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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 | |
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=css) as demo: | |
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.Column(): | |
# gr.Markdown("Please upload your model id.") | |
diffusion_model_id = 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() |