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import random
import gradio as gr
from datasets import load_dataset
from PIL import Image
from set import ExpiringMap
# from model import get_sd_small, get_sd_tiny, get_sd_every
from trans_google import google_translator
import replicate
from i18n import i18nTranslator
word_list_dataset = load_dataset("Gustavosta/Stable-Diffusion-Prompts")
word_list = word_list_dataset["train"]['Prompt']
#
# from diffusers import EulerDiscreteScheduler, DDIMScheduler, KDPM2AncestralDiscreteScheduler, \
# UniPCMultistepScheduler, DPMSolverSinglestepScheduler, DEISMultistepScheduler, PNDMScheduler, \
# DPMSolverMultistepScheduler, HeunDiscreteScheduler, EulerAncestralDiscreteScheduler, DDPMScheduler, \
# LMSDiscreteScheduler, KDPM2DiscreteScheduler
# import torch
# import base64
# from io import BytesIO
is_gpu_busy = False
# translator = i18nTranslator()
# translator.init(path='locales')
samplers = [
"EulerDiscrete",
"EulerAncestralDiscrete",
"UniPCMultistep",
"DPMSolverSinglestep",
"DPMSolverMultistep",
"KDPM2Discrete",
"KDPM2AncestralDiscrete",
"DEISMultistep",
"HeunDiscrete",
"PNDM",
"DDPM",
"DDIM",
"LMSDiscrete",
]
re_sampler = [
"DDIM",
"K_EULER",
"DPMSolverMultistep",
"K_EULER_ANCESTRAL",
"PNDM",
"KLMS"
]
rand = random.Random()
translator = google_translator()
# tiny_pipe = get_sd_tiny()
# small_pipe = get_sd_small()
# every_pipe = get_sd_every()
# def get_pipe(width: int, height: int):
# if width == 512 and height == 512:
# return tiny_pipe
# elif width == 256 and height == 256:
# return small_pipe
# else:
# return every_pipe
time_client_map = ExpiringMap()
count_client_map = ExpiringMap()
def infer(prompt: str, negative: str, width: int, height: int, sampler: str,
steps: int, seed: int, scale, request: gr.Request):
client_ip = request.client.host
if client_ip != '127.0.0.1' and client_ip != 'localhost' and client_ip != '0.0.0.0':
if time_client_map.get(client_ip):
return None, "Too many requests, please try again later."
else:
time_client_map.put(client_ip, 1, 10) # 添加一个过期时间为 10 秒的项
count = count_client_map.get(client_ip)
if count is None:
count = 0
count += 1
if count > 5:
return None, "Too many requests, please try again later."
else:
count_client_map.put(client_ip, count, 24 * 60 * 60) # 添加一个过期时间为 24 小时的项
global is_gpu_busy
if seed == 0:
seed = rand.randint(0, 10000)
else:
seed = int(seed)
#
# pipeline = get_pipe(width, height)
#
images = []
# if torch.cuda.is_available():
# generator = torch.Generator(device="cuda").manual_seed(seed)
# else:
# generator = None
# if sampler == "EulerDiscrete":
# pipeline.scheduler = EulerDiscreteScheduler.from_config(pipeline.scheduler.config)
# elif sampler == "EulerAncestralDiscrete":
# pipeline.scheduler = EulerAncestralDiscreteScheduler.from_config(pipeline.scheduler.config)
# elif sampler == "KDPM2Discrete":
# pipeline.scheduler = KDPM2DiscreteScheduler.from_config(pipeline.scheduler.config)
# elif sampler == "KDPM2AncestralDiscrete":
# pipeline.scheduler = KDPM2AncestralDiscreteScheduler.from_config(pipeline.scheduler.config)
# elif sampler == "UniPCMultistep":
