Spaces:
Sleeping
Sleeping
File size: 7,558 Bytes
7e7fb89 dd12e04 f785e6f 4e60da3 f785e6f e9722ce f785e6f 7150512 f785e6f 9fcef4d f785e6f 9fcef4d f785e6f 7150512 f785e6f ec1c2f8 f785e6f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 |
import os
os.environ['RENDERING_BACKEND'] = "osmesa"
import sys
root_dir = os.path.dirname(os.path.abspath(__file__))
sys.path.insert(1, os.path.join(root_dir, 'scenediffuser'))
import gradio as gr
import interface as IF
with gr.Blocks(css='style.css') as demo:
with gr.Column(elem_id="col-container"):
gr.Markdown("<p align='center' style='font-size: 1.5em;'>Diffusion-based Generation, Optimization, and Planning in 3D Scenes</p>")
gr.HTML(value="<img src='file/figures/teaser.png' alt='Teaser' width='710px' height='284px' style='display: block; margin: auto;'>")
gr.HTML(value="<p align='center' style='font-size: 1.2em; color: #485fc7;'><a href='https://arxiv.org/abs/2301.06015' target='_blank'>arXiv</a> | <a href='https://scenediffuser.github.io/' target='_blank'>Project Page</a> | <a href='https://github.com/scenediffuser/Scene-Diffuser' target='_blank'>Code</a></p>")
gr.Markdown("<p align='center'><i>\"SceneDiffuser provides a unified model for solving scene-conditioned generation, optimization, and planning.\"</i></p>")
## five task
## pose generation
with gr.Tab("Pose Generation"):
with gr.Row():
with gr.Column(scale=2):
selector1 = gr.Dropdown(choices=['MPH16', 'MPH1Library', 'N0SittingBooth', 'N3OpenArea'], label='Scenes', value='MPH16', interactive=True)
with gr.Row():
sample1 = gr.Slider(minimum=1, maximum=8, step=1, label='Count', interactive=True, value=1)
seed1 = gr.Slider(minimum=0, maximum=2 ** 16, step=1, label='Seed', interactive=True, value=2023)
opt1 = gr.Checkbox(label='Optimizer Guidance', interactive=True, value=True)
scale1 = gr.Slider(minimum=0.1, maximum=9.9, step=0.1, label='Scale', interactive=True, value=1.1)
button1 = gr.Button("Run")
with gr.Column(scale=3):
image1 = gr.Gallery(label="Image [Result]").style(grid=[1], height="50")
# model1 = gr.Model3D(clear_color=[255, 255, 255, 255], label="3D Model [Result]")
input1 = [selector1, sample1, seed1, opt1, scale1]
button1.click(IF.pose_generation, inputs=input1, outputs=[image1])
## motion generation
# with gr.Tab("Motion Generation"):
# with gr.Row():
# with gr.Column(scale=2):
# selector2 = gr.Dropdown(choices=['MPH16', 'MPH1Library', 'N0SittingBooth', 'N3OpenArea'], label='Scenes', value='MPH16', interactive=True)
# with gr.Row():
# sample2 = gr.Slider(minimum=1, maximum=8, step=1, label='Count', interactive=True, value=1)
# seed2 = gr.Slider(minimum=0, maximum=2 ** 16, step=1, label='Seed', interactive=True, value=2023)
# with gr.Row():
# withstart = gr.Checkbox(label='With Start', interactive=True, value=False)
# opt2 = gr.Checkbox(label='Optimizer Guidance', interactive=True, value=True)
# scale_opt2 = gr.Slider(minimum=0.1, maximum=9.9, step=0.1, label='Scale', interactive=True, value=1.1)
# button2 = gr.Button("Run")
# with gr.Column(scale=3):
# image2 = gr.Image(label="Result")
# input2 = [selector2, sample2, seed2, withstart, opt2, scale_opt2]
# button2.click(IF.motion_generation, inputs=input2, outputs=image2)
with gr.Tab("Motion Generation"):
