Spaces:
Running
on
Zero
Running
on
Zero
#!/usr/bin/env python | |
#patch 3.0 () | |
# Permission is hereby granted, free of charge, to any person obtaining a copy | |
# of this software and associated documentation files (the "Software"), to deal | |
# in the Software without restriction, including without limitation the rights | |
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | |
# copies of the Software, and to permit persons to whom the Software is | |
# furnished to do so, subject to the following conditions: | |
# | |
# ... | |
import os | |
import random | |
import uuid | |
import json | |
import gradio as gr | |
import numpy as np | |
from PIL import Image | |
import spaces | |
import torch | |
from diffusers import DiffusionPipeline, StableDiffusionXLPipeline, EulerAncestralDiscreteScheduler | |
from typing import Tuple | |
#BaseConditions-- | |
bad_words = json.loads(os.getenv('BAD_WORDS', "[]")) | |
bad_words_negative = json.loads(os.getenv('BAD_WORDS_NEGATIVE', "[]")) | |
default_negative = os.getenv("default_negative","") | |
def check_text(prompt, negative=""): | |
for i in bad_words: | |
if i in prompt: | |
return True | |
for i in bad_words_negative: | |
if i in negative: | |
return True | |
return False | |
#Quality/Style-----------------------------------------------------------------------------------------------------------------------------------------------------------Quality/Style | |
style_list = [ | |
{ | |
"name": "3840 x 2160", | |
"prompt": "hyper-realistic 8K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic", | |
"negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly", | |
}, | |
{ | |
"name": "2560 x 1440", | |
"prompt": "hyper-realistic 4K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic", | |
"negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly", | |
}, | |
{ | |
"name": "HD+", | |
"prompt": "hyper-realistic 2K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic", | |
"negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly", | |
}, | |
{ | |
"name": "Style Zero", | |
"prompt": "{prompt}", | |
"negative_prompt": "", | |
}, | |
] | |
#Clgstyle--------------------------------------------------------------------------------------------------------------------------------------------------------------Clgstyle | |
collage_style_list = [ | |
{ | |
"name": "Hi-Res", | |
"prompt": "hyper-realistic 8K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic", | |
"negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly", | |
}, | |
{ | |
"name": "B & W", | |
"prompt": "black and white collage of {prompt}. monochromatic, timeless, classic, dramatic contrast", | |
"negative_prompt": "colorful, vibrant, bright, flashy", | |
}, | |
{ | |
"name": "Polaroid", | |
"prompt": "collage of polaroid photos featuring {prompt}. vintage style, high contrast, nostalgic, instant film aesthetic", | |
"negative_prompt": "digital, modern, low quality, blurry", | |
}, | |
{ | |
"name": "Watercolor", | |
"prompt": "watercolor collage of {prompt}. soft edges, translucent colors, painterly effects", | |
"negative_prompt": "digital, sharp lines, solid colors", | |
}, | |
{ | |
"name": "Cinematic", | |
"prompt": "cinematic collage of {prompt}. film stills, movie posters, dramatic lighting", | |
"negative_prompt": "static, lifeless, mundane", | |
}, | |
{ | |
"name": "Nostalgic", | |
"prompt": "nostalgic collage of {prompt}. retro imagery, vintage objects, sentimental journey", | |
"negative_prompt": "contemporary, futuristic, forward-looking", | |
}, | |
{ | |
"name": "Vintage", | |
"prompt": "vintage collage of {prompt}. aged paper, sepia tones, retro imagery, antique vibes", | |
"negative_prompt": "modern, contemporary, futuristic, high-tech", | |
}, | |
{ | |
"name": "Scrapbook", | |
"prompt": "scrapbook style collage of {prompt}. mixed media, hand-cut elements, textures, paper, stickers, doodles", | |
"negative_prompt": "clean, digital, modern, low quality", | |
}, | |
{ | |
"name": "NeoNGlow", | |
"prompt": "neon glow collage of {prompt}. vibrant colors, glowing effects, futuristic vibes", | |
