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