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import gradio as gr |
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from PIL import Image |
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import io |
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import os |
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import warnings |
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import torch |
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import numpy as np |
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from diffusers import DiffusionPipeline |
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from huggingface_hub import login |
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import os |
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login(token=os.environ.get('HF_KEY')) |
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device = 'cpu' |
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seed = 10000 |
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torch.cuda.max_memory_allocated(device='cpu') |
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pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", use_safetensors=True) |
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pipe = pipe.to(device) |
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generator = torch.Generator(device=device).manual_seed(seed) |
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def infer(prompt): |
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int_image = pipe(prompt,num_images_per_prompt=1, generator=generator).images |
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torch.cuda.empty_cache() |
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return int_image |
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css = """ |
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.gradio-container { |
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font-family: 'IBM Plex Sans', sans-serif; |
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} |
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.gr-button { |
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color: white; |
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border-color: black; |
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background: black; |
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} |
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input[type='range'] { |
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accent-color: black; |
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} |
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.dark input[type='range'] { |
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accent-color: #dfdfdf; |
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} |
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.container { |
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max-width: 730px; |
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margin: auto; |
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padding-top: 1.5rem; |
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} |
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#gallery { |
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min-height: 22rem; |
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margin-bottom: 15px; |
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margin-left: auto; |
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margin-right: auto; |
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border-bottom-right-radius: .5rem !important; |
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border-bottom-left-radius: .5rem !important; |
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} |
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#gallery>div>.h-full { |
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min-height: 20rem; |
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} |
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.details:hover { |
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text-decoration: underline; |
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} |
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.gr-button { |
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white-space: nowrap; |
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} |
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.gr-button:focus { |
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border-color: rgb(147 197 253 / var(--tw-border-opacity)); |
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outline: none; |
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box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000); |
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--tw-border-opacity: 1; |
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--tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color); |
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--tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color); |
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--tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity)); |
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--tw-ring-opacity: .5; |
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} |
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#advanced-btn { |
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font-size: .7rem !important; |
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line-height: 19px; |
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margin-top: 12px; |
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margin-bottom: 12px; |
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padding: 2px 8px; |
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border-radius: 14px !important; |
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} |
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#advanced-options { |
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display: none; |
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margin-bottom: 20px; |
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} |
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.footer { |
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margin-bottom: 45px; |
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margin-top: 35px; |
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text-align: center; |
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border-bottom: 1px solid #e5e5e5; |
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} |
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.footer>p { |
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font-size: .8rem; |
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display: inline-block; |
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padding: 0 10px; |
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transform: translateY(10px); |
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background: white; |
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} |
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.dark .footer { |
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border-color: #303030; |
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} |
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.dark .footer>p { |
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background: #0b0f19; |
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} |
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.acknowledgments h4{ |
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margin: 1.25em 0 .25em 0; |
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font-weight: bold; |
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font-size: 115%; |
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} |
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.animate-spin { |
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animation: spin 1s linear infinite; |
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} |
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@keyframes spin { |
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from { |
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transform: rotate(0deg); |
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} |
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to { |
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transform: rotate(360deg); |
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} |
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} |
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#share-btn-container { |
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display: flex; padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; width: 13rem; |
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margin-top: 10px; |
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margin-left: auto; |
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} |
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#share-btn { |
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all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; margin-left: 0.5rem !important; padding-top: 0.25rem !important; padding-bottom: 0.25rem !important;right:0; |
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} |
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#share-btn * { |
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all: unset; |
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} |
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#share-btn-container div:nth-child(-n+2){ |
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width: auto !important; |
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min-height: 0px !important; |
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} |
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#share-btn-container .wrap { |
