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#!/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 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 | |
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() | |