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Parent(s):
fcb4ec9
Update
Browse files- app.py +130 -98
- pre-requirements.txt +0 -3
- requirements.txt +3 -26
app.py
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import os
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os.environ['PYOPENGL_PLATFORM'] = 'egl'
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import sys
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root_dir = os.path.dirname(os.path.abspath(__file__))
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sys.path.insert(1, os.path.join(root_dir, 'scenediffuser'))
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print(sys.path)
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import gradio as gr
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import
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with gr.Blocks(css='style.css') as demo:
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demo.launch()
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import gradio as gr
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import os
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os.environ["PYOPENGL_PLATFORM"] = "egl" #opengl seems to only work with TPU
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from OpenGL import EGL
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print(os.environ['PYOPENGL_PLATFORM'])
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import numpy as np
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import os
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import trimesh
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from pyrender import PerspectiveCamera,\
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DirectionalLight, SpotLight, PointLight,\
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MetallicRoughnessMaterial,\
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Primitive, Mesh, Node, Scene,\
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OffscreenRenderer
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from PIL import Image
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scene = Scene()
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axis = trimesh.creation.axis()
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axis = Mesh.from_trimesh(axis, smooth=False)
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scene.add(axis)
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r = OffscreenRenderer(
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viewport_width=720,
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viewport_height=720,
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)
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color, _ = r.render(scene)
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color = color.astype(np.float32) / 255.0
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img = Image.fromarray((color * 255).astype(np.uint8))
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r.delete()
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print(img)
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# import os
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# os.environ['PYOPENGL_PLATFORM'] = 'egl'
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# import sys
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# root_dir = os.path.dirname(os.path.abspath(__file__))
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# sys.path.insert(1, os.path.join(root_dir, 'scenediffuser'))
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# print(sys.path)
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# import gradio as gr
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# import interface as IF
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# with gr.Blocks(css='style.css') as demo:
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# with gr.Column(elem_id="col-container"):
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# gr.Markdown("<p align='center' style='font-size: 1.5em;'>Diffusion-based Generation, Optimization, and Planning in 3D Scenes</p>")
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# gr.HTML(value="<img src='file/figures/teaser.png' alt='Teaser' width='710px' height='284px' style='display: block; margin: auto;'>")
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# 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>")
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# gr.Markdown("<p align='center'><i>\"SceneDiffuser provides a unified model for solving scene-conditioned generation, optimization, and planning.\"</i></p>")
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# ## five task
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# ## pose generation
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# with gr.Tab("Pose Generation"):
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# with gr.Row():
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# with gr.Column(scale=2):
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# selector1 = gr.Dropdown(choices=['MPH16', 'MPH1Library', 'N0SittingBooth', 'N3OpenArea'], label='Scenes', value='MPH16', interactive=True)
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# with gr.Row():
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# sample1 = gr.Slider(minimum=1, maximum=8, step=1, label='Count', interactive=True, value=1)
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# seed1 = gr.Slider(minimum=0, maximum=2 ** 16, step=1, label='Seed', interactive=True, value=2023)
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# opt1 = gr.Checkbox(label='Optimizer Guidance', interactive=True, value=True)
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# scale1 = gr.Slider(minimum=0.1, maximum=9.9, step=0.1, label='Scale', interactive=True, value=1.1)
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# button1 = gr.Button("Run")
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# with gr.Column(scale=3):
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# image1 = gr.Gallery(label="Image [Result]").style(grid=[1], height="50")
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# # model1 = gr.Model3D(clear_color=[255, 255, 255, 255], label="3D Model [Result]")
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# input1 = [selector1, sample1, seed1, opt1, scale1]
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# button1.click(IF.pose_generation, inputs=input1, outputs=[image1])
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# ## motion generation
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# # with gr.Tab("Motion Generation"):
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# # with gr.Row():
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# # with gr.Column(scale=2):
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# # selector2 = gr.Dropdown(choices=['MPH16', 'MPH1Library', 'N0SittingBooth', 'N3OpenArea'], label='Scenes', value='MPH16', interactive=True)
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# # with gr.Row():
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# # sample2 = gr.Slider(minimum=1, maximum=8, step=1, label='Count', interactive=True, value=1)
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# # seed2 = gr.Slider(minimum=0, maximum=2 ** 16, step=1, label='Seed', interactive=True, value=2023)
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# # with gr.Row():
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# # withstart = gr.Checkbox(label='With Start', interactive=True, value=False)
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# # opt2 = gr.Checkbox(label='Optimizer Guidance', interactive=True, value=True)
