sdxl2 / app.py
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import gradio as gr
import requests
import time
import json
from contextlib import closing
from websocket import create_connection
from deep_translator import GoogleTranslator
from langdetect import detect
import os
from PIL import Image
import io
import base64
def flip_text(prompt, negative_prompt, task, steps, sampler, cfg_scale, seed):
result = {"prompt": prompt,"negative_prompt": negative_prompt,"task": task,"steps": steps,"sampler": sampler,"cfg_scale": cfg_scale,"seed": seed}
print(result)
language = detect(prompt)
if language == 'ru':
prompt = GoogleTranslator(source='ru', target='en').translate(prompt)
print(prompt)
cfg = int(cfg_scale)
steps = int(steps)
seed = int(seed)
width = 1024
height = 1024
url_sd1 = os.getenv("url_sd1")
url_sd2 = os.getenv("url_sd2")
url_sd3 = os.getenv("url_sd3")
print(task)
try:
print('n_1')
with closing(create_connection(f"{url_sd3}", timeout=60)) as conn:
conn.send('{"fn_index":3,"session_hash":""}')
conn.send(f'{{"data":["{text}, 4k photo","[deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry",7.5,"(No style)"],"event_data":null,"fn_index":3,"session_hash":""}}')
while True:
status = json.loads(conn.recv())['msg']
print(status)
if status == 'estimation':
continue
if status == 'process_starts':
break
photo = json.loads(conn.recv())['output']['data'][0][0]
photo = photo.replace('data:image/jpeg;base64,', '').replace('data:image/png;base64,', '')
photo = Image.open(io.BytesIO(base64.decodebytes(bytes(photo, "utf-8"))))
return photo
except:
print(n_2)
if task == 'Stable Diffusion XL 1.0':
model = 'sd_xl_base_1.0'
if task == 'Crystal Clear XL':
model = '[3d] crystalClearXL_ccxl_97637'
if task == 'Juggernaut XL':
model = '[photorealistic] juggernautXL_version2_113240'
if task == 'DreamShaper XL':
model = '[base model] dreamshaperXL09Alpha_alpha2Xl10_91562'
if task == 'SDXL Niji':
model = '[midjourney] sdxlNijiV51_sdxlNijiV51_112807'
if task == 'Cinemax SDXL':
model = '[movie] cinemaxAlphaSDXLCinema_alpha1_107473'
if task == 'NightVision XL':
model = '[photorealistic] nightvisionXLPhotorealisticPortrait_beta0702Bakedvae_113098'
negative = negative_prompt
try:
with closing(create_connection(f"{url_sd1}")) as conn:
conn.send('{"fn_index":231,"session_hash":""}')
conn.send(f'{{"data":["task()","{prompt}","{negative}",[],{steps},"{sampler}",false,false,1,1,{cfg},{seed},-1,0,0,0,false,{width},{height},false,0.7,2,"Lanczos",0,0,0,"Use same sampler","","",[],"None",true,"{model}","Automatic",null,null,null,false,false,"positive","comma",0,false,false,"","Seed","",[],"Nothing","",[],"Nothing","",[],true,false,false,false,0,null,null,false,null,null,false,null,null,false,50,[],"","",""],"event_data":null,"fn_index":231,"session_hash":""}}')
print(conn.recv())
print(conn.recv())
print(conn.recv())
print(conn.recv())
photo = f"{url_sd2}" + str(json.loads(conn.recv())['output']['data'][0][0]["name"])
return photo
except:
return None
css = """
#generate {
width: 100%;
background: #e253dd !important;
border: none;
border-radius: 50px;
outline: none !important;
color: white;
}
#generate:hover {
background: #de6bda !important;
outline: none !important;
color: #fff;
}
footer {visibility: hidden !important;}
"""
with gr.Blocks(css=css) as demo:
with gr.Tab("Базовые настройки"):
with gr.Row():
prompt = gr.Textbox(placeholder="Введите описание изображения...", show_label=True, label='Описание изображения:', lines=3)
with gr.Row():
task = gr.Radio(interactive=True, value="Stable Diffusion XL 1.0", show_label=True, label="Модель нейросети:", choices=['Stable Diffusion XL 1.0', 'Crystal Clear XL',
'Juggernaut XL', 'DreamShaper XL',
'SDXL Niji', 'Cinemax SDXL', 'NightVision XL'])
with gr.Tab("Расширенные настройки"):
with gr.Row():
negative_prompt = gr.Textbox(placeholder="Negative Prompt", show_label=True, label='Negative Prompt:', lines=3, value="[deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry")
with gr.Row():
sampler = gr.Dropdown(value="DPM++ SDE Karras", show_label=True, label="Sampling Method:", choices=[
"Euler", "Euler a", "Heun", "DPM++ 2M", "DPM++ SDE", "DPM++ 2M Karras", "DPM++ SDE Karras", "DDIM"])
with gr.Row():
steps = gr.Slider(show_label=True, label="Sampling Steps:", minimum=1, maximum=50, value=35, step=1)
with gr.Row():
cfg_scale = gr.Slider(show_label=True, label="CFG Scale:", minimum=1, maximum=20, value=7, step=1)
with gr.Row():
seed = gr.Number(show_label=True, label="Seed:", minimum=-1, maximum=1000000, value=-1, step=1)
with gr.Column():
text_button = gr.Button("Сгенерировать изображение", variant='primary', elem_id="generate")
with gr.Column(scale=2):
image_output = gr.Image(show_label=True, label='Результат:', elem_id='image_output')
text_button.click(flip_text, inputs=[prompt, negative_prompt, task, steps, sampler, cfg_scale, seed], outputs=image_output)
demo.queue(concurrency_count=12)
demo.launch()