app.py

import gradio as gr
import os
import sys
from pathlib import Path
import random
import string
import time
from queue import Queue
from threading import Thread
import emoji

text_gen = gr.Interface.load("spaces/phenomenon1981/MagicPrompt-Stable-Diffusion")

def get_prompts(prompt_text):
    if prompt_text:
        return text_gen("dreamlikeart, " + prompt_text)
    else:
        return text_gen("")


proc1 = gr.Interface.load("models/dreamlike-art/dreamlike-diffusion-1.0")


def restart_script_periodically():
    while True:
        random_time = random.randint(540, 600)
        time.sleep(random_time)
        os.execl(sys.executable, sys.executable, *sys.argv)


restart_thread = Thread(target=restart_script_periodically, daemon=True)
restart_thread.start()

queue = Queue()
queue_threshold = 100


def add_random_noise(prompt, noise_level=0.00):
    if noise_level == 0:
        noise_level = 0.00
    percentage_noise = noise_level * 5
    num_noise_chars = int(len(prompt) * (percentage_noise / 100))
    noise_indices = random.sample(range(len(prompt)), num_noise_chars)
    prompt_list = list(prompt)
    noise_chars = list(string.ascii_letters + string.punctuation + ' ' + string.digits)
    noise_chars.extend(
        ['😍', '💩', '😂', '🤔', '😊', '🤗', '😭', '🙄', '😷', '🤯', '🤫', '🥴', '😴', '🤩', '🥳', '😔', '😩', '🤪',
         '😇', '🤢', '😈', '👹', '👻', '🤖', '👽', '💀', '🎃', '🎅', '🎄', '🎁', '🎂', '🎉', '🎈', '🎊', '🎮', '❤️',
         '💔', '💕', '💖', '💗', '🐶', '🐱', '🐭', '🐹', '🦊', '🐻', '🐨', '🐯', '🦁', '🐘', '🔥', '🌧️', '🌞', '🌈',
         '💥', '🌴', '🌊', '🌺', '🌻', '🌸', '🎨', '🌅', '🌌', '☁️', '⛈️', '❄️', '☀️', '🌤️', '⛅️', '🌥️', '🌦️', '🌧️',
         '🌩️', '🌨️', '🌫️', '☔️', '🌬️', '💨', '🌪️', '🌈'])
    for index in noise_indices:
        prompt_list[index] = random.choice(noise_chars)
    return "".join(prompt_list)


def send_it1(inputs, noise_level, proc1=proc1):
    prompt_with_noise = add_random_noise(inputs, noise_level)
    while queue.qsize() >= queue_threshold:
        time.sleep(2)
    queue.put(prompt_with_noise)
    output1 = proc1(prompt_with_noise)
    return output1
    
with gr.Blocks(css='style.css') as demo:
    with gr.HTML("""<h1 style="font-weight: 900; margin-bottom: 7px;margin-top:5px">
                  RayicDegeri.com - Araba Resmi Oluşturucu Yapay Zeka Sistemi
                </h1>
                <h3 style="font-weight: 900; margin-bottom: 7px;margin-top:5px">
                  Lütfen, Marka: ...., Seri: ..., Model: ...., Yıl: .... şeklinde giriniz.
                  Örneğin: Marka: Renault, Seri: Symbol, Model: 1.5 dCi Authentique, Yıl: 2012
                </h3>""")

    with gr.Row(variant="compact"):
        prompt_marka = gr.Textbox(
            label="Enter your prompt",
            show_label=False,
            max_lines=2,
            placeholder="Markanızı Giriniz. (Örneğin, Renault, BMW, AUDI)",
        ).style(
            container=False,
        )

        prompt_seri = gr.Textbox(
            label="Enter your prompt",
            show_label=False,
            max_lines=2,
            placeholder="Serinizi Giriniz. (Örneğin, Clio, Symbol)",
        ).style(
            container=False,
        )

        prompt_model = gr.Textbox(
            label="Enter your prompt",
            show_label=False,
            max_lines=2,
            placeholder="Modelinizi Giriniz. (Örneğin, 1.5 dCi Authentique)",
        ).style(
            container=False,
        )

        prompt_yil = gr.Textbox(
            label="Enter your prompt",
            show_label=False,
            max_lines=2,
            placeholder="Aracınızın Yılını Giriniz. (Örneğin, 2012,2020)",
        ).style(
            container=False,
        )
        prompts = f"Brand: {prompt_marka}  / Series: {prompt_seri}  / Model: {prompt_model}  / Year: {prompt_yil}"
        run = gr.Button("Oluştur").style(full_width=False)

    with gr.Row():
        with gr.Row():
            noise_level = gr.Slider(minimum=0.0, maximum=3, step=0.1, label="Görüntünün Gürültü Katsayısı")
    with gr.Row():
        with gr.Row():
            output1 = gr.Image(label="Dreamlike Diffusion 1.0", show_label=False)

    run.click(send_it1, inputs=[prompts, noise_level], outputs=[output1])
    with gr.Row():
                gr.HTML(

)

demo.launch(enable_queue=True, inline=True)
block.queue(concurrency_count=100)