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import gradio as gr |
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import requests |
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import io |
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import random |
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import os |
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from PIL import Image |
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API_URL = os.getenv("HF_MODEL_API_URL") |
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API_TOKEN = os.getenv("HF_READ_TOKEN") |
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headers = {"Authorization": f"Bearer {API_TOKEN}"} |
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def query(prompt, is_negative=False, image_style="None style", steps=50, cfg_scale=7, seed=None): |
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if image_style == "None style": |
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payload = { |
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"inputs": prompt + ", 8k", |
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"is_negative": is_negative, |
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"steps": steps, |
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"cfg_scale": cfg_scale, |
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"seed": seed if seed is not None else random.randint(-1, 2147483647) |
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} |
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elif image_style == "Cinematic": |
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payload = { |
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"inputs": prompt+", realistic, detailed, textured, skin, hair, eyes, by Alex Huguet, Mike Hill, Ian Spriggs, JaeCheol Park, Marek Denko", |
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"is_negative": is_negative+", abstract, cartoon, stylized", |
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"steps": steps, |
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"cfg_scale": cfg_scale, |
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"seed": seed if seed is not None else random.randint(-1, 2147483647) |
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} |
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elif image_style == "Digital Art": |
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payload = { |
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"inputs": prompt + ", faded , vintage , nostalgic , by Jose Villa , Elizabeth Messina , Ryan Brenizer , Jonas Peterson , Jasmine Star", |
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"is_negative": is_negative + ", sharp , modern , bright", |
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"steps": steps, |
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"cfg_scale": cfg_scale, |
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"seed": seed if seed is not None else random.randint(-1, 2147483647) |
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} |
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elif image_style == "Portrait": |
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payload = { |
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"inputs": prompt + ", soft light, sharp, exposure blend, medium shot, bokeh, (hdr:1.4), high contrast, (cinematic, teal and orange:0.85), (muted colors, dim colors, soothing tones:1.3), low saturation, (hyperdetailed:1.2), (noir:0.4), (natural skin texture, hyperrealism, soft light, sharp:1.2)", |
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"is_negative": is_negative, |
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"steps": steps, |
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"cfg_scale": cfg_scale, |
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"seed": seed if seed is not None else random.randint(-1, 2147483647) |
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} |
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image_bytes = requests.post(API_URL, headers=headers, json=payload).content |
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image = Image.open(io.BytesIO(image_bytes)) |
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return 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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.gradio-container { |
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max-width: 730px !important; |
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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 {padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; max-width: 13rem; margin-left: auto;} |
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div#share-btn-container > div {flex-direction: row;background: black;align-items: center} |
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#share-btn-container:hover {background-color: #060606} |
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#share-btn {all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; margin-left: 0.5rem !important; padding-top: 0.5rem !important; padding-bottom: 0.5rem !important;right:0;} |
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#share-btn * {all: unset} |
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#share-btn-container div:nth-child(-n+2){width: auto !important;min-height: 0px !important;} |
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#share-btn-container .wrap {display: none !important} |
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#share-btn-container.hidden {display: none!important} |
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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-container .form{ |
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border-top-right-radius: 0; |
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border-bottom-right-radius: 0; |
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} |
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#gen-button{ |
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border-top-left-radius:0; |
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border-bottom-left-radius: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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.tabitem{border: 0 !important} |
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""" |
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with gr.Blocks(css=css) as sdxl: |
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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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🎨 New Super-Fast SDXL |
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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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SDXL is a high quality text-to-image model from Stability AI. This demo is running on <a style="text-decoration: underline;" href="https://huggingface.co/docs/api-inference/quicktour">HuggingFace Inference API ⚡</a>, to achieve efficient and cost-effective inference of 1024×1024 images. <a href="https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0" target="_blank">What model?</a> |
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</p> |
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</div> |
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""" |
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) |
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with gr.Row(): |
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with gr.Column(scale=1): |
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text_prompt = gr.Textbox(label="Prompt", placeholder="a cute cat", lines=1, elem_id="prompt-text-input") |
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negative_prompt = gr.Textbox(label="Negative Prompt", value="text, blurry, fuzziness", lines=1, elem_id="negative-prompt-text-input") |
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image_style = gr.Dropdown(label="Style", choices=["None style", "Cinematic", "Digital Art", "Portrait"], value="None style", allow_custom_value=False) |
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text_button = gr.Button("Generate", variant='primary', elem_id="gen-button") |
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with gr.Row(): |
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with gr.Column(scale=1): |
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image_output = gr.Image(type="pil", label="Output Image", elem_id="gallery") |
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text_button.click(query, inputs=[text_prompt, negative_prompt, image_style], outputs=image_output) |
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sdxl.launch(show_api=False) |
