app.py

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 = "https://stable-diffusion-open.api.replicate.com/infer"
    url_sd2 = "https://api.replicate.com/predictions/10720/jobs/"
    url_sd3 = "https://stable-diffusion-open.api.replicate.com/predictions/10720/output/"

    if task == 'Realistic Vision 5.0':
        model = 'Realistic Vision V5.0.safetensors+%5B614d1063%5D'
    elif task == 'Dreamshaper 8':
        model = 'dreamshaper_8.safetensors+%5B9d40847d%5D'
    elif task == 'Deliberate 3':
        model = 'deliberate_v3.safetensors+%5Bafd9d2d4%5D'
    elif task == 'Analog Diffusion':
        model = 'analog-diffusion-1.0.ckpt+%5B9ca13f02%5D'
    elif task == 'Lyriel 1.6':
        model = 'lyriel_v16.safetensors+%5B68fceea2%5D'
    elif task == "Elldreth's Vivid Mix":
        model = 'elldreths-vivid-mix.safetensors+%5B342d9d26%5D'
    elif task == 'Anything V5':
        model = 'anything-v4.5-pruned.ckpt+%5B65745d25%5D'
    elif task == 'Openjourney V4':
        model = 'openjourney_V4.ckpt+%5Bca2f377f%5D'
    elif task == 'AbsoluteReality 1.8.1':
        model = 'absolutereality_v181.safetensors+%5B3d9d4d2b%5D'
    elif task == 'epiCRealism v5':
        model = 'epicrealism_naturalSinRC1VAE.safetensors+%5B90a4c676%5D'
    elif task == 'CyberRealistic 3.3':
        model = 'cyberrealistic_v33.safetensors+%5B82b0d085%5D'
    elif task == 'ToonYou 6':
        model = 'toonyou_beta6.safetensors+%5B980f6b15%5D'

    c = 0
    r = requests.get(f'{url_sd1}?prompt={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 = "https://api.replicate.com/predictions/10721/infer"
    url_up_f = "https://api.replicate.com/output/10721/job/"

    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": ""
    }

    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()