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dfb6163 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | import os
from PIL import Image
import gradio as gr
def create_interface_style_transfer(runner):
with gr.Blocks():
with gr.Row():
gr.Markdown(
'1. 上传内容和风格图像作为输入.\n'
'2. （可选）根据需要定制以下配置.\n'
'3. 点击“运行”开始转换.'
)
with gr.Row():
with gr.Column():
with gr.Row():
content_image = gr.Image(label='内容图像', type='pil', interactive=True, value=None)
style_image = gr.Image(label='风格图像', type='pil', interactive=True, value=None)
run_button = gr.Button(value='Run')
with gr.Accordion('选项', open=True):
seed = gr.Number(label='种子', value=2025, precision=0, minimum=0, maximum=2**31)
num_steps = gr.Slider(label='步数', minimum=1, maximum=1000, value=200, step=1)
lr = gr.Slider(label='学习率', minimum=0.01, maximum=0.5, value=0.05, step=0.01)
content_weight = gr.Slider(label='内容权重', minimum=0., maximum=1., value=0.25, step=0.001)
mixed_precision = gr.Radio(choices=['bf16', 'no'], value='bf16', label='混合精度')
model_path=gr.Textbox(label='模型路径', value=r'D:\learn_torch\Exploration_Platform\model',placeholder='Path to your local model')
base_model_list = ['stable-diffusion-v1-5/stable-diffusion-v1-5', ]
model = gr.Radio(choices=base_model_list, label='选择基础模型', value='stable-diffusion-v1-5/stable-diffusion-v1-5')
with gr.Column():
gr.Markdown('#### 输出图片:\n')
result_gallery = gr.Gallery(label='Output', elem_id='gallery', columns=2, height='auto', preview=True)
gr.Markdown(
'Notes:\n'
'* 如果你发现风格效果不够，你可以尝试增加“步数”或减少“内容权重”`\n'
'* 我们通常建议使用“内容权重”为“0.25”'
)
ips = [content_image, style_image, seed, num_steps, lr, content_weight, mixed_precision, model_path,model]
run_button.click(fn=runner.run_style_transfer, inputs=ips, outputs=[result_gallery])
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