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#!/usr/bin/env python
from __future__ import annotations
import gradio as gr
from model import Model
DESCRIPTION = '''# TEXTure
This is an unofficial demo for [https://github.com/TEXTurePaper/TEXTurePaper](https://github.com/TEXTurePaper/TEXTurePaper).
This demo only accepts as input `.obj` files with less than 100,000 faces.
Inference takes about 10 minutes on a T4 GPU.
'''
model = Model()
with gr.Blocks(css='style.css') as demo:
gr.Markdown(DESCRIPTION)
gr.HTML("""
<p>For faster inference without waiting in queue, you may duplicate the space and upgrade to GPU in settings.
<br/>
<a href="https://huggingface.co/spaces/hysts/TEXTure?duplicate=true">
<img style="margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>
<p/>""")
with gr.Row():
with gr.Column():
input_shape = gr.Model3D(label='Input 3D mesh')
text = gr.Text(label='Text')
seed = gr.Slider(label='Seed',
minimum=0,
maximum=100000,
value=3,
step=1)
guidance_scale = gr.Slider(label='Guidance scale',
minimum=0,
maximum=50,
value=7.5,
step=0.1)
run_button = gr.Button('Run')
with gr.Column():
result = gr.Video(label='Result')
output_file = gr.File(label='Output mesh file')
with gr.Row():
examples = [
['shapes/dragon1.obj', 'a photo of a dragon', 0, 7.5],
['shapes/dragon2.obj', 'a photo of a dragon', 0, 7.5],
['shapes/eagle.obj', 'a photo of an eagle', 0, 7.5],
['shapes/napoleon.obj', 'a photo of Napoleon Bonaparte', 3, 7.5],
['shapes/nascar.obj', 'A next gen nascar', 2, 10],
]
gr.Examples(examples=examples,
inputs=[
input_shape,
text,
seed,
guidance_scale,
],
outputs=[
result,
output_file,
],
cache_examples=False)
run_button.click(fn=model.run,
inputs=[
input_shape,
text,
seed,
guidance_scale,
],
outputs=[
result,
output_file,
])
demo.queue(max_size=5).launch()
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