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Running
on
Zero
File size: 2,753 Bytes
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import os
import shutil
from functools import partial
import gradio as gr
from common import (
MAX_SEED,
VERSION,
TrellisImageTo3DPipeline,
active_btn_by_content,
extract_3d_representations_v2,
extract_urdf,
get_seed,
image_to_3d,
preprocess_image_fn,
preprocess_sam_image_fn,
select_point,
)
from gradio.themes import Default
from gradio.themes.utils.colors import slate
from gradio_litmodel3d import LitModel3D
from asset3d_gen.models.delight import DelightingModel
from asset3d_gen.models.segment import RembgRemover, SAMPredictor
from asset3d_gen.models.super_resolution import ImageRealESRGAN
from asset3d_gen.utils.gpt_clients import GPT_CLIENT
from asset3d_gen.validators.quality_checkers import (
ImageAestheticChecker,
ImageSegChecker,
MeshGeoChecker,
)
from asset3d_gen.validators.urdf_convertor import URDFGenerator
TMP_DIR = os.path.join(
os.path.dirname(os.path.abspath(__file__)), "sessions/imageto3d"
)
os.makedirs(TMP_DIR, exist_ok=True)
# RBG_REMOVER = RembgRemover()
# SAM_PREDICTOR = SAMPredictor(model_type="vit_h")
# DELIGHT = DelightingModel()
# IMAGESR_MODEL = ImageRealESRGAN(outscale=4)
# PIPELINE = TrellisImageTo3DPipeline.from_pretrained(
# "JeffreyXiang/TRELLIS-image-large"
# )
# # PIPELINE.cuda()
# IMAGE_BUFFER = {}
# SEG_CHECKER = ImageSegChecker(GPT_CLIENT)
# GEO_CHECKER = MeshGeoChecker(GPT_CLIENT)
# AESTHETIC_CHECKER = ImageAestheticChecker()
# CHECKERS = [GEO_CHECKER, SEG_CHECKER, AESTHETIC_CHECKER]
# URDF_CONVERTOR = URDFGenerator(GPT_CLIENT, render_view_num=4)
def start_session(req: gr.Request) -> None:
user_dir = os.path.join(TMP_DIR, str(req.session_hash))
os.makedirs(user_dir, exist_ok=True)
def end_session(req: gr.Request) -> None:
user_dir = os.path.join(TMP_DIR, str(req.session_hash))
if os.path.exists(user_dir):
shutil.rmtree(user_dir)
with gr.Blocks(
delete_cache=(43200, 43200)
) as demo:
with gr.Column(scale=1):
video_output = gr.Video(
label="Generated 3D Asset",
autoplay=True,
loop=True,
height=300,
)
model_output_gs = gr.Model3D(
label="Gaussian Representation", height=300, interactive=False
)
aligned_gs = gr.Textbox(visible=False)
with gr.Row():
model_output_mesh = LitModel3D(
label="Mesh Representation",
height=300,
exposure=10,
interactive=False
)
gr.Markdown(
""" The rendering of `Gaussian Representation` takes additional 10s. """ # noqa
)
demo.load(start_session)
demo.unload(end_session)
if __name__ == "__main__":
demo.launch()
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