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on
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Running
on
Zero
File size: 2,298 Bytes
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if __name__ == "__main__":
import os
import sys
sys.path.append(os.curdir)
if 'CUDA_VISIBLE_DEVICES' not in os.environ:
os.environ['CUDA_VISIBLE_DEVICES'] = '0'
os.environ['TRANSFORMERS_OFFLINE']='0'
os.environ['DIFFUSERS_OFFLINE']='0'
os.environ['HF_HUB_OFFLINE']='0'
os.environ['GRADIO_ANALYTICS_ENABLED']='False'
os.environ['HF_ENDPOINT']='https://hf-mirror.com'
import torch
torch.set_float32_matmul_precision('medium')
torch.backends.cuda.matmul.allow_tf32 = True
torch.set_grad_enabled(False)
import gradio as gr
import argparse
from gradio_app.gradio_3dgen import create_ui as create_3d_ui
# from app.gradio_3dgen_steps import create_step_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.
'''
def launch(
port,
listen=False,
share=False,
gradio_root="",
):
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")
launch_args = {}
if listen:
launch_args["server_name"] = "0.0.0.0"
demo.queue(default_concurrency_limit=1).launch(
server_port=None if port == 0 else port,
share=share,
root_path=gradio_root if gradio_root != "" else None, # "/myapp"
**launch_args,
)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
args, extra = parser.parse_known_args()
parser.add_argument("--listen", action="store_true")
parser.add_argument("--port", type=int, default=0)
parser.add_argument("--share", action="store_true")
parser.add_argument("--gradio_root", default="")
args = parser.parse_args()
launch(
args.port,
listen=args.listen,
share=args.share,
gradio_root=args.gradio_root,
) |