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#!/usr/bin/env python
#patch 0.01 ()
# 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
from typing import Tuple
import gradio as gr
import numpy as np
from PIL import Image
import spaces
import torch
from diffusers import StableDiffusionXLPipeline, EulerAncestralDiscreteScheduler
DESCRIPTIONz= """## EPIC REALISM 🙀
"""
DESCRIPTIONy = """
<p align="left">
<a title="Github" href="https://github.com/PRITHIVSAKTHIUR/Canopus-Realism" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
<img src="https://img.shields.io/github/stars/PRITHIVSAKTHIUR/Canopus-Realism?label=GitHub%20%E2%98%85&logo=github&color=C8C" alt="badge-github-stars">
</a>
</p>
"""
def save_image(img):
unique_name = str(uuid.uuid4()) + ".png"
img.save(unique_name)
return unique_name
def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
if randomize_seed:
seed = random.randint(0, MAX_SEED)
return seed
MAX_SEED = np.iinfo(np.int32).max
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
USE_TORCH_COMPILE = 0
ENABLE_CPU_OFFLOAD = 0
if torch.cuda.is_available():
pipe = StableDiffusionXLPipeline.from_pretrained(
"SG161222/RealVisXL_V4.0_Lightning",
torch_dtype=torch.float16,
use_safetensors=True,
)
pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
pipe.load_lora_weights("prithivMLmods/Canopus-Realism-LoRA", weight_name="Canopus-Realism-LoRA.safetensors", adapter_name="rlms")
pipe.set_adapters("rlms")
pipe.to("cuda")
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": "",
},
]
styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in style_list}
DEFAULT_STYLE_NAME = "3840 x 2160"
STYLE_NAMES = list(styles.keys())
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])
else:
p, n = styles[DEFAULT_STYLE_NAME]
if not negative:
negative = ""
return p.replace("{prompt}", positive), n + negative
@spaces.GPU(duration=60, enable_queue=True)
def generate(
prompt: str,
negative_prompt: str = "",
use_negative_prompt: bool = False,
seed: int = 0,
width: int = 1024,
height: int = 1024,
guidance_scale: float = 3,
randomize_seed: bool = False,
style_name: str = DEFAULT_STYLE_NAME,
progress=gr.Progress(track_tqdm=True),
):
seed = int(randomize_seed_fn(seed, randomize_seed))
positive_prompt, effective_negative_prompt = apply_style(style_name, prompt, negative_prompt)
if not use_negative_prompt:
effective_negative_prompt = "" # type: ignore
images = pipe(
prompt=positive_prompt,
negative_prompt=effective_negative_prompt,
width=width,
height=height,
guidance_scale=guidance_scale,
num_inference_steps=20,
num_images_per_prompt=1,
cross_attention_kwargs={"scale": 0.65},
output_type="pil",
).images
image_paths = [save_image(img) for img in images]
print(image_paths)
return image_paths, seed
examples = [
"A man dressed in sunglasses and brown jacket, in the style of cypherpunk, timeless beauty, exacting precision, uhd image, aleksandr deyneka, matte background, leather/hide --ar 67:101 --v 5",
"A black suit with black and white stripes, in the style of claire-obscure lighting, realistic genre scenes, light amber and violet, portraits with soft lighting, photo-realistic, cinematic lighting, hyper-realistic pop --ar 51:64 --v 5.2"
]
css = '''
.gradio-container{max-width: 545px !important}
h1{text-align:center}
footer {
visibility: hidden
}
'''
def load_predefined_images():
predefined_images = [
"assets/3.png",
"assets/4.png",
"assets/5.png",
"assets/6.png",
"assets/7.png",
"assets/8.png",
"assets/9.png",
"assets/10.png",
"assets/11.png",
]
return predefined_images
with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
gr.Markdown(DESCRIPTIONz)
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", scale=0)
result = gr.Gallery(label="Result", columns=1, preview=True, show_label=False)
with gr.Accordion("Advanced options", open=False, visible=False):
use_negative_prompt = gr.Checkbox(label="Use negative prompt", value=True)
negative_prompt = gr.Text(
label="Negative prompt",
lines=4,
max_lines=6,
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",
placeholder="Enter a negative prompt",
visible=True,
)
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=3.0,
)
style_selection = gr.Radio(
show_label=True,
container=True,
interactive=True,
choices=STYLE_NAMES,
value=DEFAULT_STYLE_NAME,
label="Quality Style",
)
gr.Examples(
examples=examples,
inputs=prompt,
outputs=[result, seed],
fn=generate,
cache_examples=False,
)
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,
seed,
width,
height,
guidance_scale,
randomize_seed,
style_selection,
],
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)
gr.Markdown("**Disclaimer:**")
gr.Markdown("This space provides realistic image generation, which works better for human faces and portraits. Realistic trigger works properly, better for photorealistic trigger words, close-up shots, face diffusion, male, female characters.")
gr.Markdown("**Note:**")
gr.Markdown("⚠️users are accountable for the content they generate and are responsible for ensuring it meets appropriate ethical standards.")
if __name__ == "__main__":
demo.queue(max_size=40).launch()