car_prediction / app.py
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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(
['๐Ÿ˜', '๐Ÿ’ฉ', '๐Ÿ˜‚', '๐Ÿค”', '๐Ÿ˜Š', '๐Ÿค—', '๐Ÿ˜ญ', '๐Ÿ™„', '๐Ÿ˜ท', '๐Ÿคฏ', '๐Ÿคซ', '๐Ÿฅด', '๐Ÿ˜ด', '๐Ÿคฉ', '๐Ÿฅณ', '๐Ÿ˜”', '๐Ÿ˜ฉ', '๐Ÿคช',
'๐Ÿ˜‡', '๐Ÿคข', '๐Ÿ˜ˆ', '๐Ÿ‘น', '๐Ÿ‘ป', '๐Ÿค–', '๐Ÿ‘ฝ', '๐Ÿ’€', '๐ŸŽƒ', '๐ŸŽ…', '๐ŸŽ„', '๐ŸŽ', '๐ŸŽ‚', '๐ŸŽ‰', '๐ŸŽˆ', '๐ŸŽŠ', '๐ŸŽฎ', 'โค๏ธ',
'๐Ÿ’”', '๐Ÿ’•', '๐Ÿ’–', '๐Ÿ’—', '๐Ÿถ', '๐Ÿฑ', '๐Ÿญ', '๐Ÿน', '๐ŸฆŠ', '๐Ÿป', '๐Ÿจ', '๐Ÿฏ', '๐Ÿฆ', '๐Ÿ˜', '๐Ÿ”ฅ', '๐ŸŒง๏ธ', '๐ŸŒž', '๐ŸŒˆ',
'๐Ÿ’ฅ', '๐ŸŒด', '๐ŸŒŠ', '๐ŸŒบ', '๐ŸŒป', '๐ŸŒธ', '๐ŸŽจ', '๐ŸŒ…', '๐ŸŒŒ', 'โ˜๏ธ', 'โ›ˆ๏ธ', 'โ„๏ธ', 'โ˜€๏ธ', '๐ŸŒค๏ธ', 'โ›…๏ธ', '๐ŸŒฅ๏ธ', '๐ŸŒฆ๏ธ', '๐ŸŒง๏ธ',
'๐ŸŒฉ๏ธ', '๐ŸŒจ๏ธ', '๐ŸŒซ๏ธ', 'โ˜”๏ธ', '๐ŸŒฌ๏ธ', '๐Ÿ’จ', '๐ŸŒช๏ธ', '๐ŸŒˆ'])
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)
image.save(f"{prompt_list}.png")
return output1
def send_it2(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)
output2 = proc1(prompt_with_noise)
return output2
# def send_it3(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)
# output3 = proc1(prompt_with_noise)
# return output3
# def send_it4(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)
# output4 = proc1(prompt_with_noise)
# return output4
with gr.Blocks(css='style.css') as demo:
with gr.Row(variant="compact"):
prompt = gr.Textbox(
label="Enter your prompt",
show_label=False,
max_lines=2,
placeholder="Araรง bilginizi giriniz.",
).style(
container=False,
)
run = gr.Button("OluลŸtur [Az detaylฤฑ]").style(full_width=False)
with gr.Row():
with gr.Row():
noise_level = gr.Slider(minimum=0.0, maximum=3, step=0.1, label="Gรถrรผntรผnรผn Gรผrรผltรผ Katsayฤฑsฤฑ")
with gr.Row():
with gr.Row():
output1 = gr.Image(label="Dreamlike Diffusion 1.0", show_label=False)
output2 = gr.Image(label="Dreamlike Diffusion 1.0", show_label=False)
run.click(send_it1, inputs=[prompt, noise_level], outputs=[output1])
with gr.Row():
gr.HTML(
"""
<div class="footer">
<p><a href=f"/{prompt_list}.png" download>
<img src=f"/{prompt_list}.png">
</a>
</p>
</div>
"""
)
demo.launch(enable_queue=True, inline=True)
block.queue(concurrency_count=100)