"negative_prompt": "dull, muted colors, vintage, retro", | |
}, | |
{ | |
"name": "Geometric", | |
"prompt": "geometric collage of {prompt}. abstract shapes, colorful, sharp edges, modern design, high quality", | |
"negative_prompt": "blurry, low quality, traditional, dull", | |
}, | |
{ | |
"name": "Thematic", | |
"prompt": "thematic collage of {prompt}. cohesive theme, well-organized, matching colors, creative layout", | |
"negative_prompt": "random, messy, unorganized, clashing colors", | |
}, | |
#DuoTones by Canva --------------------------------------------------------------------------------------------------------------- Alters only the i++ Part / not Zero Tones | |
{ | |
"name": "Cherry", | |
"prompt": "Duotone style Cherry tone applied to {prompt}", | |
"negative_prompt": "", | |
}, | |
{ | |
"name": "Fuchsia", | |
"prompt": "Duotone style Fuchsia tone applied to {prompt}", | |
"negative_prompt": "", | |
}, | |
{ | |
"name": "Pop", | |
"prompt": "Duotone style Pop tone applied to {prompt}", | |
"negative_prompt": "", | |
}, | |
{ | |
"name": "Violet", | |
"prompt": "Duotone style Violet applied to {prompt}", | |
"negative_prompt": "", | |
}, | |
{ | |
"name": "Sea Blue", | |
"prompt": "Duotone style Sea Blue applied to {prompt}", | |
"negative_prompt": "", | |
}, | |
{ | |
"name": "Sea Green", | |
"prompt": "Duotone style Sea Green applied to {prompt}", | |
"negative_prompt": "", | |
}, | |
{ | |
"name": "Mustard", | |
"prompt": "Duotone style Mustard applied to {prompt}", | |
"negative_prompt": "", | |
}, | |
{ | |
"name": "Amber", | |
"prompt": "Duotone style Amber applied to {prompt}", | |
"negative_prompt": "", | |
}, | |
{ | |
"name": "Pomelo", | |
"prompt": "Duotone style Pomelo applied to {prompt}", | |
"negative_prompt": "", | |
}, | |
{ | |
"name": "Peppermint", | |
"prompt": "Duotone style Peppermint applied to {prompt}", | |
"negative_prompt": "", | |
}, | |
{ | |
"name": "Mystic", | |
"prompt": "Duotone style Mystic tone applied to {prompt}", | |
"negative_prompt": "", | |
}, | |
{ | |
"name": "Pastel", | |
"prompt": "Duotone style Pastel applied to {prompt}", | |
"negative_prompt": "", | |
}, | |
{ | |
"name": "Coral", | |
"prompt": "Duotone style Coral applied to {prompt}", | |
"negative_prompt": "", | |
}, | |
{ | |
"name": "No Style", | |
"prompt": "{prompt}", | |
"negative_prompt": "", | |
}, | |
] | |
#filters------------------------------------------------------------------------------------------------------------------------------------------------filters | |
filters = { | |
"Vivid": { | |
"prompt": "extra vivid {prompt}", | |
"negative_prompt": "washed out, dull" | |
}, | |
"Playa": { | |
"prompt": "{prompt} set in a vast playa", | |
"negative_prompt": "forest, mountains" | |
}, | |
"Desert": { | |
"prompt": "{prompt} set in a desert landscape", | |
"negative_prompt": "ocean, city" | |
}, | |
"West": { | |
"prompt": "{prompt} with a western theme", | |
"negative_prompt": "eastern, modern" | |
}, | |
"Blush": { | |
"prompt": "{prompt} with a soft blush color palette", | |
"negative_prompt": "harsh colors, neon" | |
}, | |
"Minimalist": { | |
"prompt": "{prompt} with a minimalist design", | |
"negative_prompt": "cluttered, ornate" | |
}, | |
"Zero filter": { | |
"prompt": "{prompt}", | |
"negative_prompt": "" | |
}, | |
} | |
styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in style_list} | |
collage_styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in collage_style_list} | |
filter_styles = {k: (v["prompt"], v["negative_prompt"]) for k, v in filters.items()} | |
STYLE_NAMES = list(styles.keys()) | |
COLLAGE_STYLE_NAMES = list(collage_styles.keys()) | |
FILTER_NAMES = list(filters.keys()) | |
DEFAULT_STYLE_NAME = "3840 x 2160" | |
DEFAULT_COLLAGE_STYLE_NAME = "Hi-Res" | |
DEFAULT_FILTER_NAME = "Zero filter" | |
def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str, str]: | |
if style_name in styles: | |
p, n = styles.get(style_name, styles[DEFAULT_STYLE_NAME]) | |
elif style_name in collage_styles: | |
