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Create app.py
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app.py
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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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from diffusers import DiffusionPipeline
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from rembg import remove
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import torch
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# ===== 初始化模型 =====
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device = "cuda" if torch.cuda.is_available() else "cpu"
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MAX_SEED = np.iinfo(np.int32).max
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MAX_IMAGE_SIZE = 1024
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if torch.cuda.is_available():
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pipe = DiffusionPipeline.from_pretrained(
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"stabilityai/sdxl-turbo",
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torch_dtype=torch.float16,
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variant="fp16",
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use_safetensors=True
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)
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pipe.enable_xformers_memory_efficient_attention()
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pipe = pipe.to(device)
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else:
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pipe = DiffusionPipeline.from_pretrained(
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"stabilityai/sdxl-turbo",
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use_safetensors=True
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)
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pipe = pipe.to(device)
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# ===== 功能函數 =====
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def generate_anime(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
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if randomize_seed:
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seed = random.randint(0, MAX_SEED)
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generator = torch.Generator().manual_seed(seed)
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image = pipe(
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prompt=f"{prompt}, Anime",
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negative_prompt=negative_prompt,
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guidance_scale=guidance_scale,
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num_inference_steps=num_inference_steps,
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width=width,
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height=height,
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generator=generator
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).images[0]
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return image
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def remove_background(input_img):
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if input_img is None:
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return None
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return remove(input_img)
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# ===== Gradio 介面設計 =====
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examples = [
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"A well-behaved schoolgirl with glasses",
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"Astronaut in a jungle, cold color palette, 8k",
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"An astronaut riding a green horse",
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]
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css = """
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#col-container {
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margin: 0 auto;
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max-width: 520px;
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}
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"""
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with gr.Blocks(css=css) as demo:
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with gr.Column(elem_id="col-container"):
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gr.Markdown("## 🧠 Anime Character Generator + Background Remover")
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# Prompt row
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with gr.Row():
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prompt = gr.Text(
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label="Prompt",
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show_label=False,
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max_lines=1,
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placeholder="Describe your anime character...",
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container=False,
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)
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run_button = gr.Button("🎨 Generate Anime")
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# Output image (before and after remove background)
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with gr.Row():
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result_img = gr.Image(label="Generated Image")
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removed_img = gr.Image(label="Background Removed")
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# Advanced settings
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with gr.Accordion("Advanced Settings", open=False):
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negative_prompt = gr.Text(
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label="Negative prompt",
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max_lines=1,
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placeholder="Enter a negative prompt",
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visible=True
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)
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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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with gr.Row():
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width = gr.Slider(label="Width", minimum=256, maximum=MAX_IMAGE_SIZE, step=32, value=512)
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height = gr.Slider(label="Height", minimum=256, maximum=MAX_IMAGE_SIZE, step=32, value=512)
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with gr.Row():
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guidance_scale = gr.Slider(label="Guidance Scale", minimum=0.0, maximum=10.0, step=0.1, value=0.0)
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num_inference_steps = gr.Slider(label="Steps", minimum=1, maximum=12, step=1, value=2)
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# 範例按鈕區
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gr.Markdown("#### ✨ Prompt Examples")
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with gr.Row():
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for example in examples:
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gr.Button(example).click(lambda x=example: x, outputs=prompt)
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# 主按鈕 callback
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run_button.click(
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fn=generate_anime,
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inputs=[prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
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outputs=[result_img]
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).then(
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fn=remove_background,
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inputs=[result_img],
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outputs=[removed_img]
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)
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demo.queue().launch(share=True)
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