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(prompt_text + " Dream") else: return text_gen("") proc1=gr.Interface.load("models/Yntec/DreamAnything") def restart_script_periodically(): while True: random_time = random.randint(5400, 6000) 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 #Don't add noise to the first picture no matter what (the point of noise is to get varied outputs, the first one doesn't need to vary about anything) def noadd_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) #normal behavior 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(['๐Ÿ˜', 'beautiful', '๐Ÿ˜‚', '๐Ÿค”', '๐Ÿ˜Š', '๐Ÿค—', '๐Ÿ˜ญ', '๐Ÿ™„', 'pretty', '๐Ÿคฏ', '๐Ÿคซ', '๐Ÿฅด', 'sitting', '๐Ÿคฉ', '๐Ÿฅณ', '๐Ÿ˜”', '๐Ÿ˜ฉ', '๐Ÿคช', '๐Ÿ˜‡', 'retro', '๐Ÿ˜ˆ', '๐Ÿ‘น', 'masterpiece', '๐Ÿค–', '๐Ÿ‘ฝ', 'high quality', '๐ŸŽƒ', '๐ŸŽ…', '๐ŸŽ„', '๐ŸŽ', '๐ŸŽ‚', '๐ŸŽ‰', '๐ŸŽˆ', '๐ŸŽŠ', '๐ŸŽฎ', 'โค๏ธ', '๐Ÿ’”', '๐Ÿ’•', '๐Ÿ’–', '๐Ÿ’—', '๐Ÿถ', '๐Ÿฑ', 'visible', '๐Ÿน', '๐ŸฆŠ', '๐Ÿป', '๐Ÿจ', '๐Ÿฏ', '๐Ÿฆ', '๐Ÿ˜', '๐Ÿ”ฅ', '๐ŸŒง๏ธ', '๐ŸŒž', '๐ŸŒˆ', '๐Ÿ’ฅ', '๐ŸŒด', '๐ŸŒŠ', '๐ŸŒบ', '๐ŸŒป', '๐ŸŒธ', '๐ŸŽจ', '๐ŸŒ…', '๐ŸŒŒ', 'โ˜๏ธ', 'โ›ˆ๏ธ', 'โ„๏ธ', 'โ˜€๏ธ', '๐ŸŒค๏ธ', 'โ›…๏ธ', '๐ŸŒฅ๏ธ', '๐ŸŒฆ๏ธ', '๐ŸŒง๏ธ', '๐ŸŒฉ๏ธ', '๐ŸŒจ๏ธ', '๐ŸŒซ๏ธ', 'โ˜”๏ธ', '๐ŸŒฌ๏ธ', '๐Ÿ’จ', '๐ŸŒช๏ธ', 'cute', 'kawaii', 'little']) 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 = noadd_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_itX(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) outputX = proc1(prompt_with_noise) return outputX 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 def send_it5(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) output5 = proc1(prompt_with_noise) return output5 #def send_it7(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) #output5 = proc1(prompt_with_noise) #return output0 with gr.Blocks(css='style.css') as demo: gr.HTML( """

DreamAnything

If you have an idea, put it on the first box to expand it, if you have a full prompt, you can leave the first box empty and just put it on the second one and click generate images! Noise Level: Controls how much randomness is added to the input of the boxes after the first one before it is sent to the model, so you can get 6 unique 768x768 images. Higher noise level produces more diverse outputs, while lower noise level produces similar outputs, original space created by Phenomenon1981.

โค๏ธ Press the Like Button if you enjoy my space! โค๏ธ

""" ) 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,min_width=1200 ) see_prompts = gr.Button("โœจMagicโœจ โœจPromptโœจ").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(): #Now that the first box generates a picture with noise=0 having the default at 0 makes no sense as it'd generate the same image 6 times. noise_level = gr.Slider(minimum=0.2, maximum=3, step=0.1, label="Noise Level (0.1 or less was generating the same pic 6 times! ๐Ÿคฃ)") gr.HTML( """

Please allow up to 1 minute for each image to generate, for a total of 6 minutes max.

""" ) with gr.Row(): with gr.Row(): output1=gr.Image(label="DreamAnything",show_label=False,min_width=640) output2=gr.Image(label="DreamAnything",show_label=False,min_width=640) with gr.Row(): with gr.Row(): output3=gr.Image(label="DreamAnything",show_label=False,min_width=640) output4=gr.Image(label="DreamAnything",show_label=False,min_width=640) with gr.Row(): with gr.Row(): output5=gr.Image(label="DreamAnything",show_label=False,min_width=640) outputX=gr.Image(label="DreamAnything",show_label=False,min_width=640) #with gr.Row(): #with gr.Row(): #output0=gr.Image(label="DreamAnything",show_label=False,min_width=640) 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_it7, inputs=[prompt, noise_level], outputs=[output0]) 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_itX, inputs=[prompt, noise_level], outputs=[outputX]) with gr.Row(): gr.HTML( """

Demo for DreamAnything Stable Diffusion model

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!

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