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import gradio as gr |
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import numpy as np |
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import random |
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import torch |
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from diffusers import StableDiffusionXLPipeline, AutoencoderKL, EulerAncestralDiscreteScheduler |
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from utils import randomize_seed_fn |
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MAX_SEED = np.iinfo(np.int32).max |
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def model_load(): |
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vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16) |
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pipe = StableDiffusionXLPipeline.from_pretrained( |
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"stabilityai/stable-diffusion-xl-base-1.0", vae=vae, torch_dtype=torch.float16 |
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) |
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pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config) |
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pipe.load_lora_weights("jjuun/vivid_color_style") |
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return pipe.to('cuda') |
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def sdxl_process(seed, prompt, additional_prompt, negative_prompt, num_steps, guidance_scale): |
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pipe = model_load() |
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generator = torch.Generator("cuda") |
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generator.manual_seed(int(seed)) |
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special_prompt = 'jjj, scratch art style' |
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prompt = f'{special_prompt}, {prompt}, with a black background' |
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output = pipe(prompt, additional_prompt, negative_prompt=negative_prompt, num_inference_steps=num_steps, guidance_scale=guidance_scale, |
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generator=generator).images[0] |
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return output |
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title = "🌈 Colorful illustration" |
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description_en = "🚀 How to use: please make sure to include 'a colorful' in prompt and click Run button!" |
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def create_demo(): |
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with gr.Blocks() as demo: |
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gr.Markdown(f"<h1 style='text-align: center;'>{title}</h1>") |
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gr.Markdown(f"<h3 style='text-align: center'>{description_en}</h3>") |
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gr.Markdown(f"<a href='https://github.com/jjuun0'><img src='https://img.shields.io/badge/GitHub-181717?style=flat-square&logo=GitHub&logoColor=white'/></a>") |
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with gr.Row(): |
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with gr.Column(): |
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prompt = gr.Textbox(label="Prompt") |
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run_button = gr.Button("Run") |
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with gr.Accordion("Advanced options", open=False): |
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num_steps = gr.Slider(label="Number of steps", minimum=1, maximum=100, value=20, step=1) |
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guidance_scale = gr.Slider(label="Guidance scale", minimum=0.1, maximum=30.0, value=9.0, step=0.1) |
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seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0) |
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randomize_seed = gr.Checkbox(label="Randomize seed", value=True) |
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a_prompt = gr.Textbox(label="Additional prompt", value="") |
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n_prompt = gr.Textbox( |
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label="Negative prompt", |
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value="", |
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) |
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with gr.Column(): |
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result = gr.Image(label="Output") |
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result_seed = gr.Textbox(label="Used seed") |
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gr.Examples( |
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examples= [["a colorful fox", "20", "9", "0", "", "", "examples/fox.png"], |
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["a colorful messi", "20", "9", "191251724", "", "", "examples/messi.png"], |
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["a colorful pyramid", "20", "9", "0", "", "", "examples/pyramid.png"], |
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["a colorful octopus playing violin", "20", "9", "0", "", "", "examples/octopus.png"]], |
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inputs = [prompt, num_steps, guidance_scale, seed, a_prompt, n_prompt, result] |
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) |
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inputs = [ |
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seed, |
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prompt, |
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a_prompt, |
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n_prompt, |
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num_steps, |
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guidance_scale, |
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] |
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run_button.click( |
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fn=randomize_seed_fn, |
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inputs=[seed, randomize_seed], |
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outputs=result_seed, |
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queue=False, |
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api_name=False, |
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).then( |
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fn=sdxl_process, |
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inputs=inputs, |
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outputs=result, |
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api_name=False, |
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) |
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return demo |
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if __name__ == "__main__": |
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demo = create_demo() |
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demo.queue().launch() |
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