with gr.Row():
with gr.Column(scale=2):
input2 = [
gr.Dropdown(choices=['MPH16', 'MPH1Library', 'N0SittingBooth', 'N3OpenArea'], label='Scenes')
]
button2 = gr.Button("Generate")
gr.HTML("<p style='font-size: 0.9em; color: #555555;'>Notes: the output results are pre-sampled results. We will deploy a real-time model for this task soon.</p>")
with gr.Column(scale=3):
output2 = gr.Image(label="Result")
button2.click(IF.motion_generation, inputs=input2, outputs=output2)
## grasp generation
with gr.Tab("Grasp Generation"):
with gr.Row():
with gr.Column(scale=2):
input3 = [
gr.Dropdown(choices=['contactdb+apple', 'contactdb+camera', 'contactdb+cylinder_medium', 'contactdb+door_knob', 'contactdb+rubber_duck', 'contactdb+water_bottle', 'ycb+baseball', 'ycb+pear', 'ycb+potted_meat_can', 'ycb+tomato_soup_can'], label='Objects')
]
button3 = gr.Button("Run")
gr.HTML("<p style='font-size: 0.9em; color: #555555;'>Notes: the output results are pre-sampled results. We will deploy a real-time model for this task soon.</p>")
with gr.Column(scale=3):
output3 = [
gr.Model3D(clear_color=[255, 255, 255, 255], label="Result")
]
button3.click(IF.grasp_generation, inputs=input3, outputs=output3)
## path planning
with gr.Tab("Path Planing"):
with gr.Row():
with gr.Column(scale=2):
selector4 = gr.Dropdown(choices=['scene0603_00', 'scene0621_00', 'scene0626_00', 'scene0634_00', 'scene0637_00', 'scene0640_00', 'scene0641_00', 'scene0645_00', 'scene0653_00', 'scene0667_00', 'scene0672_00', 'scene0673_00', 'scene0678_00', 'scene0694_00', 'scene0698_00'], label='Scenes', value='scene0621_00', interactive=True)
mode4 = gr.Radio(choices=['Sampling', 'Planning'], value='Sampling', label='Mode', interactive=True)
with gr.Row():
sample4 = gr.Slider(minimum=1, maximum=8, step=1, label='Count', interactive=True, value=1)
seed4 = gr.Slider(minimum=0, maximum=2 ** 16, step=1, label='Seed', interactive=True, value=2023)
with gr.Box():
opt4 = gr.Checkbox(label='Optimizer Guidance', interactive=True, value=True)
scale_opt4 = gr.Slider(minimum=0.02, maximum=4.98, step=0.02, label='Scale', interactive=True, value=1.0)
with gr.Box():
pla4 = gr.Checkbox(label='Planner Guidance', interactive=True, value=True)
scale_pla4 = gr.Slider(minimum=0.02, maximum=0.98, step=0.02, label='Scale', interactive=True, value=0.2)
button4 = gr.Button("Run")
with gr.Column(scale=3):
image4 = gr.Gallery(label="Image [Result]").style(grid=[1], height="50")
number4 = gr.Number(label="Steps", precision=0)
gr.HTML("<p style='font-size: 0.9em; color: #555555;'>Notes: 1. It may take a long time to do planning in <b>Planning</b> mode. 2. The <span style='color: #cc0000;'>red</span> balls represent the planning result, starting with the lightest red ball and ending with the darkest red ball. The <span style='color: #00cc00;'>green</span> ball indicates the target position.</p>")
input4 = [selector4, mode4, sample4, seed4, opt4, scale_opt4, pla4, scale_pla4]
button4.click(IF.path_planning, inputs=input4, outputs=[image4, number4])
## arm motion planning
with gr.Tab("Arm Motion Planning"):
gr.Markdown('Coming soon!')
demo.launch()
|