui = False 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, ) def excute_udiff(diffusion_model_id, concept, attacker): print(f"my IP is {myip}, my port is {myport}") print(f"my input is diffusion_model_id: {diffusion_model_id}, concept: {concept}, attacker: {attacker}") result = requests.post('http://{}:{}/udiff'.format(myip, myport), json={"diffusion_model_id": diffusion_model_id, "concept": concept, "attacker": attacker}) result = result.text[1:-1] return result css = ''' .instruction{position: absolute; top: 0;right: 0;margin-top: 0px !important} .arrow{position: absolute;top: 0;right: -110px;margin-top: -8px !important} #component-4, #component-3, #component-10{min-height: 0} .duplicate-button img{margin: 0} #img_1, #img_2, #img_3, #img_4{height:15rem} #mdStyle{font-size: 0.7rem} #titleCenter {text-align:center} ''' with gr.Blocks(css=custom_css) as demo: gr.HTML(TITLE) gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text") # gr.Markdown("# Demo of UnlearnDiffAtk.") # gr.Markdown("### UnlearnDiffAtk is an effective and efficient adversarial prompt generation approach for unlearned diffusion models(DMs).") # # gr.Markdown("####For more details, please visit the [project](https://www.optml-group.com/posts/mu_attack), # # check the [code](https://github.com/OPTML-Group/Diffusion-MU-Attack), and read the [paper](https://arxiv.org/abs/2310.11868).") # gr.Markdown("### Please notice that the process may take a long time, but the results will be saved. You can try it later if it waits for too long.") with gr.Row() as udiff: with gr.Row(): drop = gr.Dropdown(["Object-Church", "Object-Parachute", "Object-Garbage","Style-Van Gogh", "Concept-Nudity", "Concept-Violence", "Illegal Activity", "None"], label="Unlearning undesirable") with gr.Column(): # gr.Markdown("Please upload your model id.") drop_model = gr.Dropdown(["ESD", "FMN", "AC","UCE", "SLD"], label="Unlearned DM") # diffusion_model_T = gr.Textbox(label='diffusion_model_id') # concept = gr.Textbox(label='concept') # attacker = gr.Textbox(label='attacker') # start_button = gr.Button("Attack!") # with gr.Column(): # result = gr.Textbox(label="unsafe prompt") with gr.Column(): gr.Examples(examples=[ ["CompVis/stable-diffusion-v1-4", "nudity", "text_grad"] ], inputs=[diffusion_model_id, concept, attacker]) start_button.click(fn=excute_udiff, inputs=[diffusion_model_id, concept, attacker], outputs=result, api_name="udiff") # demo.queue(default_enabled=False, api_open=False, max_size=5).launch(debug=True, show_api=False) demo.queue().launch(server_name='0.0.0.0') # with gr.Blocks() as demo: # with gr.Row(): # prompt = gr.Textbox(label='Input Prompt') # with gr.Row(): # shown_columns_1 = gr.CheckboxGroup( # choices=["Church","Parachute","Tench", "Garbage Truck"], # label="Undersirable Objects", # elem_id="column-object", # interactive=True, # ) # with gr.Row(): # shown_columns_2 = gr.CheckboxGroup( # choices=["Van Gogh"], # label="Undersirable Styles", # elem_id="column-style", # interactive=True, # ) # with gr.Row(): # shown_columns_3 = gr.CheckboxGroup( # choices=["Violence","Illegal Activity","Nudity"], # label="Undersirable Concepts (Outputs that may be offensive in nature)", # elem_id="column-select", # interactive=True, # ) # with gr.Row(): # with gr.Column(scale=1, min_width=300): # img1 = gr.Image("images/cheetah.jpg",label="Unlearning") # with gr.Column(scale=1, min_width=300): # img2 = gr.Image("images/cheetah.jpg",label="Attacking") # with gr.Row(): # # gr.Markdown("Please upload your model id.") # diffusion_model_id = gr.Textbox(label='diffusion_model_id') # shown_columns_4 = gr.Slider( # 1, 100, value=40, # step=1, label="Attacking Steps", info="Choose between 1 and 100", # interactive=True,) # # concept = gr.Textbox(label='concept') # attacker = gr.Textbox(label='attacker') # start_button = gr.Button("Attack!") # demo.launch()