| |
|
|
| import gradio as gr |
|
|
| from settings import (DEFAULT_IMAGE_RESOLUTION, DEFAULT_NUM_IMAGES, |
| MAX_IMAGE_RESOLUTION, MAX_NUM_IMAGES, MAX_SEED) |
| from utils import randomize_seed_fn |
|
|
|
|
| def create_demo(process): |
| with gr.Blocks() as demo: |
| with gr.Row(): |
| with gr.Column(): |
| image = gr.Image() |
| prompt = gr.Textbox(label='Prompt') |
| run_button = gr.Button('Run') |
| with gr.Accordion('Advanced options', open=False): |
| num_samples = gr.Slider(label='Number of images', |
| minimum=1, |
| maximum=MAX_NUM_IMAGES, |
| value=DEFAULT_NUM_IMAGES, |
| step=1) |
| image_resolution = gr.Slider( |
| label='Image resolution', |
| minimum=256, |
| maximum=MAX_IMAGE_RESOLUTION, |
| value=DEFAULT_IMAGE_RESOLUTION, |
| step=256) |
| num_steps = gr.Slider(label='Number of steps', |
| minimum=1, |
| maximum=100, |
| value=20, |
| step=1) |
| guidance_scale = gr.Slider(label='Guidance scale', |
| minimum=0.1, |
| maximum=30.0, |
| value=9.0, |
| step=0.1) |
| seed = gr.Slider(label='Seed', |
| minimum=0, |
| maximum=MAX_SEED, |
| step=1, |
| value=0) |
| randomize_seed = gr.Checkbox(label='Randomize seed', |
| value=True) |
| a_prompt = gr.Textbox( |
| label='Additional prompt', |
| value='best quality, extremely detailed') |
| n_prompt = gr.Textbox( |
| label='Negative prompt', |
| value= |
| 'longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality' |
| ) |
| with gr.Column(): |
| result = gr.Gallery(label='Output', |
| show_label=False, |
| columns=2, |
| object_fit='scale-down') |
| inputs = [ |
| image, |
| prompt, |
| a_prompt, |
| n_prompt, |
| num_samples, |
| image_resolution, |
| num_steps, |
| guidance_scale, |
| seed, |
| ] |
| prompt.submit( |
| fn=randomize_seed_fn, |
| inputs=[seed, randomize_seed], |
| outputs=seed, |
| queue=False, |
| api_name=False, |
| ).then( |
| fn=process, |
| inputs=inputs, |
| outputs=result, |
| api_name=False, |
| ) |
| run_button.click( |
| fn=randomize_seed_fn, |
| inputs=[seed, randomize_seed], |
| outputs=seed, |
| queue=False, |
| api_name=False, |
| ).then( |
| fn=process, |
| inputs=inputs, |
| outputs=result, |
| api_name='ip2p', |
| ) |
| return demo |
|
|
|
|
| if __name__ == '__main__': |
| from model import Model |
| model = Model(task_name='ip2p') |
| demo = create_demo(model.process_ip2p) |
| demo.queue().launch() |
|
|
