PBRealistic / app.py
waqashayder's picture
xx
84fe0bd verified
#!/usr/bin/env python
#patch 0.04
#Func() Dalle Collage Moved Midjourney Space
#Pruned DalleCollage Space
import os
import random
import uuid
import json
import torch
print(f"Is CUDA available: {torch.cuda.is_available()}")
# True
print(f"CUDA device: {torch.cuda.get_device_name(torch.cuda.current_device())}")
# Tesla T4
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
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 = """## MidJourney
Drop your best results in the community: [rb.gy/klkbs7](http://rb.gy/klkbs7), Have you tried the stable hamster space? [rb.gy/hfrm2f](http://rb.gy/hfrm2f)
"""
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")
if torch.cuda.is_available():
pipe = DiffusionPipeline.from_pretrained(
"----you model goes here-----",
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)
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
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: 670px !important}
h1{text-align:center}
'''
with gr.Blocks(css=css, theme="bethecloud/storj_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):
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.Row(visible=True):
grid_size_selection = gr.Dropdown(
choices=["2x1", "1x2", "2x2", "2x3", "3x2", "1x1"],
value="2x2",
label="Grid Size"
)
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",
)
if __name__ == "__main__":
demo.queue(max_size=20).launch()