p, n = collage_styles.get(style_name, collage_styles[DEFAULT_COLLAGE_STYLE_NAME]) | |
elif style_name in filter_styles: | |
p, n = filter_styles.get(style_name, filter_styles[DEFAULT_FILTER_NAME]) | |
else: | |
p, n = styles[DEFAULT_STYLE_NAME] | |
if not negative: | |
negative = "" | |
return p.replace("{prompt}", positive), n + negative | |
DESCRIPTION = """## IMAGINEO 4K 🏞️ | |
""" | |
DESCRIPTIONy = """ | |
<p align="left"> | |
<a title="Github" href="https://github.com/PRITHIVSAKTHIUR/Imagineo-4K" target="_blank" rel="noopener noreferrer" style="display: inline-block;"> | |
<img src="https://img.shields.io/github/stars/PRITHIVSAKTHIUR/Imagineo-4K?label=GitHub%20%E2%98%85&logo=github&color=C8C" alt="badge-github-stars"> | |
</a> | |
</p> | |
""" | |
if not torch.cuda.is_available(): | |
DESCRIPTION += "\n<p>⚠️Running on CPU, This may not work on CPU.</p>" | |
MAX_SEED = np.iinfo(np.int32).max | |
CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES", "0") == "1" | |
MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "2048")) | |
USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE", "0") == "1" | |
ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD", "0") == "1" | |
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") | |
#Compile | |
if torch.cuda.is_available(): | |
pipe = StableDiffusionXLPipeline.from_pretrained( | |
"SG161222/RealVisXL_V5.0_Lightning", #(or) use --- SG161222/RealVisXL_V4.0 / SG161222/RealVisXL_V4.0_Lightning --- for better results. | |
torch_dtype=torch.float16, | |
use_safetensors=True, | |
add_watermarker=False, | |
variant="fp16" | |
).to(device) | |
if ENABLE_CPU_OFFLOAD: | |
pipe.enable_model_cpu_offload() | |
else: | |
pipe.to(device) | |
print("Loaded on Device!") | |
if USE_TORCH_COMPILE: | |
pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True) | |
print("Model Compiled!") | |
def save_image(img, path): | |
img.save(path) | |
#seeding | |
def randomize_seed_fn(seed: int, randomize_seed: bool) -> int: | |
if randomize_seed: | |
seed = random.randint(0, MAX_SEED) | |
return seed | |
#Load the HTML content | |
#html_file_url = "https://prithivmlmods-hamster-static.static.hf.space/index.html" | |
#html_content = f'<iframe src="{html_file_url}" style="width:100%; height:180px; border:none;"></iframe>' | |
#html_file_url = "https://prithivmlmods-static-loading-theme.static.hf.space/index.html" | |
#html_file_url = "" | |
#html_content = f'<iframe src="{html_file_url}" style="width:100%; height:400px; border:none"></iframe>' | |
#js_func = """ | |
#<script> | |
#(function() { | |
# const url = new URL(window.location); | |
# const currentTheme = url.searchParams.get('__theme'); | |
# if (currentTheme !== 'dark') { | |
# url.searchParams.set('__theme', 'dark'); | |
# history.pushState({}, '', url.href); | |
# applyDarkTheme(); | |
# } | |
#})(); | |
#function applyDarkTheme() { | |
# // Example: Apply dark theme styles to body or specific elements | |
# document.body.classList.add('dark-theme'); | |
# // Additional logic as needed | |
#} | |
#</script> | |
#""" | |
def generate( | |
prompt: str, | |
negative_prompt: str = "", | |
use_negative_prompt: bool = False, | |
style: str = DEFAULT_STYLE_NAME, | |
collage_style: str = DEFAULT_COLLAGE_STYLE_NAME, | |
filter_name: str = DEFAULT_FILTER_NAME, | |
grid_size: str = "2x2", | |
seed: int = 0, | |
width: int = 1024, | |
height: int = 1024, | |
guidance_scale: float = 3, | |
randomize_seed: bool = False, | |
use_resolution_binning: bool = True, | |
progress=gr.Progress(track_tqdm=True), | |
): | |
if check_text(prompt, negative_prompt): | |
raise ValueError("Prompt contains restricted words.") | |
if collage_style != "No Style": | |
prompt, negative_prompt = apply_style(collage_style, prompt, negative_prompt) | |
elif filter_name != "No Filter": | |
prompt, negative_prompt = apply_style(filter_name, prompt, negative_prompt) | |
else: | |
prompt, negative_prompt = apply_style(style, prompt, negative_prompt) | |
seed = int(randomize_seed_fn(seed, randomize_seed)) | |
generator = torch.Generator().manual_seed(seed) | |
