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| import gradio as gr | |
| import os | |
| import sys | |
| from pathlib import Path | |
| import time | |
| import accelerate | |
| models = [ | |
| "", | |
| "runwayml/stable-diffusion-v1-5", | |
| "CompVis/stable-diffusion-v1-4", | |
| "claudfuen/photorealistic-fuen-v1", | |
| "andite/anything-v4.0", | |
| "naclbit/trinart_stable_diffusion_v2", | |
| "nitrosocke/Arcane-Diffusion", | |
| "nitrosocke/archer-diffusion", | |
| "nitrosocke/elden-ring-diffusion", | |
| "nitrosocke/redshift-diffusion", | |
| "nitrosocke/spider-verse-diffusion", | |
| "nitrosocke/mo-di-diffusion", | |
| "nitrosocke/classic-anim-diffusion", | |
| "dreamlike-art/dreamlike-photoreal-1.0", | |
| "dreamlike-art/dreamlike-photoreal-2.0", | |
| "wavymulder/wavyfusion", | |
| "wavymulder/Analog-Diffusion", | |
| "prompthero/midjourney-v4-diffusion", | |
| "prompthero/openjourney", | |
| "dallinmackay/Van-Gogh-diffusion", | |
| "hakurei/waifu-diffusion", | |
| "DGSpitzer/Cyberpunk-Anime-Diffusion", | |
| "Fictiverse/Stable_Diffusion_BalloonArt_Model", | |
| "dallinmackay/Tron-Legacy-diffusion", | |
| "AstraliteHeart/pony-diffusion", | |
| "nousr/robo-diffusion", | |
| "Linaqruf/anything-v3", | |
| "Omnibus/maximum_diffusion_fast", | |
| "", | |
| ] | |
| model_1=models[1] | |
| model_2=models[2] | |
| model_3=models[3] | |
| model_4=models[4] | |
| model_5=models[5] | |
| model_6=models[6] | |
| model_7=models[9] | |
| model_8=models[13] | |
| model_9=models[14] | |
| model_10=models[15] | |
| model_11=models[16] | |
| model_12=models[17] | |
| text_gen=gr.Interface.load("spaces/Omnibus/MagicPrompt-Stable-Diffusion_link",live=True, preprocess=True) | |
| proc1=gr.Interface.load(f"models/{model_1}",live=False,preprocess=True, postprocess=False) | |
| proc2=gr.Interface.load(f"models/{model_2}",live=False,preprocess=True, postprocess=False) | |
| proc3=gr.Interface.load(f"models/{model_3}",live=False,preprocess=True, postprocess=False) | |
| proc4=gr.Interface.load(f"models/{model_4}",live=False,preprocess=True, postprocess=False) | |
| proc5=gr.Interface.load(f"models/{model_5}",live=False,preprocess=True, postprocess=False) | |
| proc6=gr.Interface.load(f"models/{model_6}",live=False,preprocess=True, postprocess=False) | |
| proc7=gr.Interface.load(f"models/{model_7}",live=False,preprocess=True, postprocess=False) | |
| proc8=gr.Interface.load(f"models/{model_8}",live=False,preprocess=True, postprocess=False) | |
| proc9=gr.Interface.load(f"models/{model_9}",live=False,preprocess=True, postprocess=False) | |
| proc10=gr.Interface.load(f"models/{model_10}",live=False,preprocess=True, postprocess=False) | |
| proc11=gr.Interface.load(f"models/{model_11}",live=False,preprocess=True, postprocess=False) | |
| proc12=gr.Interface.load(f"models/{model_12}",live=False,preprocess=True, postprocess=False) | |
| ''' | |
| proc1=gr.Interface.load("models/nitrosocke/Arcane-Diffusion", live=False, preprocess=True, postprocess=False) | |
| proc2=gr.Interface.load("models/naclbit/trinart_stable_diffusion_v2", live=False, preprocess=True, postprocess=False) | |
| proc3=gr.Interface.load("models/nitrosocke/redshift-diffusion", live=False, preprocess=True, postprocess=False) | |
| proc4=gr.Interface.load("models/runwayml/stable-diffusion-v1-5", live=False, preprocess=True, postprocess=False) | |
| proc5=gr.Interface.load("models/claudfuen/photorealistic-fuen-v1", live=False, preprocess=True, postprocess=False) | |
| proc6=gr.Interface.load("models/CompVis/stable-diffusion-v1-4", live=False, preprocess=True, postprocess=False) | |
| proc7=gr.Interface.load("models/Linaqruf/anything-v3.0", live=False, preprocess=True, postprocess=False) | |
