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# Tencent HunyuanWorld-1.0 is licensed under TENCENT HUNYUANWORLD-1.0 COMMUNITY LICENSE AGREEMENT
# THIS LICENSE AGREEMENT DOES NOT APPLY IN THE EUROPEAN UNION, UNITED KINGDOM AND SOUTH KOREA AND
# IS EXPRESSLY LIMITED TO THE TERRITORY, AS DEFINED BELOW.
# By clicking to agree or by using, reproducing, modifying, distributing, performing or displaying
# any portion or element of the Tencent HunyuanWorld-1.0 Works, including via any Hosted Service,
# You will be deemed to have recognized and accepted the content of this Agreement,
# which is effective immediately.
# For avoidance of doubts, Tencent HunyuanWorld-1.0 means the 3D generation models
# and their software and algorithms, including trained model weights, parameters (including
# optimizer states), machine-learning model code, inference-enabling code, training-enabling code,
# fine-tuning enabling code and other elements of the foregoing made publicly available
# by Tencent at [https://github.com/Tencent-Hunyuan/HunyuanWorld-1.0].
import os
import torch
import open3d as o3d
import argparse
# hunyuan3d sence generation
from hy3dworld import LayerDecomposition
from hy3dworld import WorldComposer, process_file
class HYworldDemo:
def __init__(self, seed=42):
target_size = 3840
kernel_scale = max(1, int(target_size / 1920))
self.LayerDecomposer = LayerDecomposition()
self.hy3d_world = WorldComposer(
device=torch.device(
"cuda" if torch.cuda.is_available() else "cpu"),
resolution=(target_size, target_size // 2),
seed=seed,
filter_mask=True,
kernel_scale=kernel_scale,
)
def run(self, image_path, labels_fg1, labels_fg2, classes="outdoor", output_dir='output_hyworld', export_drc=False):
# foreground layer information
fg1_infos = [
{
"image_path": image_path,
"output_path": output_dir,
"labels": labels_fg1,
"class": classes,
}
]
fg2_infos = [
{
"image_path": os.path.join(output_dir, 'remove_fg1_image.png'),
"output_path": output_dir,
"labels": labels_fg2,
"class": classes,
}
]
# layer decompose
self.LayerDecomposer(fg1_infos, layer=0)
self.LayerDecomposer(fg2_infos, layer=1)
self.LayerDecomposer(fg2_infos, layer=2)
separate_pano, fg_bboxes = self.hy3d_world._load_separate_pano_from_dir(
output_dir, sr=True
)
# layer-wise reconstruction
layered_world_mesh = self.hy3d_world.generate_world(
separate_pano=separate_pano, fg_bboxes=fg_bboxes, world_type='mesh'
)
# save results
for layer_idx, layer_info in enumerate(layered_world_mesh):
# export ply
output_path = os.path.join(
output_dir, f"mesh_layer{layer_idx}.ply"
)
o3d.io.write_triangle_mesh(output_path, layer_info['mesh'])
# export drc
if export_drc:
output_path_drc = os.path.join(
output_dir, f"mesh_layer{layer_idx}.drc"
)
process_file(output_path, output_path_drc)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Hunyuan3D World Gen Demo")
parser.add_argument("--image_path", type=str,
default=None, help="Path to the Panorama image")
parser.add_argument("--labels_fg1", nargs='+', default=[],
help="Labels for foreground objects in layer 1")
parser.add_argument("--labels_fg2", nargs='+', default=[],
help="Labels for foreground objects in layer 2")
parser.add_argument("--classes", type=str, default="outdoor",
help="Classes for sence generation")
parser.add_argument("--seed", type=int, default=42,
help="Random seed for reproducibility")
parser.add_argument("--output_path", type=str, default="results",
help="Path to save the output results")
parser.add_argument("--export_drc", type=bool, default=False,
help="Whether to export Draco format")
args = parser.parse_args()
os.makedirs(args.output_path, exist_ok=True)
print(f"Output will be saved to: {args.output_path}")
demo_HYworld = HYworldDemo(seed=args.seed)
demo_HYworld.run(
image_path=args.image_path,
labels_fg1=args.labels_fg1,
labels_fg2=args.labels_fg2,
classes=args.classes,
output_dir=args.output_path,
export_drc=args.export_drc
)
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