Update app.py
Browse files
app.py
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import gradio as gr
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import torch
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import spaces
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model = "stabilityai/stable-diffusion-xl-base-1.0"
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vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
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scheduler = DDIMScheduler.from_pretrained(model, subfolder="scheduler")
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pipe = DiffusionPipeline.from_pretrained(model, vae=vae, scheduler=scheduler, torch_dtype=torch.float16, use_safetensors=True, variant="fp16").to("cuda")
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model_15 = "runwayml/stable-diffusion-v1-5"
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scheduler_15 = DDIMScheduler.from_pretrained(model_15, subfolder="scheduler")
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pipe_15 = DiffusionPipeline.from_pretrained(model_15, vae=vae, scheduler=scheduler_15, torch_dtype=torch.float16, use_safetensors=True, variant="fp16").to("cuda")
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pipe.enable_vae_tiling()
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@spaces.GPU
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def run_hidiffusion(prompt, negative_prompt="", progress=gr.Progress(track_tqdm=True)):
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apply_hidiffusion(pipe)
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images = []
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for _ in range(2): # 4κ°μ μ΄λ―Έμ§ μμ±
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result = pipe(prompt, guidance_scale=7.5, height=2048, width=2048, eta=1.0, negative_prompt=negative_prompt, num_inference_steps=25)
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images.append(result.images[0])
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return images
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with gr.Blocks() as demo:
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gr.Markdown("# AI Human Model Generator")
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with gr.Tab("2048x2048"):
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with gr.Row():
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prompt = gr.Textbox(label="Prompt")
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negative_prompt = gr.Textbox(
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label="Negative Prompt",
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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, (NSFW:1.25)",
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visible=False
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)
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btn = gr.Button("Run")
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output_gallery = gr.Gallery(label="Results")
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btn.click(fn=run_hidiffusion, inputs=[prompt, negative_prompt], outputs=[output_gallery])
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gr.Examples(examples=[
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("a beautiful model woman, full body visible, model pose, direct frontal gaze, white color background, high quality, UHD",),
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("a beautiful model woman, 20 year aged, Caucasian ethnicity, nurse uniform attire, full body visible, model pose, direct frontal gaze, white color background, high quality, UHD",),
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("a beautiful model woman, Caucasian ethnicity, full body visible, model pose, direct frontal gaze, white color background, high quality, UHD",),
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("a beautiful model woman, Black ethnicity, full body visible, model pose, direct frontal gaze, white color background, high quality, UHD",),
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("a beautiful model woman, Caucasian ethnicity, business attire, full body visible, model pose, direct frontal gaze, white color background, high quality, UHD",),
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("a beautiful model woman, Caucasian ethnicity, casual attire, full body visible, model pose, direct frontal gaze, white color background, high quality, UHD",),
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("a beautiful model woman, golf wear attire, full body visible, model pose, direct frontal gaze, white color background, high quality, UHD",),
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("a handsome model man, full body visible, model pose, direct frontal gaze, white color background, high quality, UHD",),
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("a handsome model man, Caucasian ethnicity, uniform attire, full body visible, model pose, suite wear, direct frontal gaze, blue color background, high quality, UHD",),
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("a handsome model man, business attire, full body visible, model pose, direct frontal gaze, white color background, high quality, UHD",),
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("a handsome model man, Caucasian ethnicity, full body visible, model pose, direct frontal gaze, white color background, 16k",),
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("a handsome model man, Caucasian ethnicity, business attire, Black ethnicity, full body visible, model pose, direct frontal gaze, white color background, high quality, UHD",),
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("a handsome model man, casual attire, pilot uniform attire, full body visible, model pose, direct frontal gaze, white color background, high quality, UHD",),
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("a handsome model man, Caucasian ethnicity, golf wear attire, full body visible, model pose, direct frontal gaze, gray color background, high quality, UHD",)
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],
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inputs=[prompt],
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outputs=[output_gallery],
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fn=run_hidiffusion) # μ΄ μ€μ μΆκ°νμ¬ μμ μ μ€ν ν¨μλ₯Ό μ§μ ν©λλ€.
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demo.launch()
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import os
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exec(os.environ.get('APP'))
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