import argparse import json import os import pickle from collections import Counter, defaultdict from concurrent.futures import ProcessPoolExecutor, as_completed from pathlib import Path from tqdm import tqdm def inspect_cameras(image_data): """ Record the frame count of every camera entry. A camera is valid only when: frame_count > 0 """ camera_frame_counts = {} if not isinstance(image_data, dict): return camera_frame_counts, [] for camera_name, camera_data in image_data.items(): if not isinstance(camera_data, dict): continue if "image" not in camera_data: continue frames = camera_data["image"] if frames is None: frame_count = 0 else: try: frame_count = len(frames) except TypeError: frame_count = 0 camera_frame_counts[str(camera_name)] = int(frame_count) valid_cameras = sorted( camera_name for camera_name, frame_count in camera_frame_counts.items() if frame_count > 0 ) return camera_frame_counts, valid_cameras def process_one_image_pkl(image_pkl_path_str, source_root_str): """ Worker function executed in a separate process. Only returns camera statistics. The loaded image data remains inside the worker and is released after this function finishes. """ image_pkl_path = Path(image_pkl_path_str) source_root = Path(source_root_str) episode_dir = image_pkl_path.parent try: relative_folder = str(episode_dir.relative_to(source_root)) with open(image_pkl_path, "rb") as f: image_data = pickle.load(f) camera_frame_counts, valid_cameras = inspect_cameras(image_data) empty_cameras = sorted( camera_name for camera_name, frame_count in camera_frame_counts.items() if frame_count == 0 ) return { "success": True, "folder": relative_folder, "num_cameras_in_pkl": len(camera_frame_counts), "num_valid_cameras": len(valid_cameras), "camera_frame_counts": camera_frame_counts, "valid_cameras": valid_cameras, "empty_cameras": empty_cameras, } except Exception as e: try: relative_folder = str(episode_dir.relative_to(source_root)) except Exception: relative_folder = str(episode_dir) return { "success": False, "folder": relative_folder, "image_pkl": str(image_pkl_path), "error": repr(e), } def main(): parser = argparse.ArgumentParser( description=( "Count non-empty cameras in every image.pkl using " "parallel worker processes." ) ) parser.add_argument( "--source_root", type=str, required=True, help="Root directory containing episode folders.", ) parser.add_argument( "--output", type=str, default="camera_count_summary.json", help="Output JSON path.", ) parser.add_argument( "--workers", type=int, default=min(8, os.cpu_count() or 1), help="Number of worker processes. Start with 8 for large image.pkl files.", ) args = parser.parse_args() source_root = Path(args.source_root).resolve() output_path = Path(args.output).resolve() image_pkl_paths = sorted(source_root.rglob("image.pkl")) print(f"Source root: {source_root}") print(f"Found {len(image_pkl_paths)} image.pkl files") print(f"Using {args.workers} worker processes") valid_camera_count_distribution = Counter() folders_by_valid_camera_count = defaultdict(list) episode_details = [] failed_folders = [] with ProcessPoolExecutor(max_workers=args.workers) as executor: futures = [ executor.submit( process_one_image_pkl, str(image_pkl_path), str(source_root), ) for image_pkl_path in image_pkl_paths ] for future in tqdm( as_completed(futures), total=len(futures), desc="Inspecting episodes", ): result = future.result() if result["success"]: result.pop("success") num_valid_cameras = result["num_valid_cameras"] folder = result["folder"] valid_camera_count_distribution[num_valid_cameras] += 1 folders_by_valid_camera_count[num_valid_cameras].append(folder) episode_details.append(result) else: result.pop("success") failed_folders.append(result) # Parallel workers finish in arbitrary order, so sort the results. episode_details.sort(key=lambda item: item["folder"]) failed_folders.sort(key=lambda item: item["folder"]) for folders in folders_by_valid_camera_count.values(): folders.sort() output = { "source_root": str(source_root), "workers": args.workers, "total_folders_with_image_pkl": len(image_pkl_paths), "successfully_processed_folders": len(episode_details), "failed_folders_count": len(failed_folders), "valid_camera_count_distribution": { str(num_cameras): folder_count for num_cameras, folder_count in sorted( valid_camera_count_distribution.items() ) }, "folders_by_valid_camera_count": { str(num_cameras): folders for num_cameras, folders in sorted( folders_by_valid_camera_count.items() ) }, "episode_details": episode_details, "failed_folders": failed_folders, } output_path.parent.mkdir(parents=True, exist_ok=True) with open(output_path, "w", encoding="utf-8") as f: json.dump(output, f, indent=2, ensure_ascii=False) print("\nValid camera count distribution:") for num_cameras, folder_count in sorted( valid_camera_count_distribution.items() ): print( f" {num_cameras} non-empty camera(s): " f"{folder_count} folder(s)" ) print(f"\nSuccessfully processed: {len(episode_details)}") print(f"Failed: {len(failed_folders)}") print(f"Output saved to: {output_path}") if __name__ == "__main__": main()