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Parent(s):
Duplicate from phenomenon1981/DreamlikeArt-PhotoReal-2.0
Browse filesCo-authored-by: Dee Jay <phenomenon1981@users.noreply.huggingface.co>
- .gitattributes +34 -0
- README.md +19 -0
- app.py +158 -0
- requirements.txt +4 -0
- style.css +84 -0
.gitattributes
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README.md
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---
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title: DreamlikeArt-PhotoReal 2.0
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emoji: 🧘🏻♀️
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colorFrom: blue
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colorTo: yellow
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sdk: gradio
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sdk_version: 3.16.1
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app_file: app.py
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pinned: false
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duplicated_from: phenomenon1981/DreamlikeArt-PhotoReal-2.0
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---
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---
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title: DreamlikeArt-PhotoReal 2.0
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emoji: 🧘🏻♀️
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colorFrom: blue
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colorTo: yellow
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sdk: gradio
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sdk_version: 3.16.1
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app_file: app.py
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app.py
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import gradio as gr
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import os
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import sys
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from pathlib import Path
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import random
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import string
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import time
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from queue import Queue
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from threading import Thread
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import emoji
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text_gen=gr.Interface.load("spaces/phenomenon1981/MagicPrompt-Stable-Diffusion")
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def get_prompts(prompt_text):
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if prompt_text:
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return text_gen("photo, " + prompt_text)
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else:
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return text_gen("")
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proc1=gr.Interface.load("models/dreamlike-art/dreamlike-photoreal-2.0")
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def restart_script_periodically():
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while True:
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random_time = random.randint(540, 600)
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time.sleep(random_time)
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os.execl(sys.executable, sys.executable, *sys.argv)
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restart_thread = Thread(target=restart_script_periodically, daemon=True)
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restart_thread.start()
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queue = Queue()
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queue_threshold = 100
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def add_random_noise(prompt, noise_level=0.00):
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if noise_level == 0:
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noise_level = 0.00
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percentage_noise = noise_level * 5
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num_noise_chars = int(len(prompt) * (percentage_noise/100))
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noise_indices = random.sample(range(len(prompt)), num_noise_chars)
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prompt_list = list(prompt)
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noise_chars = list(string.ascii_letters + string.punctuation + ' ' + string.digits)
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noise_chars.extend(['😍', '💩', '😂', '🤔', '😊', '🤗', '😭', '🙄', '😷', '🤯', '🤫', '🥴', '😴', '🤩', '🥳', '😔', '😩', '🤪', '😇', '🤢', '😈', '👹', '👻', '🤖', '👽', '💀', '🎃', '🎅', '🎄', '🎁', '🎂', '🎉', '🎈', '🎊', '🎮', '❤️', '💔', '💕', '💖', '💗', '🐶', '🐱', '🐭', '🐹', '🦊', '🐻', '🐨', '🐯', '🦁', '🐘', '🔥', '🌧️', '🌞', '🌈', '💥', '🌴', '🌊', '🌺', '🌻', '🌸', '🎨', '🌅', '🌌', '☁️', '⛈️', '❄️', '☀️', '🌤️', '⛅️', '🌥️', '🌦️', '🌧️', '🌩️', '🌨️', '🌫️', '☔️', '🌬️', '💨', '🌪️', '🌈'])
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for index in noise_indices:
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prompt_list[index] = random.choice(noise_chars)
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return "".join(prompt_list)
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def send_it1(inputs, noise_level, proc1=proc1):
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prompt_with_noise = add_random_noise(inputs, noise_level)
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while queue.qsize() >= queue_threshold:
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time.sleep(2)
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queue.put(prompt_with_noise)
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output1 = proc1(prompt_with_noise)
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return output1
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def send_it2(inputs, noise_level, proc1=proc1):
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prompt_with_noise = add_random_noise(inputs, noise_level)
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while queue.qsize() >= queue_threshold:
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time.sleep(2)
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queue.put(prompt_with_noise)
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output2 = proc1(prompt_with_noise)
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return output2
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#def send_it3(inputs, noise_level, proc1=proc1):
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#prompt_with_noise = add_random_noise(inputs, noise_level)
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#while queue.qsize() >= queue_threshold:
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#time.sleep(2)
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#queue.put(prompt_with_noise)
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#output3 = proc1(prompt_with_noise)
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#return output3
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#def send_it4(inputs, noise_level, proc1=proc1):
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#prompt_with_noise = add_random_noise(inputs, noise_level)
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#while queue.qsize() >= queue_threshold:
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#time.sleep(2)
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#queue.put(prompt_with_noise)
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#output4 = proc1(prompt_with_noise)
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#return output4
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with gr.Blocks(css='style.css') as demo:
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gr.HTML(
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"""
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<div style="text-align: center; max-width: 650px; margin: 0 auto;">
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<div>
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<h1 style="font-weight: 900; font-size: 3rem; margin-bottom:20px;">
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Dreamlike Photoreal 2.0
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</h1>
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</div>
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<p style="margin-bottom: 10px; font-size: 96%">
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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,
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<a href="https://twitter.com/DavidJohnstonxx/">created by Phenomenon1981</a>.