# pipeline.scheduler = UniPCMultistepScheduler.from_config(pipeline.scheduler.config)
# elif sampler == "DPMSolverSinglestep":
# pipeline.scheduler = DPMSolverSinglestepScheduler.from_config(pipeline.scheduler.config)
# elif sampler == "DPMSolverMultistep":
# pipeline.scheduler = DPMSolverMultistepScheduler.from_config(pipeline.scheduler.config)
# elif sampler == "HeunDiscrete":
# pipeline.scheduler = HeunDiscreteScheduler.from_config(pipeline.scheduler.config)
# elif sampler == "DEISMultistep":
# pipeline.scheduler = DEISMultistepScheduler.from_config(pipeline.scheduler.config)
# elif sampler == "PNDM":
# pipeline.scheduler = PNDMScheduler.from_config(pipeline.scheduler.config)
# elif sampler == "DDPM":
# pipeline.scheduler = DDPMScheduler.from_config(pipeline.scheduler.config)
# elif sampler == "DDIM":
# pipeline.scheduler = DDIMScheduler.from_config(pipeline.scheduler.config)
# elif sampler == "LMSDiscrete":
# pipeline.scheduler = LMSDiscreteScheduler.from_config(pipeline.scheduler.config)
try:
translate_prompt = translator.translate(prompt, lang_tgt='en')
translate_negative = translator.translate(negative, lang_tgt='en')
except Exception as ex:
print(ex)
translate_prompt = prompt
translate_negative = negative
output = replicate.run(
"stability-ai/stable-diffusion:db21e45d3f7023abc2a46ee38a23973f6dce16bb082a930b0c49861f96d1e5bf",
input={
"prompt": translate_prompt,
"negative_prompt": translate_negative,
"guidance_scale": scale,
"num_inference_steps": steps,
"seed": seed,
"scheduler": sampler,
}
)
# image = pipeline(prompt=translate_prompt,
# negative_prompt=translate_negative,
# guidance_scale=scale,
# num_inference_steps=steps,
# generator=generator,
# height=height,
# width=width).images[0]
# buffered = BytesIO()
# image.save(buffered, format="JPEG")
# img_str = base64.b64encode(buffered.getvalue())
# img_base64 = bytes("data:image/jpeg;base64,", encoding='utf-8') + img_str
images.append(output[0])
return images, ""
css = """
.gradio-container {
font-family: 'IBM Plex Sans', sans-serif;
}
.gr-button {
color: white;
border-color: black;
background: black;
}
input[type='range'] {
accent-color: black;
}
.dark input[type='range'] {
accent-color: #dfdfdf;
}
.container {
max-width: 1130px;
margin: auto;
padding-top: 1.5rem;
}
#prompt-column {
min-height: 500px
}
#gallery {
min-height: 22rem;
margin-bottom: 15px;
margin-left: auto;
margin-right: auto;
border-bottom-right-radius: .5rem !important;
border-bottom-left-radius: .5rem !important;
}
#gallery>div>.h-full {
min-height: 20rem;
}
.details:hover {
text-decoration: underline;
}
.gr-button {
white-space: nowrap;
}
.gr-button:focus {
border-color: rgb(147 197 253 / var(--tw-border-opacity));
outline: none;
box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000);
--tw-border-opacity: 1;
--tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color);
--tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color);
--tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity));
--tw-ring-opacity: .5;
}
#advanced-btn {
font-size: .7rem !important;
line-height: 19px;
margin-top: 12px;