| proc8=gr.Interface.load("models/andite/anything-v4.0", live=False, preprocess=True, postprocess=False) | |
| proc9=gr.Interface.load("models/dreamlike-art/dreamlike-photoreal-1.0", live=False, preprocess=True, postprocess=False) | |
| proc10=gr.Interface.load("models/prompthero/openjourney", live=False, preprocess=True, postprocess=False) | |
| proc11=gr.Interface.load("models/prompthero/midjourney-v4-diffusion", live=False, preprocess=True, postprocess=False) | |
| proc12=gr.Interface.load("models/wavymulder/Analog-Diffusion", live=False, preprocess=True, postprocess=False) | |
| ''' | |
| def get_prompts(prompt_text): | |
| return text_gen(prompt_text) | |
| def send_it1(inputs,proc1=proc1): | |
| output1=proc1(inputs) | |
| return(output1) | |
| def send_it2(inputs,proc2=proc2): | |
| output2=proc2(inputs) | |
| return(output2) | |
| def send_it3(inputs,proc3=proc3): | |
| output3=proc3(inputs) | |
| return(output3) | |
| def send_it4(inputs,proc4=proc4): | |
| output4=proc4(inputs) | |
| return(output4) | |
| def send_it5(inputs,proc5=proc5): | |
| output5=proc5(inputs) | |
| return(output5) | |
| def send_it6(inputs,proc6=proc6): | |
| output6=proc6(inputs) | |
| return(output6) | |
| def send_it7(inputs,proc7=proc7): | |
| output7=proc7(inputs) | |
| return(output7) | |
| def send_it8(inputs,proc8=proc8): | |
| output8=proc8(inputs) | |
| return(output8) | |
| def send_it9(inputs,proc9=proc9): | |
| output9=proc9(inputs) | |
| return(output9) | |
| def send_it10(inputs,proc10=proc10): | |
| output10=proc10(inputs) | |
| return(output10) | |
| def send_it11(inputs,proc11=proc11): | |
| output11=proc11(inputs) | |
| return(output11) | |
| def send_it12(inputs,proc12=proc12): | |
| output12=proc12(inputs) | |
| return(output12) | |
| def main(): | |
| with gr.Blocks(batch=False) as myface: | |
| with gr.Row(): | |
| with gr.Tab("Title"): | |
| gr.HTML("""<title>Maximum Diffusion</title><div style="text-align: center; max-width: 1500px; margin: 0 auto;"> | |
| <div style="display: inline-flex;align-items: center;gap: 0.8rem;font-size: 1.75rem;margin-bottom: 10px;line-height: 1em;"> | |
| <h1 style="font-weight: 900;font-size:30; margin-top: 9px;">Maximum Diffusion</h1></div> | |
| <br><br><p style="margin-bottom: 1px;font-size: 15;font-weight: 100;line-height: 1.5em;"> | |
| Text to Image Model Comparison Space - CPU</p> | |
| <br><p style="margin-bottom: 0px;font-size: 15;font-weight: 100;line-height: 1.5em;"> | |
| This space becomes quickly encumbered when even 1 model of 12 fails to load, or error out</p> | |
| <p style="margin-bottom: 0px;font-size: 15;font-weight: 100;line-height: 1.5em;"> | |
| Any tips on how to "time-out" Gradio.Interface models are welcome in the "Community" button above<br> | |
| <br></div>""") | |
| with gr.Tab("Description"): | |
| gr.HTML("""<div style="text-align:center;"> | |
| <h4>Enter your Prompt into the "Short Prompt" box and click "Magic Prompt" to load a prettified version of your prompt<br> | |
| When you are satisfied with the prompt that is in the "Text to Image" box, click "Launch" to load the Models.<br><br> | |
| Images load faster with a simpler prompt.<br> | |
| Most images should load within 2 minutes.<br> | |
| Some models become stuck on certain prompts, and refreshing the page seems to fix it.<br><br> | |
| Not responsible for content, use at your own risk. | |
| </h4></div>""") | |
| with gr.Tab("DIY"): | |
| gr.HTML("""<div style="text-align:Left;"> | |
| <h4>Copy/Paste this code in your app.py file<br><br> | |
| import gradio as gr<br> | |
| max_d=gr.Interface.load("spaces/Omnibus/maximum_diffusion")<br> | |
| max_d.launch()<br> | |
| </h4></div>""") | |
