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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
queue = Queue()
queue_threshold = 8
text_gen=gr.Interface.load("spaces/Omnibus/MagicPrompt-Stable-Diffusion")
proc1=gr.Interface.load("models/dreamlike-art/dreamlike-diffusion-1.0")
def reset_queue_periodically():
start_time = time.time()
while True:
if time.time() - start_time > 300: # 300 seconds
queue.queue.clear()
start_time = time.time()
reset_queue_thread = Thread(target=reset_queue_periodically)
reset_queue_thread.start()
def add_random_noise(prompt, noise_level=0.07):
# Get the percentage of characters to add as noise
percentage_noise = noise_level * 5
# Get the number of characters to add as noise
num_noise_chars = int(len(prompt) * (percentage_noise/100))
# Get the indices of the characters to add noise to
noise_indices = random.sample(range(len(prompt)), num_noise_chars)
# Add noise to the selected characters
prompt_list = list(prompt)
for index in noise_indices:
prompt_list[index] = random.choice(string.ascii_letters + string.punctuation)
return "".join(prompt_list)
def send_it1(inputs, noise_level, proc1=proc1):
global queue
prompt_with_noise = add_random_noise(inputs, noise_level)
queue.put(prompt_with_noise)
while queue.qsize() > queue_threshold:
time.sleep(1)
output1 = proc1(queue.get())
return output1
def send_it2(inputs, noise_level, proc1=proc1):
global queue
prompt_with_noise = add_random_noise(inputs, noise_level)
queue.put(prompt_with_noise)
while queue.qsize() > queue_threshold:
time.sleep(1)
output2 = proc1(queue.get())
return output2
def send_it3(inputs, noise_level, proc1=proc1):
global queue
prompt_with_noise = add_random_noise(inputs, noise_level)
queue.put(prompt_with_noise)
while queue.qsize() > queue_threshold:
time.sleep(1)
output3 = proc1(queue.get())
return output3
def send_it4(inputs, noise_level, proc1=proc1):
global queue
prompt_with_noise = add_random_noise(inputs, noise_level)
queue.put(prompt_with_noise)
while queue.qsize() > queue_threshold:
time.sleep(1)
output4 = proc1(queue.get())
return output4
def send_it5(inputs, noise_level, proc1=proc1):
global queue
prompt_with_noise = add_random_noise(inputs, noise_level)
queue.put(prompt_with_noise)
while queue.qsize() > queue_threshold:
time.sleep(1)
output5 = proc1(queue.get())
return output5
def send_it6(inputs, noise_level, proc1=proc1):
global queue
prompt_with_noise = add_random_noise(inputs, noise_level)
queue.put(prompt_with_noise)
while queue.qsize() > queue_threshold:
time.sleep(1)
output6 = proc1(queue.get())
return output6
def send_it7(inputs, noise_level, proc1=proc1):
global queue
prompt_with_noise = add_random_noise(inputs, noise_level)
queue.put(prompt_with_noise)
while queue.qsize() > queue_threshold:
time.sleep(1)
output7 = proc1(queue.get())
return output7
def send_it8(inputs, noise_level, proc1=proc1):
global queue
prompt_with_noise = add_random_noise(inputs, noise_level)
queue.put(prompt_with_noise)
while queue.qsize() > queue_threshold:
time.sleep(1)
output8 = proc1(queue.get())
return output8
def get_prompts(prompt_text):
global queue
queue.put(prompt_text)
while queue.qsize() > queue_threshold:
time.sleep(1)
output = text_gen(queue.get())
return output
with gr.Blocks() as myface:
with gr.Row():
input_text=gr.Textbox(label="Short Prompt")
see_prompts=gr.Button("Magic Prompt")
with gr.Row():
prompt=gr.Textbox(label="Enter Prompt")
noise_level=gr.Slider(minimum=0.1, maximum=3, step=0.1, label="Noise Level: Controls how much randomness is added to the input before it is sent to the model. Higher noise level produces more diverse outputs, while lower noise level produces similar outputs.")
run=gr.Button("Generate")
with gr.Row():
like_message = gr.Button("❤️ Press the Like Button if you enjoy my space! ❤️")
with gr.Row():
output1=gr.Image(label="Dreamlike Diffusion 1.0")
output2=gr.Image(label="Dreamlike Diffusion 1.0")
with gr.Row():
output3=gr.Image(label="Dreamlike Diffusion 1.0")
output4=gr.Image(label="Dreamlike Diffusion 1.0")
with gr.Row():
output5=gr.Image(label="Dreamlike Diffusion 1.0")
output6=gr.Image(label="Dreamlike Diffusion 1.0")
with gr.Row():
output7=gr.Image(label="Dreamlike Diffusion 1.0")
output8=gr.Image(label="Dreamlike Diffusion 1.0")
run.click(send_it1, inputs=[prompt, noise_level], outputs=[output1])
run.click(send_it2, inputs=[prompt, noise_level], outputs=[output2])
run.click(send_it3, inputs=[prompt, noise_level], outputs=[output3])
run.click(send_it4, inputs=[prompt, noise_level], outputs=[output4])
run.click(send_it5, inputs=[prompt, noise_level], outputs=[output5])
run.click(send_it6, inputs=[prompt, noise_level], outputs=[output6])
run.click(send_it7, inputs=[prompt, noise_level], outputs=[output7])
run.click(send_it8, inputs=[prompt, noise_level], outputs=[output8])
see_prompts.click(get_prompts, inputs=[input_text], outputs=[prompt])
myface.launch(enable_queue=True, inline=True)
myface.queue(concurrency_count=8)
reset_queue_thread.join()