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import os
import json
import argparse
import numpy as np
import collections
from src.layoutvlm.scene import Scene
from src.layoutvlm.layoutvlm import LayoutVLM
from utils.placement_utils import get_random_placement
# os.environ["LIBGL_ALWAYS_SOFTWARE"] = "1"
# os.environ["GALLIUM_DRIVER"] = "llvmpipe"
# os.environ["MESA_GL_VERSION_OVERRIDE"] = "3.3"
# os.environ["MESA_GLSL_VERSION_OVERRIDE"] = "330"
# os.environ["EGL_SOFTWARE"] = "1"
# # 确保 DISPLAY 环境变量已设置
# if "DISPLAY" not in os.environ:
# os.environ["DISPLAY"] = ":99"
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("--scene_json_file", help="Path to scene JSON file", default="/home/v-meiszhang/amlt-project/LayoutVLM/benchmark_tasks/bookstore/bookstore_2.json")
parser.add_argument("--save_dir", help="Directory to save results", default="./results/test_run3")
# parser.add_argument("--model", help="Model to use for layout generation", default="gpt-4")
# parser.add_argument("--openai_api_key", help="OpenAI API key", required=True)
parser.add_argument("--asset_dir", help="Directory to load assets from.", default="/home/v-meiszhang/backup/objaverse_processed")
return parser.parse_args()
def prepare_task_assets(task, asset_dir):
"""
Prepare assets for the task by processing their metadata and annotations.
This is a minimal version that assumes assets are already downloaded and processed.
"""
if "layout_criteria" not in task:
task["layout_criteria"] = "the layout should follow the task description and adhere to common sense"
all_data = collections.defaultdict(list)
for original_uid in task["assets"].keys():
# Remove the idx number from the uid
uid = '-'.join(original_uid.split('-')[:-1])
# Load asset data
data_path = os.path.join(asset_dir, uid, "data.json")
if not os.path.exists(data_path):
print(f"Warning: Asset data not found for {uid}")
continue
with open(data_path, "r") as f:
data = json.load(f)
data['path'] = os.path.join(asset_dir, uid, f"{uid}.glb")
all_data[uid].append(data)
# Process categories and create asset entries
category_count = collections.defaultdict(int)
for uid, duplicated_assets in all_data.items():
category_var_name = duplicated_assets[0]['annotations']['category']
category_var_name = category_var_name.replace('-', "_").replace(" ", "_").replace("'", "_").replace("/", "_").replace(",", "_").lower()
category_count[category_var_name] += 1
task["assets"] = {}
category_idx = collections.defaultdict(int)
for uid, duplicated_assets in all_data.items():
category_var_name = duplicated_assets[0]['annotations']['category']
category_var_name = category_var_name.replace('-', "_").replace(" ", "_").replace("'", "_").replace("/", "_").replace(",", "_").lower()
category_idx[category_var_name] += 1
for instance_idx, data in enumerate(duplicated_assets):
# Create category name with suffix if needed
category_var_name = f"{category_var_name}_{chr(ord('A') + category_idx[category_var_name]-1)}" if category_count[category_var_name] > 1 else category_var_name
# Create instance name
var_name = f"{category_var_name}_{instance_idx}" if len(duplicated_assets) > 1 else category_var_name
# Create asset entry
task["assets"][f"{category_var_name}-{instance_idx}"] = {
"uid": uid,
"count": len(duplicated_assets),
"instance_var_name": var_name,
"asset_var_name": category_var_name,
"instance_idx": instance_idx,
"annotations": data["annotations"],
"category": data["annotations"]["category"],
'description': data['annotations']['description'],
'path': data['path'],
'onCeiling': data['annotations']['onCeiling'],
'onFloor': data['annotations']['onFloor'],
'onWall': data['annotations']['onWall'],
'onObject': data['annotations']['onObject'],
'frontView': data['annotations']['frontView'],
'assetMetadata': {
"boundingBox": {
"x": float(data['assetMetadata']['boundingBox']['y']), # SWAP x and y
"y": float(data['assetMetadata']['boundingBox']['x']),
"z": float(data['assetMetadata']['boundingBox']['z'])
},
}
}
return task
def main():
args = parse_args()
# if args.openai_api_key:
# os.environ["OPENAI_API_KEY"] = args.openai_api_key
# Create save directory
os.makedirs(args.save_dir, exist_ok=True)
# Load scene configuration
with open(args.scene_json_file, 'r') as f:
scene_config = json.load(f)
# Prepare assets
scene_config = prepare_task_assets(scene_config, args.asset_dir)
# Initialize constraint solver
layout_solver = LayoutVLM(
mode="one_shot",
save_dir=args.save_dir,
asset_source="objaverse" # Default to objaverse
)
# Generate layout
layout = layout_solver.solve(scene_config)
# Save results
output_path = os.path.join(args.save_dir, 'layout.json')
with open(output_path, 'w') as f:
json.dump(layout, f, indent=2)
print(f"Layout generated and saved to {output_path}")
# Render final scene with all placed 3D assets
print("Rendering final scene with 3D assets...")
from utils.blender_render import render_existing_scene
from utils.blender_utils import reset_blender
try:
output_images, visual_marks = render_existing_scene(
layout,
scene_config,
save_dir=args.save_dir,
high_res=True,
render_top_down=True,
apply_3dfront_texture=False,
combine_obj_components=False,
fov_multiplier=1.3,
add_coordinate_mark=True,
annotate_object=True,
annotate_wall=True,
add_object_bbox=False,
topdown_save_file=os.path.join(args.save_dir, 'final_scene_top_down.png'),
sideview_save_file=os.path.join(args.save_dir, 'final_scene_side_view.png'),
side_view_indices=[0, 1, 2, 3] # Render from multiple angles
)
reset_blender()
print(f"Final scene renderings saved to {args.save_dir}")
print(f" - Top-down view: final_scene_top_down.png")
print(f" - Side views: final_scene_side_view.png")
except Exception as e:
print(f"Warning: Failed to render final scene: {e}")
if __name__ == "__main__":
main()