margin-bottom: 12px;
padding: 2px 8px;
border-radius: 14px !important;
}
#advanced-options {
display: none;
margin-bottom: 20px;
}
.footer {
margin-bottom: 45px;
margin-top: 35px;
text-align: center;
border-bottom: 1px solid #e5e5e5;
}
.footer>p {
font-size: .8rem;
display: inline-block;
padding: 0 10px;
transform: translateY(10px);
background: white;
}
.dark .footer {
border-color: #303030;
}
.dark .footer>p {
background: #0b0f19;
}
.acknowledgments h4{
margin: 1.25em 0 .25em 0;
font-weight: bold;
font-size: 115%;
}
.animate-spin {
animation: spin 1s linear infinite;
}
@keyframes spin {
from {
transform: rotate(0deg);
}
to {
transform: rotate(360deg);
}
}
#share-btn-container {
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;
margin-top: 10px;
margin-left: auto;
}
#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: 0.25rem !important; padding-bottom: 0.25rem !important;right:0;
}
#share-btn * {
all: unset;
}
#share-btn-container div:nth-child(-n+2){
width: auto !important;
min-height: 0px !important;
}
#share-btn-container .wrap {
display: none !important;
}
.gr-form{
flex: 1 1 50%; border-top-right-radius: 0; border-bottom-right-radius: 0;
}
#prompt-container{
gap: 0;
}
#prompt-text-input, #negative-prompt-text-input{padding: .45rem 0.625rem}
#component-16{border-top-width: 1px!important;margin-top: 1em}
.image_duplication{position: absolute; width: 100px; left: 50px}
.generate-container {display: flex; justify-content: flex-end;}
#generate-btn {background: linear-gradient(to bottom right, #ffedd5, #fdba74)}
"""
block = gr.Blocks(css=css)
# text, negative, width, height, sampler, steps, seed, guidance_scale
# examples = [
# [
# 'A high tech solarpunk utopia in the Amazon rainforest',
# 'low quality',
# 512,
# 512,
# 'ddim',
# 30,
# 0,
# 9
# ],
# [
# 'A pikachu fine dining with a view to the Eiffel Tower',
# 'low quality',
# 512,
# 512,
# 'ddim',
# 30,
# 0,
# 9
# ],
# [
# 'A mecha robot in a favela in expressionist style',
# 'low quality, 3d, photorealistic',
# 512,
# 512,
# 'ddim',
# 30,
# 0,
# 9
# ],
# [
# 'an insect robot preparing a delicious meal',
# 'low quality, illustration',
# 512,
# 512,
# 'ddim',
# 30,
# 0,
# 9
# ],
# [
# "A small cabin on top of a snowy mountain in the style of Disney, artstation",
# 'low quality, ugly',
# 512,
# 512,
# 'ddim',
# 30,
# 0,
# 9
# ],
# ]
examples = list(map(lambda x: [
x,
'low quality',
512,
512,
'DPMSolverMultistep',
30,
0,
9
], word_list))[:500]
with block:
title = "Stable Diffusion 2.1 Demo"
desc = """ small stable diffusion Demo App. <br />
Click <strong>Generate image</strong> Button to generate image. <br />
Also Change params to have a try <br />
more size may cost more time. <br />
It's just a simplified demo, you can use more advanced features optimize image quality <br />"""
tutorial_link = "https://docs.cworld.ai/docs/cworld-ai/quick-start-stable-diffusion"
gr.HTML(
f"""
<div style="text-align: center; margin: 0 auto;">
<a href="https://cworld.ai">
<svg style="margin: 0 auto;" width="155" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 407 100">
<g id="SvgjsG2746"
