HIST/ControlNet

1# This file is adapted from https://github.com/lllyasviel/ControlNet/blob/f4748e3630d8141d7765e2bd9b1e348f47847707/gradio_canny2image.py2# The original license file is LICENSE.ControlNet this repo.3import gradio as gr4 5 6def create_demo(process):7    with gr.Blocks() as demo:8        with gr.Row():9            gr.Markdown('## Control Stable Diffusion with Canny Edge 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=12,19                                            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                    low_threshold = gr.Slider(label='Canny low threshold',27                                              minimum=1,28                                              maximum=255,29                                              value=100,30                                              step=1)31                    high_threshold = gr.Slider(label='Canny high threshold',32                                               minimum=1,33                                               maximum=255,34                                               value=200,35                                               step=1)36                    ddim_steps = gr.Slider(label='Steps',37                                           minimum=1,38                                           maximum=100,39                                           value=20,40                                           step=1)41                    scale = gr.Slider(label='Guidance Scale',42                                      minimum=0.1,43                                      maximum=30.0,44                                      value=9.0,45                                      step=0.1)46                    seed = gr.Slider(label='Seed',47                                     minimum=-1,48                                     maximum=2147483647,49                                     step=1,50                                     randomize=True)51                    eta = gr.Number(label='eta (DDIM)', value=0.0)52                    a_prompt = gr.Textbox(53                        label='Added Prompt',54                        value='best quality, extremely detailed')55                    n_prompt = gr.Textbox(56                        label='Negative Prompt',57                        value=58                        'longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality'59                    )60            with gr.Column():61                result_gallery = gr.Gallery(label='Output',62                                            show_label=False,63                                            elem_id='gallery').style(64                                                grid=2, height='auto')65        ips = [66            input_image, prompt, a_prompt, n_prompt, num_samples,67            image_resolution, ddim_steps, scale, seed, eta, low_threshold,68            high_threshold69        ]70        run_button.click(fn=process,71                         inputs=ips,72                         outputs=[result_gallery],73                         api_name='canny')74    return demo75