LastUpdated10.07.2024.txt

#!/usr/bin/env python
#patch 2.0 ()
# 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
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


#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>
#"""


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": "",
    },
    
]

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",
    },

    {
        "name": "No Style",
        "prompt": "{prompt}",
        "negative_prompt": "",
    },
    
]

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 = "Vivid"

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 = DiffusionPipeline.from_pretrained(
        "SG161222/RealVisXL_V4.0",
        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

@spaces.GPU(enable_queue=True)
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": 20,
        "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_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 = [

    "Portrait of a beautiful woman in a hat, summer outfit, with freckles on her face, in a close up shot, with sunlight, outdoors, in soft light, with a beach background, looking at the camera, with high resolution photography, in the style of Hasselblad X2D50c --ar 85:128 --v 6.0 --style raw",
    "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",
    "Closeup of blonde woman depth of field, bokeh, shallow focus, minimalism, fujifilm xh2s with Canon EF lens, cinematic --ar 85:128 --v 6.0 --style raw"
]

css = '''
.gradio-container{max-width: 600px !important}
h1{text-align:center}
'''

#with gr.Blocks(css=css, theme="bethecloud/storj_theme", js=js_func) as demo:
with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
#with gr.Blocks(css=css, theme="Nymbo/Alyx_Theme") as demo:
    gr.Markdown(DESCRIPTION)
    gr.DuplicateButton(
        value="Duplicate Space for private use",
        elem_id="duplicate-button",
        visible=os.getenv("SHOW_DUPLICATE_BUTTON") == "1",
    )
    with gr.Group():
        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")
        result = gr.Gallery(label="Grid", columns=1, preview=True)

    
    with gr.Row(visible=True):
        grid_size_selection = gr.Dropdown(
            choices=["2x1", "1x2", "2x2", "2x3", "3x2", "1x1"],
            value="2x2",
            label="Grid Size"
        )

    with gr.Row(visible=True):
        filter_selection = gr.Radio(
            show_label=True,
            container=True,
            interactive=True,
            choices=FILTER_NAMES,
            value=DEFAULT_FILTER_NAME,
            label="Filter Type",
        )

    with gr.Row(visible=True):
        style_selection = gr.Radio(
            show_label=True,
            container=True,
            interactive=True,
            choices=STYLE_NAMES,
            value=DEFAULT_STYLE_NAME,
            label="Quality Style",
        )

    with gr.Row(visible=True):
        collage_style_selection = gr.Radio(
            show_label=True,
            container=True,
            interactive=True,
            choices=COLLAGE_STYLE_NAMES,
            value=DEFAULT_COLLAGE_STYLE_NAME,
            label="Collage Template",
        )

    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=30,
                step=1,
                value=15,
            )
        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=8,
                value=1024,
            )
            height = gr.Slider(
                label="Height",
                minimum=512,
                maximum=2048,
                step=8,
                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",
    )
    # Adding a predefined gallery section
    gr.Markdown("### Generated Images")
    predefined_gallery = gr.Gallery(label="Generated Images", columns=3, show_label=False, value=load_predefined_images())

    #gr.Markdown("⚠️ responsible for ensuring it meets appropriate ethical standards")
    gr.Markdown(DESCRIPTIONy)

    # Adding a disclaimer
    gr.Markdown("**Disclaimer:**")
    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("**Local or Colab ??:**")
    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("**Note:**")
    gr.Markdown("⚠️ users are accountable for the content they generate and are responsible for ensuring it meets appropriate ethical standards.")
    #gr.HTML(html_content)

    
if __name__ == "__main__":
    demo.queue(max_size=40).launch()