transform="matrix(0.8454106280193237,0,0,0.8454106280193237,-4.2270531400966185,-4.2270531400966185)"
fill="#111">
<g xmlns="http://www.w3.org/2000/svg">
<g>
<g>
<path d="M50,11c21.5,0,39,17.5,39,39S71.5,89,50,89S11,71.5,11,50S28.5,11,50,11 M50,5C25.1,5,5,25.1,5,50s20.1,45,45,45 s45-20.1,45-45S74.9,5,50,5L50,5z"></path>
</g>
</g>
<path d="M55,75H45v-5c0-2.8,2.2-5,5-5h0c2.8,0,5,2.2,5,5V75z"></path>
<rect x="25" y="35" width="10" height="20"></rect>
<rect x="65" y="35" width="10" height="20"></rect>
</g>
</g>
<g id="SvgjsG2747"
transform="matrix(3.3650250410766605,0,0,3.3650250410766605,93.98098208712985,-3.546415304677616)"
fill="#111">
<path
d="M8.1 17.42 l1.42 1.28 c-0.94 1.04 -2.28 1.5 -3.78 1.5 c-2.84 0 -5.14 -2.18 -5.14 -5.12 s2.3 -5.14 5.14 -5.14 c1.5 0 2.84 0.46 3.78 1.5 l-1.42 1.28 c-0.58 -0.78 -1.42 -1.08 -2.36 -1.08 c-1.7 0 -3.08 1.42 -3.08 3.44 c0 2 1.38 3.44 3.08 3.44 c0.94 0 1.78 -0.3 2.36 -1.1 z M23.42 10.12 l2.06 0 l-3.76 9.88 l-1.26 0 l-2.46 -6.4 l-2.44 6.4 l-1.26 0 l-3.78 -9.88 l2.08 0 l2.34 6.9 l2.06 -6.08 l0.26 -0.82 l1.48 0 l0.28 0.82 l2.06 6.08 z M31.62 11.64 c-1.7 0 -3.08 1.42 -3.08 3.44 c0 2 1.38 3.44 3.08 3.44 s3.08 -1.44 3.08 -3.44 c0 -2.02 -1.38 -3.44 -3.08 -3.44 z M31.62 9.94 c2.84 0 5.14 2.2 5.14 5.14 s-2.3 5.12 -5.14 5.12 s-5.14 -2.18 -5.14 -5.12 s2.3 -5.14 5.14 -5.14 z M44.9 10.24 l-0.44 1.62 c-0.14 -0.08 -0.58 -0.22 -0.94 -0.22 c-1.7 0 -2.5 1.62 -2.5 3.62 l0 4.74 l-2.06 0 l0 -9.88 l2.06 0 l0 1.4 c0.24 -0.92 1.3 -1.58 2.48 -1.58 c0.54 0 1.12 0.14 1.4 0.3 z M48.379999999999995 4.619999999999999 l0 15.38 l-2.08 0 l0 -15.38 l2.08 0 z M50.98 15.08 c0 -2.94 2.1 -5.14 4.94 -5.14 c0.98 0 2.18 0.42 2.84 0.96 l0 -5.9 l2.08 0 l0 15 l-2.08 0 l0 -0.74 c-0.78 0.58 -1.86 0.94 -2.84 0.94 c-2.84 0 -4.94 -2.18 -4.94 -5.12 z M53.06 15.08 c0 2 1.38 3.44 3.06 3.44 c1.12 0 2.12 -0.52 2.64 -1.58 c0.28 -0.54 0.44 -1.18 0.44 -1.86 s-0.16 -1.32 -0.44 -1.88 c-0.52 -1.06 -1.52 -1.56 -2.64 -1.56 c-1.68 0 -3.06 1.42 -3.06 3.44 z M66.46 18.78 c0 0.8 -0.62 1.42 -1.42 1.42 c-0.78 0 -1.4 -0.62 -1.4 -1.42 c0 -0.76 0.62 -1.38 1.4 -1.38 c0.8 0 1.42 0.62 1.42 1.38 z M73.08 9.92 c2.84 0 3.98 1.72 3.98 3.18 l0 6.9 l-2.06 0 l0 -1.08 c-0.72 0.98 -2 1.26 -2.8 1.26 c-2.26 0 -3.74 -1.32 -3.74 -3.08 c0 -2.46 1.84 -3.34 3.74 -3.34 l2.8 0 l0 -0.66 c0 -0.62 -0.24 -1.48 -1.92 -1.48 c-0.94 0 -1.8 0.5 -2.36 1.28 l-1.42 -1.28 c0.94 -1.04 2.28 -1.7 3.78 -1.7 z M75 16.92 l0 -1.48 l-2.52 0 c-1.22 0 -2.08 0.62 -1.94 1.74 c0.12 0.94 0.88 1.32 1.94 1.32 c1.9 0 2.52 -0.9 2.52 -1.58 z M81.9 10.12 l0 9.88 l-2.06 0 l0 -9.88 l2.06 0 z M82 6.5 c0 0.64 -0.5 1.14 -1.14 1.14 c-0.62 0 -1.12 -0.5 -1.12 -1.14 c0 -0.62 0.5 -1.12 1.12 -1.12 c0.64 0 1.14 0.5 1.14 1.12 z"></path>
</g>
</svg>
</a>
<div
style="
display: inline-flex;
align-items: center;
gap: 0.8rem;
font-size: 1.75rem;
"
>
<h1 style="font-weight: 900; margin-bottom: 7px;margin-top:5px">
{title}
</h1>
</div>
<p style="margin-bottom: 10px; font-size: 94%; line-height: 23px;">
{desc}
There is the <a href="{tutorial_link}"> tutorial </a>
</p>
</div>
"""
)
with gr.Group():
with gr.Box():
