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import gradio as gr
import numpy as np
import random
import torch
from diffusers import StableDiffusionXLPipeline, AutoencoderKL
from utils import randomize_seed_fn
MAX_SEED = np.iinfo(np.int32).max
def model_load():
vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
pipe = StableDiffusionXLPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0", vae=vae, torch_dtype=torch.float16
)
# load lora weight
pipe.load_lora_weights("jjuun/vivid_color_style")
return pipe.to('cuda')
def sdxl_process(seed, prompt, additional_prompt, negative_prompt, num_steps, guidance_scale):
pipe = model_load()
generator = torch.Generator("cuda")
generator.manual_seed(seed)
special_prompt = 'jjj, scratch art style'
prompt = f'{special_prompt}, {prompt}, with a black background'
output = pipe(prompt, additional_prompt, negative_prompt=negative_prompt, num_inference_steps=num_steps, guidance_scale=guidance_scale,
generator=generator).images[0]
return output
title = "🌈 Colorful illustration"
description_en = "🚀 How to use: please make sure to include 'a colorful' in prompt and click Run button!"
def create_demo():
with gr.Blocks() as demo:
gr.Markdown(f"<h1 style='text-align: center;'>{title}</h1>")
gr.Markdown(f"<h3 style='text-align: center'>{description_en}</h3>")
with gr.Row():
with gr.Column():
prompt = gr.Textbox(label="Prompt")
run_button = gr.Button("Run")
with gr.Accordion("Advanced options", open=False):
num_steps = gr.Slider(label="Number of steps", minimum=1, maximum=100, value=20, step=1)
guidance_scale = gr.Slider(label="Guidance scale", minimum=0.1, maximum=30.0, value=9.0, step=0.1)
seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0)
randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
a_prompt = gr.Textbox(label="Additional prompt", value="")
n_prompt = gr.Textbox(
label="Negative prompt",
value="longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
)
with gr.Column():
result = gr.Image(label="Output")
result_seed = gr.Textbox(label="Used seed")
gr.Examples(
examples= [["a colorful lion", "20", "9", "0", "", "longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality", "examples/lion.png"],
["a colorful messi", "20", "9", "0", "", "longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality", "examples/messi.png"]],
inputs = [prompt, num_steps, guidance_scale, seed, a_prompt, n_prompt, result]
)
inputs = [
seed,
prompt,
a_prompt,
n_prompt,
num_steps,
guidance_scale,
]
run_button.click(
fn=randomize_seed_fn,
inputs=[seed, randomize_seed],
outputs=result_seed,
queue=False,
api_name=False,
).then(
fn=sdxl_process,
inputs=inputs,
outputs=result,
api_name=False,
)
return demo
if __name__ == "__main__":
demo = create_demo()
demo.queue().launch()
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