File size: 1,565 Bytes
7c39d15 4499b2e 7c39d15 d3a448c 7c39d15 37aeb5b 5a3e910 37aeb5b 04f25a3 0c552a7 37aeb5b 0c552a7 37aeb5b |
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 |
import shlex
import subprocess
subprocess.run(
shlex.split(
"pip install package/onnxruntime_gpu-1.17.0-cp310-cp310-manylinux_2_28_x86_64.whl --force-reinstall --no-deps"
)
)
subprocess.run(
shlex.split(
"pip install package/nvdiffrast-0.3.1.torch-cp310-cp310-linux_x86_64.whl"
)
)
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)
|