SLDFKJSDLFKJ
Browse files- app.py +329 -6
- requirements.txt +1 -0
app.py
CHANGED
@@ -1,11 +1,334 @@
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import gradio as gr
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import
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return cmd_out.stdout.decode("utf-8")
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iface.launch()
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# import gradio as gr
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# import subprocess
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# def greet(name):
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# cmd_out = subprocess.run(["pip", "list"], stdout=subprocess.PIPE)
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# return cmd_out.stdout.decode("utf-8")
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# iface = gr.Interface(fn=greet, inputs="text", outputs="text")
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# iface.launch()
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import gradio as gr
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from datasets import load_dataset
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from PIL import Image
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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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model_id = "runwayml/stable-diffusion-v1-5"
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device = "cuda"
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word_list_dataset = load_dataset(
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"stabilityai/word-list", data_files="list.txt", use_auth_token=True
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)
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word_list = word_list_dataset["train"]["text"]
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is_gpu_busy = False
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def infer(prompt):
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global is_gpu_busy
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samples = 4
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steps = 50
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scale = 7.5
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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(
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"Unsafe content found. Please try again with different prompts."
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)
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images = []
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url = os.getenv("JAX_BACKEND_URL")
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payload = {"prompt": prompt}
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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
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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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#container-advanced-btns{
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display: flex;
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flex-wrap: wrap;
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justify-content: space-between;
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align-items: center;
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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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}
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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;
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}
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#share-btn * {
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all: unset;
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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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#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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"""
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block = gr.Blocks(css=css)
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examples = [
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[
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"The spirit of a tamagotchi wandering in the city of Paris",
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# 4,
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# 45,
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# 7.5,
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# 1024,
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],
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[
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"A delicious ceviche cheesecake slice",
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# 4,
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# 45,
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# 7,
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# 1024,
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],
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[
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"A pao de queijo foodcart in front of a japanese castle",
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# 4,
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# 45,
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# 7,
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# 1024,
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],
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[
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"alone in the amusement park by Edward Hopper",
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# 4,
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# 45,
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# 7,
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# 1024,
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],
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[
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"A large cabin on top of a sunny mountain in the style of Dreamworks, artstation",
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# 4,
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# 45,
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# 7,
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# 1024,
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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; max-width: 650px; margin: 0 auto; padding-top: 7px;">
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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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<h1 style="font-weight: 900; margin-bottom: 7px;">
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Stable Diffusion v1-5 Demo
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</h1>
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</div>
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<p style="margin-bottom: 10px; font-size: 94%">
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Stable Diffusion v1-5 is the latest version of the state of the art text-to-image model.<br>For faster generation you can try
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<a href="https://app.runwayml.com/ai-tools/text-to-image"
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style="text-decoration: underline;" target="_blank">text to image tool at Runway.</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.Group():
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with gr.Box():
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with gr.Row(elem_id="prompt-container").style(
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mobile_collapse=False, equal_height=True
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):
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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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with gr.Group(elem_id="container-advanced-btns"):
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advanced_button = gr.Button("Advanced options", elem_id="advanced-btn")
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with gr.Group(elem_id="share-btn-container"):
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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.Row(elem_id="advanced-options"):
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gr.Markdown("Advanced settings are temporarily unavailable")
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samples = gr.Slider(label="Images", minimum=1, maximum=4, value=4, step=1)
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steps = gr.Slider(label="Steps", minimum=1, maximum=50, value=45, step=1)
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scale = gr.Slider(
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label="Guidance Scale", minimum=0, maximum=50, value=7.5, step=0.1
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)
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seed = gr.Slider(
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label="Seed",
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minimum=0,
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maximum=2147483647,
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step=1,
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randomize=True,
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)
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ex = gr.Examples(
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examples=examples,
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fn=infer,
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inputs=text,
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outputs=[gallery],
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cache_examples=True,
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postprocess=False,
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)
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ex.dataset.headers = [""]
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text.submit(infer, inputs=text, outputs=[gallery], postprocess=False)
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btn.click(infer, inputs=text, outputs=[gallery], postprocess=False)
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advanced_button.click(
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None,
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[],
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text,
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_js="""
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() => {
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const options = document.querySelector("body > gradio-app").querySelector("#advanced-options");
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options.style.display = ["none", ""].includes(options.style.display) ? "flex" : "none";
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}""",
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)
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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/CompVis" style="text-decoration: underline;" target="_blank">CompVis</a> and <a href="https://runwayml.com/" style="text-decoration: underline;" target="_blank">Runway</a> supported by <a href="https://huggingface.co/stabilityai" style="text-decoration: underline;" target="_blank">Stability AI</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
|
323 |
+
</p>
|
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+
</div>
|
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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/spaces/CompVis/stable-diffusion-license" style="text-decoration: underline;" target="_blank">CreativeML Open RAIL-M</a> license. The authors claim no rights on the outputs you generate, you are free to use them and are accountable for their use which must not go against the provisions set in this license. The license forbids you from sharing any content that violates any laws, produce any harm to a person, disseminate any personal information that would be meant for harm, spread misinformation and target vulnerable groups. For the full list of restrictions please <a href="https://huggingface.co/spaces/CompVis/stable-diffusion-license" 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 to the fact 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/runwayml/stable-diffusion-v1-5" 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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|
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+
block.queue(concurrency_count=40, max_size=20).launch(max_threads=150)
|
|
requirements.txt
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
python-dotenv
|