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# # scale_opt2 = gr.Slider(minimum=0.1, maximum=9.9, step=0.1, label='Scale', interactive=True, value=1.1)
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# # button2 = gr.Button("Run")
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# # with gr.Column(scale=3):
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# # image2 = gr.Image(label="Result")
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# # input2 = [selector2, sample2, seed2, withstart, opt2, scale_opt2]
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# # button2.click(IF.motion_generation, inputs=input2, outputs=image2)
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# with gr.Tab("Motion Generation"):
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# with gr.Row():
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# with gr.Column(scale=2):
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# input2 = [
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# gr.Dropdown(choices=['MPH16', 'MPH1Library', 'N0SittingBooth', 'N3OpenArea'], label='Scenes')
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# ]
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# button2 = gr.Button("Generate")
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# 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>")
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# with gr.Column(scale=3):
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# output2 = gr.Image(label="Result")
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# button2.click(IF.motion_generation, inputs=input2, outputs=output2)
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# ## grasp generation
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# with gr.Tab("Grasp Generation"):
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# with gr.Row():
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# with gr.Column(scale=2):
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# input3 = [
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# 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')
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# ]
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# button3 = gr.Button("Run")
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# 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>")
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# with gr.Column(scale=3):
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# output3 = [
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# gr.Model3D(clear_color=[255, 255, 255, 255], label="Result")
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# ]
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# button3.click(IF.grasp_generation, inputs=input3, outputs=output3)
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# ## path planning
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# with gr.Tab("Path Planing"):
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# with gr.Row():
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# with gr.Column(scale=2):
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# 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)
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# mode4 = gr.Radio(choices=['Sampling', 'Planning'], value='Sampling', label='Mode', interactive=True)
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# with gr.Row():
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# sample4 = gr.Slider(minimum=1, maximum=8, step=1, label='Count', interactive=True, value=1)
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# seed4 = gr.Slider(minimum=0, maximum=2 ** 16, step=1, label='Seed', interactive=True, value=2023)
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# with gr.Box():
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# opt4 = gr.Checkbox(label='Optimizer Guidance', interactive=True, value=True)
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# scale_opt4 = gr.Slider(minimum=0.02, maximum=4.98, step=0.02, label='Scale', interactive=True, value=1.0)
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# with gr.Box():
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# pla4 = gr.Checkbox(label='Planner Guidance', interactive=True, value=True)
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# scale_pla4 = gr.Slider(minimum=0.02, maximum=0.98, step=0.02, label='Scale', interactive=True, value=0.2)
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# button4 = gr.Button("Run")
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# with gr.Column(scale=3):
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# image4 = gr.Gallery(label="Image [Result]").style(grid=[1], height="50")
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# number4 = gr.Number(label="Steps", precision=0)
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# 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>")
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# input4 = [selector4, mode4, sample4, seed4, opt4, scale_opt4, pla4, scale_pla4]
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# button4.click(IF.path_planning, inputs=input4, outputs=[image4, number4])
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# ## arm motion planning
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# with gr.Tab("Arm Motion Planning"):
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# gr.Markdown('Coming soon!')
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# demo.launch()
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pre-requirements.txt
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--extra-index-url https://download.pytorch.org/whl/cu113
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torch==1.11.0+cu113
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torchvision==0.12.0+cu113
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requirements.txt
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git+https://github.com/Silverster98/pointops@T4
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git+https://github.com/nghorbani/human_body_prior
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urdf-parser-py==0.0.4
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einops==0.4.1
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hydra-core==1.2.0
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loguru==0.6.0
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matplotlib==3.5.1
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natsort==8.2.0
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networkx==2.8.6
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omegaconf==2.2.2
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opencv-python==4.6.0.66
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Pillow==9.0.1
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plotly==5.11.0
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protobuf==3.19.4
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pyquaternion==0.9.9
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pyrender==0.1.45
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smplx==0.1.28
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tabulate==0.8.10
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tensorboard==2.8.0
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tqdm==4.62.3
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transforms3d==0.4.1
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transformations==2022.9.26
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trimesh==3.12.7
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pyrender
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trimesh
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pillow
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