| with gr.Tab("Credits"): | |
| with gr.Row(): | |
| gr.Column() | |
| with gr.Column(style="text-align:left;"): | |
| gr.HTML(""" | |
| <div style="vertical-align:center"> | |
| <br> | |
| <p>I learned everything I know from: | |
| <p><a href="https://huggingface.co/spaces/anzorq/finetuned_diffusion">Finetuned Diffusion</a></p> | |
| <p><a href="https://huggingface.co/spaces/Gustavosta/MagicPrompt-Stable-Diffusion">Magic Prompt Stable Diffusion</a></p> | |
| <p><a href="https://huggingface.co/spaces/huggingface-projects/magic-diffusion">Magic Diffusion</a></p> | |
| <p>Models by <a href="https://huggingface.co/Gustavosta">@Gustavosta</a>, <a href="https://twitter.com/haruu1367">@haruu1367</a>, <a href="https://twitter.com/DGSpitzer">@Helixngc7293</a>, <a href="https://twitter.com/dal_mack">@dal_mack</a>, <a href="https://twitter.com/prompthero">@prompthero</a> and others.</p> | |
| </div> | |
| """) | |
| gr.Column() | |
| with gr.Tab("Tools"): | |
| with gr.Tab("View"): | |
| with gr.Row(): | |
| with gr.Column(style="width=50%, height=70%"): | |
| gr.Pil(label="Crop") | |
| with gr.Column(style="width=50%, height=70%"): | |
| gr.Pil(label="Crop") | |
| with gr.Tab("Draw"): | |
| with gr.Row(): | |
| with gr.Column(style="width=50%, height=70%"): | |
| gr.Pil(label="Crop") | |
| with gr.Column(style="width=50%, height=70%"): | |
| gr.Pil(label="Draw") | |
| gr.ImagePaint(label="Draw") | |
| with gr.Tab("Text"): | |
| with gr.Row(): | |
| with gr.Column(scale=50): | |
| gr.Textbox(label="", lines=8, interactive=True) | |
| with gr.Column(scale=50): | |
| gr.Textbox(label="", lines=8, interactive=True) | |
| with gr.Tab("Color Picker"): | |
| with gr.Row(): | |
| with gr.Column(scale=50): | |
| gr.ColorPicker(label="Color", interactive=True) | |
| with gr.Column(scale=50): | |
| gr.ImagePaint(label="Draw", interactive=True) | |
| with gr.Row(): | |
| input_text=gr.Textbox(label="Short Prompt") | |
| see_prompts=gr.Button("Magic Prompt") | |
| with gr.Row(): | |
| prompt=gr.Textbox(label="Text to Image") | |
| run=gr.Button("Launch") | |
| with gr.Row(): | |
| output1=gr.Image(label=(f"{model_1}")) | |
| output2=gr.Image(label=(f"{model_2}")) | |
| output3=gr.Image(label=(f"{model_3}")) | |
| output4=gr.Image(label=(f"{model_4}")) | |
| with gr.Row(): | |
| output5=gr.Image(label=(f"{model_5}")) | |
| output6=gr.Image(label=(f"{model_6}")) | |
| output7=gr.Image(label=(f"{model_7}")) | |
| output8=gr.Image(label=(f"{model_8}")) | |
| with gr.Row(): | |
| output9=gr.Image(label=(f"{model_9}")) | |
| output10=gr.Image(label=(f"{model_10}")) | |
| output11=gr.Image(label=(f"{model_11}")) | |
| output12=gr.Image(label=(f"{model_12}")) | |
| see_prompts.click(get_prompts, inputs=[input_text], outputs=[prompt]) | |
| run.click(send_it1, inputs=[prompt], outputs=[output1]) | |
| run.click(send_it2, inputs=[prompt], outputs=[output2]) | |
| run.click(send_it3, inputs=[prompt], outputs=[output3]) | |
| run.click(send_it4, inputs=[prompt], outputs=[output4]) | |
| run.click(send_it5, inputs=[prompt], outputs=[output5]) | |
| run.click(send_it6, inputs=[prompt], outputs=[output6]) | |
| run.click(send_it7, inputs=[prompt], outputs=[output7]) | |
| run.click(send_it8, inputs=[prompt], outputs=[output8]) | |
| run.click(send_it9, inputs=[prompt], outputs=[output9]) | |
| run.click(send_it10, inputs=[prompt], outputs=[output10]) | |
| run.click(send_it11, inputs=[prompt], outputs=[output11]) | |
| run.click(send_it12, inputs=[prompt], outputs=[output12]) | |
| myface.queue(concurrency_count=600,status_update_rate=1) | |
| myface.launch(enable_queue=True,inline=True,max_threads=600) | |
| if __name__ == "__main__": | |
| main() | |