Datasculptor/ControlNetv15

1# This file is adapted from https://github.com/lllyasviel/ControlNet/blob/f4748e3630d8141d7765e2bd9b1e348f47847707/gradio_scribble2image.py2# The original license file is LICENSE.ControlNet in this repo.3import gradio as gr4 5 6def create_demo(process, max_images=12):7    with gr.Blocks() as demo:8        with gr.Row():9            gr.Markdown('## Control Stable Diffusion with Scribble Maps')10        with gr.Row():11            with gr.Column():12                input_image = gr.Image(source='upload', type='numpy')13                prompt = gr.Textbox(label='Prompt')14                run_button = gr.Button(label='Run')15                with gr.Accordion('Advanced options', open=False):16                    num_samples = gr.Slider(label='Images',17                                            minimum=1,18                                            maximum=max_images,19                                            value=1,20                                            step=1)21                    image_resolution = gr.Slider(label='Image Resolution',22                                                 minimum=256,23                                                 maximum=768,24                                                 value=512,25                                                 step=256)26                    ddim_steps = gr.Slider(label='Steps',27                                           minimum=1,28                                           maximum=100,29                                           value=20,30                                           step=1)31                    scale = gr.Slider(label='Guidance Scale',32                                      minimum=0.1,33                                      maximum=30.0,34                                      value=9.0,35                                      step=0.1)36                    seed = gr.Slider(label='Seed',37                                     minimum=-1,38                                     maximum=2147483647,39                                     step=1,40                                     randomize=True,41                                     queue=False)42                    eta = gr.Number(label='eta (DDIM)', value=0.0)43                    a_prompt = gr.Textbox(44                        label='Added Prompt',45                        value='best quality, extremely detailed')46                    n_prompt = gr.Textbox(47                        label='Negative Prompt',48                        value=49                        'longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality'50                    )51            with gr.Column():52                result_gallery = gr.Gallery(label='Output',53                                            show_label=False,54                                            elem_id='gallery').style(55                                                grid=2, height='auto')56        ips = [57            input_image, prompt, a_prompt, n_prompt, num_samples,58            image_resolution, ddim_steps, scale, seed, eta59        ]60        run_button.click(fn=process,61                         inputs=ips,62                         outputs=[result_gallery],63                         api_name='scribble')64    return demo65