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import gradio as gr | |
import os | |
import sys | |
from pathlib import Path | |
import random | |
import string | |
import time | |
text_gen=gr.Interface.load("spaces/Omnibus/MagicPrompt-Stable-Diffusion") | |
proc1=gr.Interface.load("models/dreamlike-art/dreamlike-photoreal-2.0") | |
proc5=gr.Interface.load("models/dreamlike-art/dreamlike-diffusion-1.0") | |
def add_random_noise(prompt, noise_level=0.1): | |
noise = "".join(random.choices(string.ascii_letters + string.punctuation, k=int(noise_level * 10))) | |
return prompt + noise | |
def send_it1(inputs, noise_level, proc1=proc1): | |
prompt_with_noise = add_random_noise(inputs, noise_level) | |
output1=proc1(prompt_with_noise) | |
time.sleep(1) | |
return output1 | |
def send_it2(inputs, noise_level, proc1=proc1): | |
prompt_with_noise = add_random_noise(inputs, noise_level) | |
output2 = proc1(prompt_with_noise) | |
time.sleep(1) | |
return output2 | |
def send_it3(inputs, noise_level, proc1=proc1): | |
prompt_with_noise = add_random_noise(inputs, noise_level) | |
output3 = proc1(prompt_with_noise) | |
time.sleep(1) | |
return output3 | |
def send_it4(inputs, noise_level, proc1=proc1): | |
prompt_with_noise = add_random_noise(inputs, noise_level) | |
output4 = proc1(prompt_with_noise) | |
time.sleep(1) | |
return output4 | |
def send_it5(inputs, noise_level, proc5=proc5): | |
prompt_with_noise = add_random_noise(inputs, noise_level) | |
output5 = proc5(prompt_with_noise) | |
time.sleep(1) | |
return output5 | |
def send_it6(inputs, noise_level, proc5=proc5): | |
prompt_with_noise = add_random_noise(inputs, noise_level) | |
output6 = proc5(prompt_with_noise) | |
time.sleep(1) | |
return output6 | |
def send_it7(inputs, noise_level, proc5=proc5): | |
prompt_with_noise = add_random_noise(inputs, noise_level) | |
output7 = proc5(prompt_with_noise) | |
time.sleep(1) | |
return output7 | |
def send_it8(inputs, noise_level, proc5=proc5): | |
prompt_with_noise = add_random_noise(inputs, noise_level) | |
output8 = proc5(prompt_with_noise) | |
time.sleep(1) | |
return output8 | |
def get_prompts(prompt_text): | |
return text_gen(prompt_text) | |
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=1, 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", blocking=True) | |
with gr.Row(): | |
output1=gr.Image(label="Dreamlike Photoreal 2.0", blocking=True, timeout=30) | |
output2=gr.Image(label="Dreamlike Photoreal 2.0", blocking=True, timeout=30) | |
with gr.Row(): | |
output3=gr.Image(label="Dreamlike Photoreal 2.0", blocking=True, timeout=30) | |
output4=gr.Image(label="Dreamlike Photoreal 2.0", blocking=True, timeout=30) | |
with gr.Row(): | |
output5=gr.Image(label="Dreamlike Diffusion 1.0", blocking=True, timeout=30) | |
output6=gr.Image(label="Dreamlike Diffusion 1.0", blocking=True, timeout=30) | |
with gr.Row(): | |
output7=gr.Image(label="Dreamlike Diffusion 1.0", blocking=True, timeout=30) | |
output8=gr.Image(label="Dreamlike Diffusion 1.0", blocking=True, timeout=30) | |
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.queue(concurrency_count=8) | |
myface.launch(enable_queue=True, inline=True) |