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</p>
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<p style="margin-bottom: 10px; font-size: 98%">
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❤️ Press the Like Button if you enjoy my space! ❤️</a>
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</p>
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</div>
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"""
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)
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with gr.Column(elem_id="col-container"):
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with gr.Row(variant="compact"):
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input_text = gr.Textbox(
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label="Short Prompt",
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show_label=False,
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max_lines=2,
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placeholder="Enter a basic idea and click 'Magic Prompt'. Got no ideas? No problem, Simply just hit the magic button!",
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).style(
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container=False,
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)
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see_prompts = gr.Button("✨ Magic Prompt ✨").style(full_width=False)
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with gr.Row(variant="compact"):
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prompt = gr.Textbox(
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label="Enter your prompt",
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show_label=False,
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max_lines=2,
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placeholder="Full Prompt",
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).style(
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container=False,
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)
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run = gr.Button("Generate Images").style(full_width=False)
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with gr.Row():
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with gr.Row():
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noise_level = gr.Slider(minimum=0.0, maximum=3, step=0.1, label="Noise Level")
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with gr.Row():
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with gr.Row():
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output1=gr.Image(label="Dreamlike-photoreal-2.0",show_label=False)
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output2=gr.Image(label="Dreamlike-photoreal-2.0",show_label=False)
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#with gr.Row():
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#output1=gr.Image()
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see_prompts.click(get_prompts, inputs=[input_text], outputs=[prompt], queue=False)
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run.click(send_it1, inputs=[prompt, noise_level], outputs=[output1])
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run.click(send_it2, inputs=[prompt, noise_level], outputs=[output2])
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with gr.Row():
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gr.HTML(
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"""
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<div class="footer">
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<p> Demo for <a href="https://huggingface.co/dreamlike-art/dreamlike-photoreal-2.0">Dreamlike Photoreal 2.0</a> Stable Diffusion model
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</p>
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</div>
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<div class="acknowledgments" style="font-size: 115%">
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<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!
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</p>
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</div>
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"""
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)
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demo.launch(enable_queue=True, inline=True)
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block.queue(concurrency_count=100)
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requirements.txt
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accelerate==0.12.0
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gradio
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xformers
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emoji
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style.css
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#col-container {
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max-width: 800px;
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margin-left: auto;
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margin-right: auto;
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}
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a {
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color: inherit;
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text-decoration: underline;
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}
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.gradio-container {
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font-family: 'IBM Plex Sans', sans-serif;
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}
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.gr-button {
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color: white;
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border-color: #9d66e5;
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background: #9d66e5;
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}
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input[type='range'] {
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accent-color: #9d66e5;
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}
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.dark input[type='range'] {
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accent-color: #dfdfdf;
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}
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.container {
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max-width: 800px;
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margin: auto;
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padding-top: 1.5rem;
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}
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#gallery {
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min-height: 22rem;
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margin-bottom: 15px;
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margin-left: auto;
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margin-right: auto;
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border-bottom-right-radius: .5rem !important;
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border-bottom-left-radius: .5rem !important;
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}
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#gallery>div>.h-full {
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min-height: 20rem;
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}
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.details:hover {
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text-decoration: underline;
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}
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.gr-button {
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white-space: nowrap;
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}
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.gr-button:focus {
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border-color: rgb(147 197 253 / var(--tw-border-opacity));
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outline: none;
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49 |
+
box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000);
|
50 |
+
--tw-border-opacity: 1;
|
51 |
+
--tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color);
|
52 |
+
--tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color);
|
53 |
+
--tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity));
|
54 |
+
--tw-ring-opacity: .5;
|
55 |
+
}
|
56 |
+
#advanced-options {
|
57 |
+
margin-bottom: 20px;
|
58 |
+
}
|
59 |
+
.footer {
|
60 |
+
margin-bottom: 45px;
|
61 |
+
margin-top: 35px;
|
62 |
+
text-align: center;
|
63 |
+
border-bottom: 1px solid #e5e5e5;
|
64 |
+
}
|
65 |
+
.footer>p {
|
66 |
+
font-size: .8rem;
|
67 |
+
display: inline-block;
|
68 |
+
padding: 0 10px;
|
69 |
+
transform: translateY(10px);
|
70 |
+
background: white;
|
71 |
+
}
|
72 |
+
.dark .logo{ filter: invert(1); }
|
73 |
+
.dark .footer {
|
74 |
+
border-color: #303030;
|
75 |
+
}
|
76 |
+
.dark .footer>p {
|
77 |
+
background: #0b0f19;
|
78 |
+
}
|
79 |
+
.acknowledgments h4{
|
80 |
+
margin: 1.25em 0 .25em 0;
|
81 |
+
font-weight: bold;
|
82 |
+
font-size: 115%;
|
83 |
+
}
|
84 |
+
|