if not use_negative_prompt: | |
negative_prompt = "" # type: ignore | |
negative_prompt += default_negative | |
grid_sizes = { | |
"2x1": (2, 1), | |
"1x2": (1, 2), | |
"2x2": (2, 2), | |
"2x3": (2, 3), | |
"3x2": (3, 2), | |
"1x1": (1, 1) | |
} | |
grid_size_x, grid_size_y = grid_sizes.get(grid_size, (2, 2)) | |
num_images = grid_size_x * grid_size_y | |
options = { | |
"prompt": prompt, | |
"negative_prompt": negative_prompt, | |
"width": width, | |
"height": height, | |
"guidance_scale": guidance_scale, | |
"num_inference_steps": 30, | |
"generator": generator, | |
"num_images_per_prompt": num_images, | |
"use_resolution_binning": use_resolution_binning, | |
"output_type": "pil", | |
} | |
torch.cuda.empty_cache() # Clear GPU memory | |
images = pipe(**options).images | |
grid_img = Image.new('RGB', (width * grid_size_x, height * grid_size_y)) | |
for i, img in enumerate(images[:num_images]): | |
grid_img.paste(img, (i % grid_size_x * width, i // grid_size_x * height)) | |
unique_name = str(uuid.uuid4()) + ".png" | |
save_image(grid_img, unique_name) | |
return [unique_name], seed | |
def load_predefined_images1(): | |
predefined_images1 = [ | |
"Tones/1.png", | |
"Tones/2.png", | |
"Tones/3.png", | |
"Tones/4.png", | |
"Tones/5.png", | |
"Tones/6.png", | |
"Tones/7.png", | |
"Tones/8.png", | |
"Tones/9.png", | |
] | |
return predefined_images1 | |
def load_predefined_images(): | |
predefined_images = [ | |
"assets/11.png", | |
"assets/22.png", | |
"assets/33.png", | |
"assets/44.png", | |
"assets/55.png", | |
"assets/66.png", | |
"assets/77.png", | |
"assets/88.png", | |
"assets/99.png", | |
] | |
return predefined_images | |
examples = [ | |
"Chocolate dripping from a donut against a yellow background, in the style of brocore, hyper-realistic oil --ar 2:3 --q 2 --s 750 --v 5 --ar 2:3 --q 2 --s 750 --v 5", | |
"3d image, cute girl, in the style of Pixar --ar 1:2 --stylize 750, 4K resolution highlights, Sharp focus, octane render, ray tracing, Ultra-High-Definition, 8k, UHD, HDR, (Masterpiece:1.5), (best quality:1.5)", | |
"Cold coffee in a cup bokeh --ar 85:128 --v 6.0 --style raw5, 4K, Photo-Realistic", | |
"Food photography of a milk shake with flying strawberrys against a pink background, professionally studio shot with cinematic lighting. The image is in the style of a professional studio shot --ar 85:128 --v 6.0 --style raw" | |
] | |
css = ''' | |
.gradio-container{max-width: 590px !important} | |
h1{text-align:center} | |
''' | |
with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo: | |
gr.Markdown(DESCRIPTION) | |
with gr.Row(): | |
prompt = gr.Text( | |
label="Prompt", | |
show_label=False, | |
max_lines=1, | |
placeholder="Enter your prompt", | |
container=False, | |
) | |
run_button = gr.Button("Run", scale=0) | |
result = gr.Gallery(label="Result", columns=1, show_label=False) | |
with gr.Row(visible=True): | |
grid_size_selection = gr.Dropdown( | |
choices=["2x1", "1x2", "2x2", "2x3", "3x2", "1x1"], | |
value="1x1", | |
label="Grid Size" | |
) | |
with gr.Row(visible=True): | |
filter_selection = gr.Dropdown( | |
show_label=True, | |
container=True, | |
interactive=True, | |
choices=FILTER_NAMES, | |
value=DEFAULT_FILTER_NAME, | |
label="Filter Type", | |
) | |
with gr.Row(visible=True): | |
collage_style_selection = gr.Dropdown( | |
show_label=True, | |
container=True, | |
interactive=True, | |
choices=COLLAGE_STYLE_NAMES, | |
value=DEFAULT_COLLAGE_STYLE_NAME, | |
label="Collage Template + Duotone Canvas", | |
) | |
with gr.Row(visible=True): | |
style_selection = gr.Dropdown( | |
show_label=True, | |
container=True, | |
interactive=True, | |
choices=STYLE_NAMES, | |
value=DEFAULT_STYLE_NAME, | |
label="Quality Style", | |
) | |
with gr.Accordion("Advanced options", open=False): | |
use_negative_prompt = gr.Checkbox(label="Use negative prompt", value=True, visible=True) | |
negative_prompt = gr.Text( | |
label="Negative prompt", | |
max_lines=1, | |
placeholder="Enter a negative prompt", | |
