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("photo, " + prompt_text) else: return text_gen("") proc1=gr.Interface.load("models/dreamlike-art/dreamlike-photoreal-2.0") 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( """

幻梦成真-2.0

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。

❤️ 喜欢的话,就点上面的❤️吧~❤️

""" ) 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="输入描述词", 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("✨ 幻梦成真✨").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-photoreal-2.0",show_label=False) output2=gr.Image(label="Dreamlike-photoreal-2.0",show_label=False) #with gr.Row(): #output1=gr.Image() 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( """

另一个模型幻梦

安利:还有一个汉化项目:TiwenTi.chat,这是一个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~

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