with gr.Row(elem_id="prompt-container").style(mobile_collapse=False, equal_height=True):
with gr.Column(elem_id="prompt-column"):
text = gr.Textbox(
label="Enter your prompt",
show_label=False,
max_lines=1,
placeholder="Enter your prompt",
elem_id="prompt-text-input",
).style(
border=(True, False, True, True),
rounded=(True, False, False, True),
container=False,
)
negative = gr.Textbox(
label="Enter your negative prompt",
show_label=False,
max_lines=1,
placeholder="Enter a negative prompt",
elem_id="negative-prompt-text-input",
).style(
border=(True, False, True, True),
rounded=(True, False, False, True),
container=False,
)
with gr.Row(elem_id="txt2img_size", scale=4):
width = gr.Slider(minimum=64, maximum=1024, step=8, label="Width", value=512,
elem_id="txt2img_width")
height = gr.Slider(minimum=64, maximum=1024, step=8, label="Height", value=512,
elem_id="txt2img_height")
with gr.Row(elem_id="txt2img_sampler", scale=4):
seed = gr.Number(value=0, label="Seed", elem_id="txt2img_seed")
sampler = gr.Dropdown(
re_sampler, value="DPMSolverMultistep",
multiselect=False,
label="Sampler",
info="sampler select"
)
steps = gr.Slider(minimum=1, maximum=50, step=1, elem_id=f"steps", label="Sampling steps",
value=20)
with gr.Accordion("Advanced settings", open=False):
# gr.Markdown("Advanced settings are temporarily unavailable")
# samples = gr.Slider(label="Images", minimum=1, maximum=4, value=4, step=1)
# steps = gr.Slider(label="Steps", minimum=1, maximum=50, value=45, step=1)
guidance_scale = gr.Slider(
label="Guidance Scale", minimum=0, maximum=40, value=9, step=0.1
)
with gr.Row(elem_id="generate-container", elem_classes="generate-container").style(height="100"):
btn = gr.Button("Generate image", elem_id="generate-btn", elem_classes="generate-btn").style(
margin=False,
rounded=(False, True, True, False),
full_width=False,
)
gallery = gr.Gallery(
label="Generated images", show_label=False, elem_id="gallery"
).style()
result = gr.Textbox(label="Run Status")
# with gr.Group(elem_id="container-advanced-btns"):
# # advanced_button = gr.Button("Advanced options", elem_id="advanced-btn")
# with gr.Group(elem_id="share-btn-container"):
# community_icon = gr.HTML(community_icon_html)
# loading_icon = gr.HTML(loading_icon_html)
# share_button = gr.Button("Share to community", elem_id="share-btn")
ex = gr.Examples(examples=examples, fn=infer,
inputs=[text, negative, width, height, sampler, steps, seed, guidance_scale],
outputs=[gallery, result],
examples_per_page=5,
cache_examples=False)
ex.dataset.headers = [""]
negative.submit(infer, inputs=[text, negative, width, height, sampler, steps, seed, guidance_scale],
outputs=[gallery, result], postprocess=False)
text.submit(infer, inputs=[text, negative, width, height, sampler, steps, seed, guidance_scale],
outputs=[gallery, result], postprocess=False)
btn.click(infer, inputs=[text, negative, width, height, sampler, steps, seed, guidance_scale],
outputs=[gallery, result], postprocess=False)
block.queue(concurrency_count=5,
max_size=100).launch(
max_threads=150,
# server_port=6006,
# share=True,
)
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