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Running
on
Zero
| import random | |
| import gradio as gr | |
| from functools import partial | |
| from .gradio_custommodel3d import CustomModel3D | |
| from .gradio_customgs import CustomGS | |
| def create_interface_img_to_3d(segmentation_api, freesplatter_api, model='Zero123++ v1.2'): | |
| default_views = { | |
| 'Zero123++ v1.1': ['Input', 'V2', 'V3', 'V5'], | |
| 'Zero123++ v1.2': ['V1', 'V2', 'V3', 'V5', 'V6'], | |
| 'Hunyuan3D Std': ['V1', 'V2', 'V4', 'V6'] | |
| } | |
| views_info = { | |
| 'Zero123++ v1.1': 'View poses (azimuth, elevation): V1(30, 30), V2(90, -20), V3(150, 30), V4(-150, -20), V5(-90, 30), V6(-30, -20)', | |
| 'Zero123++ v1.2': 'View poses (azimuth, elevation): V1(30, 20), V2(90, -10), V3(150, 20), V4(-150, -10), V5(-90, 20), V6(-30, -10)', | |
| 'Hunyuan3D Std': 'View poses (azimuth, elevation): V1(0, 0), V2(60, 0), V3(120, 0), V4(180, 0), V5(-120, 0), V6(-60, 0)', | |
| } | |
| var_dict = dict() | |
| with gr.Blocks(analytics_enabled=False) as interface: | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| with gr.Row(): | |
| var_dict['in_image'] = gr.Image( | |
| label='Input image', | |
| type='pil', | |
| image_mode='RGBA', | |
| ) | |
| var_dict['fg_image'] = gr.Image( | |
| label='Segmented foreground', | |
| type='pil', | |
| interactive=False, | |
| image_mode='RGBA', | |
| ) | |
| with gr.Accordion("Diffusion settings", open=True): | |
| with gr.Row(): | |
| var_dict['do_rembg'] = gr.Checkbox( | |
| label='Remove background', | |
| value=True, | |
| container=False, | |
| ) | |
| with gr.Row(): | |
| with gr.Column(): | |
| var_dict['seed'] = gr.Number( | |
| label='Random seed', | |
| value=42, | |
| min_width=100, | |
| precision=0, | |
| minimum=0, | |
| maximum=2 ** 31, | |
| elem_classes=['force-hide-container'], | |
| ) | |
| var_dict['random_seed'] = gr.Button( | |
| '\U0001f3b2\ufe0f Try your luck!', | |
| elem_classes=['tool'], | |
| ) | |
| with gr.Column(): | |
| var_dict['diffusion_steps'] = gr.Slider( | |
| label="Sampling steps", | |
| minimum=15, | |
| maximum=75, | |
| value=30, | |
| step=5, | |
| ) | |
| var_dict['guidance_scale'] = gr.Slider( | |
| label="Guidance scale", | |
| minimum=1, | |
| maximum=10, | |
| value=4, | |
| step=1, | |
| ) | |
| with gr.Accordion("Reconstruction settings", open=True): | |
| with gr.Row(): | |
| var_dict['view_indices'] = gr.CheckboxGroup( | |
| choices=['Input', 'V1', 'V2', 'V3', 'V4', 'V5', 'V6'], | |
| value=default_views[model], | |
| type='index', | |
| label='Views used for reconstruction', | |
| info='Using input image is only recommended for Zero123++ v1.1', | |
| ) | |
| with gr.Row(): | |
| var_dict['gs_type'] = gr.Radio( | |
| choices=['2DGS', '3DGS'], | |
| value='2DGS', | |
| type='value', | |
| label='Gaussian splatting type', | |
| info='2DGS often leads to better mesh geometry' | |
| ) | |
| var_dict['mesh_reduction'] = gr.Slider( | |
| label="Mesh simplification ratio", | |
| info='Larger ratio leads to less faces', | |
| minimum=0., | |
| maximum=0.9, | |
| value=0.7, | |
| step=0.1, | |
| ) | |
| with gr.Row(equal_height=False): | |
| var_dict['run_btn'] = gr.Button('Generate', variant='primary', scale=2) | |
| with gr.Row(visible=False): | |
| var_dict['model'] = gr.Textbox(value=model, label='Model') | |
| gr.Examples( | |
| examples='examples/img_to_3d', | |
| inputs=var_dict['in_image'], | |
| cache_examples=False, | |
| label='Examples (click one of the images below to start)', | |
| examples_per_page=21, | |
| ) | |
| with gr.Column(scale=1): | |
| var_dict['out_multiview'] = gr.Image( | |
| label='Generated views', | |
| interactive=False, | |
| image_mode='RGBA', | |
| ) | |
| var_dict['out_pose'] = gr.Plot( | |
| label='Estimated poses', | |
| ) | |
| var_dict['out_gs_vis'] = CustomGS( | |
| label='Output GS', | |
| interactive=False, | |
| height=320, | |
| ) | |
| var_dict['out_video'] = gr.Video( | |
| label='Output video', | |
| interactive=False, | |
| autoplay=True, | |
| height=320, | |
| ) | |
| var_dict['out_mesh'] = CustomModel3D( | |
| label='Output mesh', | |
| interactive=False, | |
| height=400, | |
| ) | |
| var_dict['run_btn'].click( | |
| fn=segmentation_api, | |
| inputs=var_dict['in_image'], | |
| outputs=var_dict['fg_image'], | |
| concurrency_id='default_group', | |
| api_name='run_segmentation', | |
| ).success( | |
| fn=partial(freesplatter_api, cache_dir=interface.GRADIO_CACHE), | |
| inputs=[var_dict['fg_image'], | |
| var_dict['model'], | |
| var_dict['diffusion_steps'], | |
| var_dict['guidance_scale'], | |
| var_dict['seed'], | |
| var_dict['view_indices'], | |
| var_dict['gs_type'], | |
| var_dict['mesh_reduction']], | |
| outputs=[var_dict['out_multiview'], var_dict['out_gs_vis'], var_dict['out_video'], var_dict['out_mesh'], var_dict['out_pose']], | |
| concurrency_id='default_group', | |
| api_name='run_image_to_3d', | |
| ) | |
| var_dict['random_seed'].click( | |
| fn=lambda: random.randint(0, 2 ** 31), | |
| outputs=var_dict['seed'], | |
| show_progress=False, | |
| api_name=False, | |
| ) | |
| return interface, var_dict | |