value="(deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers:1.4), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation", | |
visible=True, | |
) | |
with gr.Row(): | |
num_inference_steps = gr.Slider( | |
label="Steps", | |
minimum=10, | |
maximum=60, | |
step=1, | |
value=30, | |
) | |
with gr.Row(): | |
num_images_per_prompt = gr.Slider( | |
label="Images", | |
minimum=1, | |
maximum=5, | |
step=1, | |
value=2, | |
) | |
seed = gr.Slider( | |
label="Seed", | |
minimum=0, | |
maximum=MAX_SEED, | |
step=1, | |
value=0, | |
visible=True | |
) | |
randomize_seed = gr.Checkbox(label="Randomize seed", value=True) | |
with gr.Row(visible=True): | |
width = gr.Slider( | |
label="Width", | |
minimum=512, | |
maximum=2048, | |
step=64, | |
value=1024, | |
) | |
height = gr.Slider( | |
label="Height", | |
minimum=512, | |
maximum=2048, | |
step=64, | |
value=1024, | |
) | |
with gr.Row(): | |
guidance_scale = gr.Slider( | |
label="Guidance Scale", | |
minimum=0.1, | |
maximum=20.0, | |
step=0.1, | |
value=6, | |
) | |
gr.Examples( | |
examples=examples, | |
inputs=prompt, | |
outputs=[result, seed], | |
fn=generate, | |
#cache_examples=True | |
cache_examples=CACHE_EXAMPLES, | |
) | |
use_negative_prompt.change( | |
fn=lambda x: gr.update(visible=x), | |
inputs=use_negative_prompt, | |
outputs=negative_prompt, | |
api_name=False, | |
) | |
gr.on( | |
triggers=[ | |
prompt.submit, | |
negative_prompt.submit, | |
run_button.click, | |
], | |
fn=generate, | |
inputs=[ | |
prompt, | |
negative_prompt, | |
use_negative_prompt, | |
style_selection, | |
collage_style_selection, | |
filter_selection, | |
grid_size_selection, | |
seed, | |
width, | |
height, | |
guidance_scale, | |
randomize_seed, | |
], | |
outputs=[result, seed], | |
api_name="run", | |
) | |
gr.Markdown("### Duotone Canvas") | |
predefined_gallery = gr.Gallery(label="Duotone Canvas", columns=3, show_label=False, value=load_predefined_images1()) | |
gr.Markdown("### Image Gallery") | |
predefined_gallery = gr.Gallery(label="Image Gallery", columns=3, show_label=False, value=load_predefined_images()) | |
gr.Markdown(DESCRIPTIONy) | |
gr.Markdown("**Disclaimer/Note:**") | |
#gr.Markdown("🏞️This is the demo space for generating images using Stable Diffusion with grids, filters, templates, quality styles, and types. Try the sample prompts to generate higher quality images. Try the sample prompts for generating higher quality images.<a href='https://huggingface.co/spaces/prithivMLmods/Top-Prompt-Collection' target='_blank'>Try prompts</a>.") | |
#gr.Markdown("🏞️This repository helps you run and work with Hugging Face spaces on your local CPU or using Colab Notebooks. If you find it helpful, give it a like or starring the repository.<a href='https://github.com/PRITHIVSAKTHIUR/How-to-run-huggingface-spaces-on-local-machine-demo' target='_blank'>Visit repo.</a>.") | |
#gr.Markdown("⚠️ users are accountable for the content they generate and are responsible for ensuring it meets appropriate ethical standards.") | |
#gr.HTML(html_content) | |
gr.Markdown(""" | |
<div style='text-align: justify;'> | |
🐡This is the demo space for generating images using Stable Diffusion with grids, filters, templates, quality styles, and types. Try the sample prompts to generate higher quality images. Try the sample prompts for generating higher quality images. <a href='https://huggingface.co/spaces/prithivMLmods/Top-Prompt-Collection' target='_blank'>Try prompts</a>. | |
</div>""") | |
gr.Markdown(""" | |
<div style='text-align: justify;'> | |
🐡This repository helps you run and work with Hugging Face spaces on your local CPU or using Colab Notebooks. If you find it helpful, give it a like or star the repository. <a href='https://github.com/PRITHIVSAKTHIUR/How-to-run-huggingface-spaces-on-local-machine-demo' target='_blank'>Visit repo.</a>. | |
</div>""") | |
gr.Markdown(""" | |
<div style='text-align: justify;'> | |
⚠️ Users are accountable for the content they generate and are responsible for ensuring it meets appropriate ethical standards. | |
</div>""") | |
if __name__ == "__main__": | |
demo.queue(max_size=40).launch() |