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()