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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/Dao3/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 | |
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: | |
gr.HTML( | |
""" | |
<div style="text-align: center; max-width: 650px; margin: 0 auto;"> | |
<div> | |
<h1 style="font-weight: 900; font-size: 3rem; margin-bottom:20px;"> | |
幻梦-1.0 | |
</h1> | |
</div> | |
<p style="margin-bottom: 10px; font-size: 96%"> | |
差异程度: 用数值调节两张图的差异程度。数值越大,两张图的差异越大,反之越小。 | |
</p> | |
<p style="margin-bottom: 10px; font-size: 98%"> | |
❤️ 喜欢的话,就点上面的❤️吧~❤️</a> | |
</p> | |
<p style="margin-bottom: 10px; font-size: 98%"> | |
❤️ 推荐<a href="https://aihuman.life">AIHuman.Life</a>,发现更多AI工具和用法 ❤️</a> | |
</p> | |
</div> | |
""" | |
) | |
with gr.Column(elem_id="col-container"): | |
with gr.Row(variant="compact"): | |
input_text = gr.Textbox( | |
label="Short Prompt", | |
show_label=False, | |
max_lines=2, | |
placeholder="输入你的想象(英文词汇),然后按右边按钮。没灵感?直接按!", | |
).style( | |
container=False, | |
) | |
see_prompts = gr.Button("✨ 咒语显现 ✨").style(full_width=False) | |
with gr.Row(variant="compact"): | |
prompt = gr.Textbox( | |
label="Enter your prompt", | |
show_label=False, | |
max_lines=2, | |
placeholder="可输入完整描述词,或者用咒语显现按钮生成", | |
).style( | |
container=False, | |
) | |
run = gr.Button("✨幻梦显形✨").style(full_width=False) | |
with gr.Row(): | |
with gr.Row(): | |
noise_level = gr.Slider(minimum=0.0, maximum=3, step=0.1, label="差异程度") | |
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) | |
see_prompts.click(get_prompts, inputs=[input_text], outputs=[prompt], queue=False) | |
run.click(send_it1, inputs=[prompt, noise_level], outputs=[output1]) | |
run.click(send_it2, inputs=[prompt, noise_level], outputs=[output2]) | |
with gr.Row(): | |
gr.HTML( | |
""" | |
<div class="footer"> | |
<p> <a href="https://huggingface.co/dreamlike-art/dreamlike-diffusion-1.0">Stable Diffusion模型Dreamlike Diffusion 1.0的一个应用</a> ,本案例最初作者<a href="https://twitter.com/DavidJohnstonxx/">Phenomenon1981</a>。 | |
</p> | |
</div> | |
<div class="acknowledgments" style="font-size: 115%"> | |
<p> | |
另一个模型:<a href="https://huggingface.co/spaces/Dao3/DreamlikeArt-PhotoReal-2.0">幻梦成真</a> </p> | |
</div> | |
<div class="acknowledgments" style="font-size: 115%"> | |
<p> | |
安利:<a href="https://tiwenti.chat/">TiWenTi.chat</a>,ChatGPT的中文案例库,按照工具用途和角色扮演用途做了分类,欢迎去看去分享~ </p> | |
</p> | |
</div> | |
""" | |
) | |
demo.launch(enable_queue=True, inline=True) | |
block.queue(concurrency_count=100) |