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| import gradio as gr | |
| import numpy as np | |
| import random | |
| from diffusers import DiffusionPipeline | |
| from rembg import remove | |
| import torch | |
| # ===== εε§ε樑ε ===== | |
| 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) | |
| # ===== εθ½ε½ζΈ ===== | |
| 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 δ»ι’θ¨θ¨ ===== | |
| 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("## π§ 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("π¨ 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) | |
| # η―δΎζιε | |
| gr.Markdown("#### β¨ Prompt Examples") | |
| with gr.Row(): | |
| for example in examples: | |
| gr.Button(example).click(lambda x=example: x, outputs=prompt) | |
| # δΈ»ζι 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) | |