ZoneMaestro_code / tools /utils /statistics_asset_distribution.py
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#!/usr/bin/env python3
"""
Statistics of asset library distribution in different datasets.
Analyzes the proportion of 3D assets from different sources.
"""
import json
import os
import sys
from pathlib import Path
from collections import defaultdict
BASE_PATH = Path("/home/v-meiszhang/backup/datas/InternScenes/Layout_info")
def extract_asset_library(uid):
"""Extract the asset library name from a model uid."""
if uid.startswith("objaverse/"):
return "objaverse"
elif uid.startswith("objaverse_old/"):
return "objaverse_old"
elif uid.startswith("partnet_mobility"):
return "partnet_mobility"
elif uid.startswith("3D-FUTURE-model"):
return "3D-FUTURE-model"
elif uid.startswith("hssd-models"):
return "hssd-models"
elif uid.startswith("gen_assets"):
return "gen_assets"
elif uid.startswith("gr100"):
return "gr100"
else:
return "unknown"
def process_dataset(dataset_name, dataset_path):
"""Process a single dataset and return statistics."""
# Statistics containers
total_instances = 0
library_stats = defaultdict(lambda: {"count": 0, "scenes": set()})
category_stats = defaultdict(lambda: defaultdict(int))
scene_count = 0
scenes_with_instances = 0
# Handle different dataset structures
if dataset_name == "arkitscenes":
# ARKitScenes has Training/Validation subdirs
search_dirs = []
for split in ["Training", "Validation"]:
split_path = dataset_path / split
if split_path.exists():
search_dirs.extend(sorted(split_path.iterdir()))
else:
# Other datasets have scenes directly
search_dirs = sorted(dataset_path.iterdir())
# Process all scenes
for scene_dir in search_dirs:
if not scene_dir.is_dir():
continue
scene_count += 1
layout_file = scene_dir / "layout.json"
if not layout_file.exists():
continue
try:
with open(layout_file, 'r') as f:
data = json.load(f)
# layout.json is directly a list of instances
if isinstance(data, list):
instances = data
else:
instances = data.get("instances", [])
if not instances:
continue
scenes_with_instances += 1
for instance in instances:
total_instances += 1
uid = instance.get("model_uid", "")
category = instance.get("category", "unknown")
if not uid:
library = "empty_uid"
else:
library = extract_asset_library(uid)
library_stats[library]["count"] += 1
library_stats[library]["scenes"].add(scene_dir.name)
category_stats[library][category] += 1
except Exception as e:
print(f" Error {scene_dir.name}: {e}", file=sys.stderr)
return {
"total_instances": total_instances,
"library_stats": library_stats,
"category_stats": category_stats,
"scene_count": scene_count,
"scenes_with_instances": scenes_with_instances
}
def print_statistics(dataset_name, stats):
"""Print statistics for a dataset."""
total_instances = stats["total_instances"]
library_stats = stats["library_stats"]
category_stats = stats["category_stats"]
scene_count = stats["scene_count"]
scenes_with_instances = stats["scenes_with_instances"]
print("=" * 80)
print(f"{dataset_name.upper()} ASSET LIBRARY STATISTICS")
print("=" * 80)
print()
print(f"Total scenes: {scene_count}")
print(f"Scenes with instances: {scenes_with_instances}")
print(f"Total instances: {total_instances}")
print()
if total_instances == 0:
print("No instances found!")
print()
return
print("-" * 80)
print("ASSET LIBRARY DISTRIBUTION")
print("-" * 80)
print()
# Sort by count descending
sorted_libs = sorted(library_stats.items(), key=lambda x: x[1]["count"], reverse=True)
print(f"{'Library':<25} {'Count':<10} {'Percentage':<12} {'Scenes':<10}")
print("-" * 80)
for library, stats_data in sorted_libs:
count = stats_data["count"]
percentage = 100.0 * count / total_instances if total_instances > 0 else 0
scenes_count = len(stats_data["scenes"])
print(f"{library:<25} {count:<10} {percentage:>10.2f}% {scenes_count:<10}")
print("-" * 80)
print()
# Print top categories per library
print("-" * 80)
print("TOP CATEGORIES BY ASSET LIBRARY")
print("-" * 80)
print()
for library, _ in sorted_libs[:8]: # Top 8 libraries
categories = category_stats[library]
sorted_cats = sorted(categories.items(), key=lambda x: x[1], reverse=True)
print(f"{library}:")
for category, count in sorted_cats[:5]: # Top 5 categories
percentage = 100.0 * count / library_stats[library]["count"]
print(f" - {category:<30} {count:<8} ({percentage:>6.2f}%)")
print()
print("=" * 80)
print()
def main():
datasets = ["scannet", "arkitscenes", "3rscan", "matterport3d"]
if len(sys.argv) > 1:
# Process specific dataset if provided
datasets = sys.argv[1:]
for dataset_name in datasets:
dataset_path = BASE_PATH / dataset_name
if not dataset_path.exists():
print(f"Warning: {dataset_path} not found, skipping")
continue
print(f"Processing {dataset_name}...")
stats = process_dataset(dataset_name, dataset_path)
print_statistics(dataset_name, stats)
if __name__ == "__main__":
main()