Spaces:
Running
Running
File size: 7,331 Bytes
8b1029b 352c70d 8b1029b 352c70d 8b1029b bf766c3 8b1029b 410ba09 8b1029b 410ba09 352c70d 410ba09 352c70d 410ba09 8b1029b 849e813 8b1029b 410ba09 8b1029b 410ba09 962fd7c 410ba09 962fd7c 410ba09 8b1029b 410ba09 561a602 8b1029b 410ba09 759f4f5 8b1029b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 |
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)
url_sd1 = os.getenv("url_sd1")
url_sd2 = os.getenv("url_sd2")
url_sd3 = os.getenv("url_sd3")
if task == 'Realistic Vision 5.0':
model = 'Realistic_Vision_V5.0.safetensors+%5B614d1063%5D'
if task == 'Dreamshaper 8':
model = 'dreamshaper_8.safetensors+%5B9d40847d%5D'
if task == 'Deliberate 3':
model = 'deliberate_v3.safetensors+%5Bafd9d2d4%5D'
if task == 'Analog Diffusion':
model = 'analog-diffusion-1.0.ckpt+%5B9ca13f02%5D'
if task == 'Lyriel 1.6':
model = 'lyriel_v16.safetensors+%5B68fceea2%5D'
if task == "Elldreth's Vivid Mix":
model = 'elldreths-vivid-mix.safetensors+%5B342d9d26%5D'
if task == 'Anything V5':
model = 'anything-v4.5-pruned.ckpt+%5B65745d25%5D'
if task == 'Openjourney V4':
model = 'openjourney_V4.ckpt+%5Bca2f377f%5D'
if task == 'AbsoluteReality 1.8.1':
model = 'absolutereality_v181.safetensors+%5B3d9d4d2b%5D'
if task == 'epiCRealism v5':
model = 'epicrealism_naturalSinRC1VAE.safetensors+%5B90a4c676%5D'
if task == 'CyberRealistic 3.3':
model = 'cyberrealistic_v33.safetensors+%5B82b0d085%5D'
if task == 'ToonYou 6':
model = 'toonyou_beta6.safetensors+%5B980f6b15%5D'
c = 0
r = requests.get(f'{url_sd1}{prompt}&model={model}&negative_prompt={negative_prompt}&steps={steps}&cfg={cfg}&seed={seed}&sampler={sampler}&aspect_ratio=square', timeout=10)
job = r.json()['job']
while c < 10:
c += 1
time.sleep(2)
r2 = requests.get(f'{url_sd2}{job}', timeout=10)
status = r2.json()['status']
if status == 'succeeded':
photo = f'{url_sd3}{job}.png'
return photo
if status == "queued":
continue
if status == 'failed':
return None
def mirror(image_output, scale_by, method, gfpgan, codeformer):
url_up = os.getenv("url_up")
url_up_f = os.getenv("url_up_f")
scale_by = int(scale_by)
gfpgan = int(gfpgan)
codeformer = int(codeformer)
with open(image_output, "rb") as image_file:
encoded_string2 = base64.b64encode(image_file.read())
encoded_string2 = str(encoded_string2).replace("b'", '')
encoded_string2 = "data:image/png;base64," + encoded_string2
data = {"fn_index":81,"data":[0,0,encoded_string2,None,"","",True,gfpgan,codeformer,0,scale_by,512,512,None,method,"None",1,False,[],"",""],"session_hash":""}
# print(data)
r = requests.post(f"{url_up}", json=data, timeout=100)
# print(r.text)
ph = f"{url_up_f}" + str(r.json()['data'][0][0]['name'])
return ph
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;
}
#image_output {
display: flex;
justify-content: center;
}
footer {visibility: hidden !important;}
#image_output {
height: 100% !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="Deliberate 3", show_label=True, label="Модель нейросети:",
choices=["AbsoluteReality 1.8.1", "Elldreth's Vivid Mix", "Anything V5", "Openjourney V4", "Analog Diffusion",
"Lyriel 1.6", "Realistic Vision 5.0", "Dreamshaper 8", "epiCRealism v5",
"CyberRealistic 3.3", "ToonYou 6", "Deliberate 3"])
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 Karras", "DPM++ SDE Karras", "DDIM"])
with gr.Row():
steps = gr.Slider(show_label=True, label="Sampling Steps:", minimum=1, maximum=30, value=25, 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.Tab("Настройки апскейлинга"):
with gr.Column():
with gr.Row():
scale_by = gr.Number(show_label=True, label="Во сколько раз увеличить:", minimum=1, maximum=4, value=2, step=1)
with gr.Row():
method = gr.Dropdown(show_label=True, value="ESRGAN_4x", label="Алгоритм увеличения", choices=["ScuNET GAN", "SwinIR 4x", "ESRGAN_4x", "R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B"])
with gr.Column():
with gr.Row():
gfpgan = gr.Slider(show_label=True, label="Эффект GFPGAN (для улучшения лица)", minimum=0, maximum=1, value=0, step=0.1)
with gr.Row():
codeformer = gr.Slider(show_label=True, label="Эффект CodeFormer (для улучшения лица)", minimum=0, maximum=1, value=0, step=0.1)
with gr.Column():
text_button = gr.Button("Сгенерировать изображение", variant='primary', elem_id="generate")
with gr.Column():
image_output = gr.Image(show_label=True, show_download_button=True, interactive=False, label='Результат:', elem_id='image_output', type='filepath')
text_button.click(flip_text, inputs=[prompt, negative_prompt, task, steps, sampler, cfg_scale, seed], outputs=image_output)
img2img_b = gr.Button("Увеличить изображение", variant='secondary')
image_i2i = gr.Image(show_label=True, label='Увеличенное изображение:')
img2img_b.click(mirror, inputs=[image_output, scale_by, method, gfpgan, codeformer], outputs=image_i2i)
demo.queue(concurrency_count=24)
demo.launch() |