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display: none !important; |
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} |
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.gr-form{ |
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flex: 1 1 50%; border-top-right-radius: 0; border-bottom-right-radius: 0; |
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} |
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#prompt-container{ |
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gap: 0; |
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} |
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#prompt-text-input, #negative-prompt-text-input{padding: .45rem 0.625rem} |
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#component-16{border-top-width: 1px!important;margin-top: 1em} |
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.image_duplication{position: absolute; width: 100px; left: 50px} |
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""" |
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with gr.Blocks(css = css) as demo: |
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gr.HTML( |
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""" |
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<div style="text-align: center; margin: 0 auto;"> |
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<div |
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style=" |
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display: inline-flex; |
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align-items: center; |
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gap: 0.8rem; |
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font-size: 1.75rem; |
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" |
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> |
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<svg |
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width="0.65em" |
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height="0.65em" |
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viewBox="0 0 115 115" |
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fill="none" |
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xmlns="http://www.w3.org/2000/svg" |
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> |
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<rect width="23" height="23" fill="white"></rect> |
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<rect y="69" width="23" height="23" fill="white"></rect> |
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<rect x="23" width="23" height="23" fill="#AEAEAE"></rect> |
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<rect x="23" y="69" width="23" height="23" fill="#AEAEAE"></rect> |
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<rect x="46" width="23" height="23" fill="white"></rect> |
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<rect x="46" y="69" width="23" height="23" fill="white"></rect> |
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<rect x="69" width="23" height="23" fill="black"></rect> |
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<rect x="69" y="69" width="23" height="23" fill="black"></rect> |
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<rect x="92" width="23" height="23" fill="#D9D9D9"></rect> |
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<rect x="92" y="69" width="23" height="23" fill="#AEAEAE"></rect> |
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<rect x="115" y="46" width="23" height="23" fill="white"></rect> |
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<rect x="115" y="115" width="23" height="23" fill="white"></rect> |
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<rect x="115" y="69" width="23" height="23" fill="#D9D9D9"></rect> |
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<rect x="92" y="46" width="23" height="23" fill="#AEAEAE"></rect> |
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<rect x="92" y="115" width="23" height="23" fill="#AEAEAE"></rect> |
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<rect x="92" y="69" width="23" height="23" fill="white"></rect> |
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<rect x="69" y="46" width="23" height="23" fill="white"></rect> |
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<rect x="69" y="115" width="23" height="23" fill="white"></rect> |
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<rect x="69" y="69" width="23" height="23" fill="#D9D9D9"></rect> |
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<rect x="46" y="46" width="23" height="23" fill="black"></rect> |
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<rect x="46" y="115" width="23" height="23" fill="black"></rect> |
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<rect x="46" y="69" width="23" height="23" fill="black"></rect> |
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<rect x="23" y="46" width="23" height="23" fill="#D9D9D9"></rect> |
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<rect x="23" y="115" width="23" height="23" fill="#AEAEAE"></rect> |
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<rect x="23" y="69" width="23" height="23" fill="black"></rect> |
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</svg> |
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<h1 style="font-weight: 900; margin-bottom: 7px;margin-top:5px"> |
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Stable Diffusion XL Demo |
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</h1> |
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</div> |
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<p style="margin-bottom: 10px; font-size: 94%; line-height: 23px;"> |
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This is an unoffical demo for Stable Diffusion XL, which is the latest stable diffusion model released by Stability AI. The main features include Next-level photorealism capabilities, image composition and face generation, use of shorter prompts to create descriptive imagery, greater capability to produce legible text and rich visuals and jaw-dropping aesthetics. Please refer to |
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<a |
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href="https://stability.ai/stable-diffusion" |
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style="text-decoration: underline;" |
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target="_blank" |
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>the official website</a |
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>.</a> for further information |
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</p> |
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</div> |
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""" |
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) |
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gr.HTML("<p>You can duplicate this Space to run it privately without a queue for shorter queue times : <a style='display:inline-block' href='https://huggingface.co/spaces/RamAnanth1/stable-diffusion-xl?duplicate=true'><img src='https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14' alt='Duplicate Space'></a> </p>") |
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with gr.Row(elem_id="prompt-container").style(mobile_collapse=False, equal_height=True): |
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with gr.Column(): |
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text = gr.Textbox( |
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label="Enter your prompt", |
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show_label=False, |
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max_lines=1, |
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placeholder="Enter your prompt", |
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elem_id="prompt-text-input", |
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).style( |
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border=(True, False, True, True), |
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rounded=(True, False, False, True), |
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container=False, |
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) |
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btn = gr.Button("Generate image").style( |
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margin=False, |
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rounded=(False, True, True, False), |
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full_width=False, |
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) |
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gallery = gr.Gallery( |
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label="Generated images", show_label=False, elem_id="gallery" |
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).style(grid=[2], height="auto") |
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btn.click(infer, inputs=[text], outputs=[gallery]) |
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examples = [ |
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["Vintage hot rod with custom flame paint job"], |
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["Ancient, mysterious temple in a mountain range, surrounded by misty clouds and tall peaks"], |
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["Glimpses of a herd of wild elephants crossing a savanna"], |
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["Beautiful waterfall in a lush jungle, with sunlight shining through the trees,"] |
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] |
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ex = gr.Examples(examples=examples,inputs=[text], cache_examples=False) |
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demo.launch() |
