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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("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(['๐', '๐ฉ', '๐', '๐ค', '๐', '๐ค', '๐ญ', '๐', '๐ท', '๐คฏ', '๐คซ', '๐ฅด', '๐ด', '๐คฉ', '๐ฅณ', '๐', '๐ฉ', '๐คช', '๐', '๐คข', '๐', '๐น', '๐ป', '๐ค', '๐ฝ', '๐', '๐', '๐ ', '๐', '๐', '๐', '๐', '๐', '๐', '๐ฎ', 'โค๏ธ', '๐', '๐', '๐', '๐', '๐ถ', '๐ฑ', '๐ญ', '๐น', '๐ฆ', '๐ป', '๐จ', '๐ฏ', '๐ฆ', '๐', '๐ฅ', '๐ง๏ธ', '๐', '๐', '๐ฅ', '๐ด', '๐', '๐บ', '๐ป', '๐ธ', '๐จ', '๐ ', '๐', 'โ๏ธ', 'โ๏ธ', 'โ๏ธ', 'โ๏ธ', '๐ค๏ธ', 'โ ๏ธ', '๐ฅ๏ธ', '๐ฆ๏ธ', '๐ง๏ธ', '๐ฉ๏ธ', '๐จ๏ธ', '๐ซ๏ธ', 'โ๏ธ', '๐ฌ๏ธ', '๐จ', '๐ช๏ธ', '๐']) | |
| 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;"> | |
| Dreamlike Photoreal 2.0 | |
| </h1> | |
| </div> | |
| <p style="margin-bottom: 10px; font-size: 96%"> | |
| 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, | |
| <a href="https://twitter.com/DavidJohnstonxx/">created by Phenomenon1981</a>. | |
| </p> | |
| <p style="margin-bottom: 10px; font-size: 98%"> | |
| โค๏ธ Press the Like Button if you enjoy my space! โค๏ธ</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="Enter a basic idea and click 'Magic Prompt'. Got no ideas? No problem, Simply just hit the magic button!", | |
| ).style( | |
| container=False, | |
| ) | |
| see_prompts = gr.Button("โจ Magic Prompt โจ").style(full_width=False) | |
| with gr.Row(variant="compact"): | |
| prompt = gr.Textbox( | |
| label="Enter your prompt", | |
| show_label=False, | |
| max_lines=2, | |
| placeholder="Full Prompt", | |
| ).style( | |
| container=False, | |
| ) | |
| run = gr.Button("Generate Images").style(full_width=False) | |
| with gr.Row(): | |
| with gr.Row(): | |
| noise_level = gr.Slider(minimum=0.0, maximum=3, step=0.1, label="Noise Level") | |
| 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( | |
| """ | |
| <div class="footer"> | |
| <p> Demo for <a href="https://huggingface.co/dreamlike-art/dreamlike-photoreal-2.0">Dreamlike Photoreal 2.0</a> Stable Diffusion model | |
| </p> | |
| </div> | |
| <div class="acknowledgments" style="font-size: 115%"> | |
| <p> Unleash your creative side and generate mesmerizing images with just a few clicks! Enter a spark of inspiration in the "Basic Idea" text box and click the "Magic Prompt" button to elevate it to a polished masterpiece. Make any final tweaks in the "Full Prompt" box and hit the "Generate Images" button to watch your vision come to life. Experiment with the "Noise Level" for a diverse range of outputs, from similar to wildly unique. Let the fun begin! | |
| </p> | |
| </div> | |
| """ | |
| ) | |
| demo.launch(enable_queue=True, inline=True) | |
| block.queue(concurrency_count=100) |