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import shlex
import subprocess
subprocess.run(
shlex.split(
"pip install https://pkgs.dev.azure.com/onnxruntime/2a773b67-e88b-4c7f-9fc0-87d31fea8ef2/_packaging/7fa31e42-5da1-4e84-a664-f2b4129c7d45/pypi/download/onnxruntime-gpu/1.17/onnxruntime_gpu-1.17.0-cp310-cp310-manylinux_2_28_x86_64.whl --force-reinstall --no-deps"
)
)
subprocess.run(
shlex.split(
"mkdir -p /home/user/.cache/torch_extensions/ && cp -r torch_extensions/py310_cu121 /home/user/.cache/torch_extensions/"
)
)
if __name__ == "__main__":
import os
import sys
sys.path.append(os.curdir)
import torch
torch.set_float32_matmul_precision('medium')
torch.backends.cuda.matmul.allow_tf32 = True
torch.set_grad_enabled(False)
import fire
import gradio as gr
from gradio_app.gradio_3dgen import create_ui as create_3d_ui
from gradio_app.all_models import model_zoo
_TITLE = '''Unique3D: High-Quality and Efficient 3D Mesh Generation from a Single Image'''
_DESCRIPTION = '''
# [Project page](https://wukailu.github.io/Unique3D/)
* High-fidelity and diverse textured meshes generated by Unique3D from single-view images.
* The demo is still under construction, and more features are expected to be implemented soon.
# NOTE: The Hugging Face demo is still under development and cannot produce any accurate results at the moment.
'''
def launch():
model_zoo.init_models()
with gr.Blocks(
title=_TITLE,
theme=gr.themes.Monochrome(),
) as demo:
with gr.Row():
with gr.Column(scale=1):
gr.Markdown('# ' + _TITLE)
gr.Markdown(_DESCRIPTION)
create_3d_ui("wkl")
demo.queue().launch(share=True)
if __name__ == '__main__':
fire.Fire(launch)
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