import os from PIL import Image import gradio as gr def create_interface_texture_synthesis(runner): with gr.Blocks(): with gr.Row(): gr.Markdown('1. Upload the texture image as input.\n' '2. (Optional) Customize the configurations below as needed.\n' '3. Cilck `Run` to start synthesis.') with gr.Row(): with gr.Column(): with gr.Row(): texture_image = gr.Image(label='Input Texture Image', type='pil', interactive=True, value=Image.open('examples/s1.jpg').convert('RGB') if os.path.exists('examples/s1.jpg') else None) run_button = gr.Button(value='Run') with gr.Accordion('Options', open=True): height = gr.Number(label='Height', value=512, precision=0, minimum=2, maximum=4096) width = gr.Number(label='Width', value=1024, precision=0, minimum=2, maximum=4096) seed = gr.Number(label='Seed', value=2025, precision=0, minimum=0, maximum=2**31) num_steps = gr.Slider(label='Number of Steps', minimum=1, maximum=1000, value=200, step=1) iterations = gr.Slider(label='Iterations', minimum=0, maximum=10, value=2, step=1) lr = gr.Slider(label='Learning Rate', minimum=0.01, maximum=0.5, value=0.05, step=0.01) mixed_precision = gr.Radio(choices=['bf16', 'no'], value='bf16', label='Mixed Precision') num_images_per_prompt = gr.Slider(label='Num Images Per Prompt', minimum=1, maximum=10, value=1, step=1) base_model_list = ['stable-diffusion-v1-5/stable-diffusion-v1-5',] model = gr.Radio(choices=base_model_list, label='Select a Base Model', value='stable-diffusion-v1-5/stable-diffusion-v1-5') synthesis_way = gr.Radio(['Sampling', 'MultiDiffusion'], label='Synthesis Way', value='MultiDiffusion') with gr.Column(): gr.Markdown('#### Output Image:\n') result_gallery = gr.Gallery(label='Output', elem_id='gallery', columns=2, height='auto', preview=True) gr.Examples( [[Image.open('./webui/images/42.jpg').convert('RGB'), 'Sampling', 512, 1024, 50]], [texture_image, synthesis_way, height, width, num_steps] ) ips = [texture_image, height, width, seed, num_steps, iterations, lr, mixed_precision, num_images_per_prompt, synthesis_way,model] run_button.click(fn=runner.run_texture_synthesis, inputs=ips, outputs=[result_gallery])