Spaces:
Running
on
Zero
Running
on
Zero
| import gradio as gr | |
| from PIL import Image | |
| from gradio_app.custom_models.mvimg_prediction import run_mvprediction | |
| from gradio_app.utils import make_image_grid, split_image | |
| from scripts.utils import save_glb_and_video | |
| def concept_to_multiview(preview_img, input_processing, seed, guidance=1.): | |
| seed = int(seed) | |
| if preview_img is None: | |
| raise gr.Error("preview_img is none.") | |
| if isinstance(preview_img, str): | |
| preview_img = Image.open(preview_img) | |
| rgb_pils, front_pil = run_mvprediction(preview_img, remove_bg=input_processing, seed=seed, guidance_scale=guidance) | |
| rgb_pil = make_image_grid(rgb_pils, rows=2) | |
| return rgb_pil, front_pil | |
| def concept_to_multiview_ui(concurrency_id="wkl"): | |
| with gr.Row(): | |
| with gr.Column(scale=2): | |
| preview_img = gr.Image(type='pil', image_mode='RGBA', label='Frontview') | |
| input_processing = gr.Checkbox( | |
| value=True, | |
| label='Remove Background', | |
| ) | |
| seed = gr.Slider(minimum=-1, maximum=1000000000, value=-1, step=1.0, label="seed") | |
| guidance = gr.Slider(minimum=1.0, maximum=5.0, value=1.0, label="Guidance Scale", step=0.5) | |
| run_btn = gr.Button('Generate Multiview', interactive=True) | |
| with gr.Column(scale=3): | |
| # export mesh display | |
| output_rgb = gr.Image(type='pil', label="RGB", show_label=True) | |
| output_front = gr.Image(type='pil', image_mode='RGBA', label="Frontview", show_label=True) | |
| run_btn.click( | |
| fn = concept_to_multiview, | |
| inputs=[preview_img, input_processing, seed, guidance], | |
| outputs=[output_rgb, output_front], | |
| concurrency_id=concurrency_id, | |
| api_name=False, | |
| ) | |
| return output_rgb, output_front | |
| from gradio_app.custom_models.normal_prediction import predict_normals | |
| from scripts.multiview_inference import geo_reconstruct | |
| def multiview_to_mesh_v2(rgb_pil, normal_pil, front_pil, do_refine=False, expansion_weight=0.1, init_type="std"): | |
| rgb_pils = split_image(rgb_pil, rows=2) | |
| if normal_pil is not None: | |
| normal_pil = split_image(normal_pil, rows=2) | |
| if front_pil is None: | |
| front_pil = rgb_pils[0] | |
| new_meshes = geo_reconstruct(rgb_pils, normal_pil, front_pil, do_refine=do_refine, predict_normal=normal_pil is None, expansion_weight=expansion_weight, init_type=init_type) | |
| ret_mesh, video = save_glb_and_video("/tmp/gradio/generated", new_meshes, with_timestamp=True, dist=3.5, fov_in_degrees=2 / 1.35, cam_type="ortho", export_video=False) | |
| return ret_mesh | |
| def new_multiview_to_mesh_ui(concurrency_id="wkl"): | |
| with gr.Row(): | |
| with gr.Column(scale=2): | |
| rgb_pil = gr.Image(type='pil', image_mode='RGB', label='RGB') | |
| front_pil = gr.Image(type='pil', image_mode='RGBA', label='Frontview(Optinal)') | |
| normal_pil = gr.Image(type='pil', image_mode='RGBA', label='Normal(Optinal)') | |
| do_refine = gr.Checkbox( | |
| value=False, | |
| label='Refine rgb', | |
| visible=False, | |
| ) | |
| expansion_weight = gr.Slider(minimum=-1.0, maximum=1.0, value=0.1, step=0.1, label="Expansion Weight", visible=False) | |
| init_type = gr.Dropdown(choices=["std", "thin"], label="Mesh initialization", value="std", visible=False) | |
| run_btn = gr.Button('Generate 3D', interactive=True) | |
| with gr.Column(scale=3): | |
| # export mesh display | |
| output_mesh = gr.Model3D(value=None, label="mesh model", show_label=True) | |
| run_btn.click( | |
| fn = multiview_to_mesh_v2, | |
| inputs=[rgb_pil, normal_pil, front_pil, do_refine, expansion_weight, init_type], | |
| outputs=[output_mesh], | |
| concurrency_id=concurrency_id, | |
| api_name="multiview_to_mesh", | |
| ) | |
| return rgb_pil, front_pil, output_mesh | |
| ####################################### | |
| def create_step_ui(concurrency_id="wkl"): | |
| with gr.Tab(label="3D:concept_to_multiview"): | |
| concept_to_multiview_ui(concurrency_id) | |
| with gr.Tab(label="3D:new_multiview_to_mesh"): | |
| new_multiview_to_mesh_ui(concurrency_id) | |