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import gradio as gr |
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from datasets import load_dataset |
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import re |
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import os |
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import requests |
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from share_btn import community_icon_html, loading_icon_html, share_js |
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word_list = [] |
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def infer(prompt, negative="low_quality", scale=7): |
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for filter in word_list: |
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if re.search(rf"\b{filter}\b", prompt): |
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raise gr.Error("Unsafe content found. Please try again with different prompts.") |
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images = [] |
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url = os.getenv('JAX_BACKEND_URL') |
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payload = {'prompt': prompt, 'negative_prompt': negative, 'guidance_scale': scale} |
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images_request = requests.post(url, json = payload) |
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for image in images_request.json()["images"]: |
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image_b64 = (f"data:image/jpeg;base64,{image}") |
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images.append(image_b64) |
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return images, gr.update(visible=True) |
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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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""" |
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block = gr.Blocks(css=css) |
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examples = [ |
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[ |
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"A serious capybara at work, wearing a suit", |
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None, |
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None |
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], |
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[ |
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'A Squirtle fine dining with a view to the London Eye', |
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None, |
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None |
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], |
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[ |
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'A tamale food cart in front of a Japanese Castle', |
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None, |
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None |
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], |
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[ |
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'a graffiti of a robot serving meals to people', |
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None, |
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None |
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], |
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[ |
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'a beautiful cabin in Attersee, Austria, 3d animation style', |
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None, |
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None |
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], |
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] |
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with block: |
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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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SDXL is a high quality text-to-image model from Stability AI. This demo on a <a style="text-decoration: underline;" href="https://cloud.google.com/blog/products/compute/announcing-cloud-tpu-v5e-and-a3-gpus-in-ga">Google Cloud TPU v5e</a>, to achieve efficient and cost-effective inference of 1024×1024 images. <a href="#">How does it work?</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(elem_id="prompt-container").style(mobile_collapse=False, equal_height=True): |
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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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) |
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btn = gr.Button("Generate", scale=0, elem_id="gen-button") |
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gallery = gr.Gallery( |
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label="Generated images", show_label=False, elem_id="gallery", grid=[2] |
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) |
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with gr.Group(elem_id="share-btn-container", visible=False) as community_group: |
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community_icon = gr.HTML(community_icon_html) |
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loading_icon = gr.HTML(loading_icon_html) |
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share_button = gr.Button("Share to community", elem_id="share-btn") |
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with gr.Accordion("Advanced settings", open=False): |
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negative = gr.Textbox( |
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label="Enter your negative prompt", |
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show_label=False, |
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max_lines=1, |
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placeholder="Enter a negative prompt", |
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elem_id="negative-prompt-text-input", |
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) |
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guidance_scale = gr.Slider( |
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label="Guidance Scale", minimum=0, maximum=50, value=9, step=0.1 |
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) |
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ex = gr.Examples(examples=examples, fn=infer, inputs=[text, negative, guidance_scale], outputs=[gallery, community_group], cache_examples=True, postprocess=False) |
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negative.submit(infer, inputs=[text, negative, guidance_scale], outputs=[gallery, community_group], postprocess=False) |
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text.submit(infer, inputs=[text, negative, guidance_scale], outputs=[gallery, community_group], postprocess=False) |
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btn.click(infer, inputs=[text, negative, guidance_scale], outputs=[gallery, community_group], postprocess=False) |
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share_button.click( |
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None, |
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[], |
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[], |
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_js=share_js, |
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) |
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gr.HTML( |
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""" |
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<div class="footer"> |
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<p>Model by <a href="https://huggingface.co/stabilityai" style="text-decoration: underline;" target="_blank">StabilityAI</a> - backend running JAX on TPUs due to generous support of <a href="https://sites.research.google/trc/about/" style="text-decoration: underline;" target="_blank">Google TRC program</a> - Gradio Demo by 🤗 Hugging Face |
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</p> |
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</div> |
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""" |
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) |
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with gr.Accordion(label="License", open=False): |
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gr.HTML( |
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"""<div class="acknowledgments"> |
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<p><h4>LICENSE</h4> |
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The model is licensed with a <a href="https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/LICENSE.md" style="text-decoration: underline;" target="_blank">Stability AI CreativeML Open RAIL++-M</a> license. The License allows users to take advantage of the model in a wide range of settings (including free use and redistribution) as long as they respect the specific use case restrictions outlined, which correspond to model applications the licensor deems ill-suited for the model or are likely to cause harm. For the full list of restrictions please <a href="https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/LICENSE.md" target="_blank" style="text-decoration: underline;" target="_blank">read the license</a></p> |
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<p><h4>Biases and content acknowledgment</h4> |
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Despite how impressive being able to turn text into image is, beware that this model may output content that reinforces or exacerbates societal biases, as well as realistic faces, pornography and violence. The model was trained on the <a href="https://laion.ai/blog/laion-5b/" style="text-decoration: underline;" target="_blank">LAION-5B dataset</a>, which scraped non-curated image-text-pairs from the internet (the exception being the removal of illegal content) and is meant for research purposes. You can read more in the <a href="https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0" style="text-decoration: underline;" target="_blank">model card</a></p> |
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</div> |
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""" |
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) |
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block.queue(concurrency_count=4, max_size=10).launch() |
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