# -*- coding: utf-8 -*- # @Organization : Alibaba XR-Lab # @Author : Peihao Li & Lingteng Qiu & Xiaodong Gu & Qi Zuo # @Email : 220019047@link.cuhk.edu.cn # @Time : 2025-03-10 18:47:56 # @Function : dataset base import json import pdb import traceback from abc import ABC, abstractmethod import numpy as np import torch from megfile import smart_exists, smart_open, smart_path_join from PIL import Image class BaseDataset(torch.utils.data.Dataset, ABC): def __init__(self, root_dirs: str, meta_path: str): super().__init__() self.root_dirs = root_dirs self.uids = self._load_uids(meta_path) def __len__(self): return len(self.uids) @abstractmethod def inner_get_item(self, idx): pass def __getitem__(self, idx): try: return self.inner_get_item(idx) except Exception as e: traceback.print_exc() print(f"[DEBUG-DATASET] Error when loading {self.uids[idx]}") # raise e return self.__getitem__((idx + 1) % self.__len__()) @staticmethod def _load_uids(meta_path: str): # meta_path is a json file if meta_path == None: uids = [] else: with open(meta_path, "r") as f: uids = json.load(f) return uids @staticmethod def _load_rgba_image(file_path, bg_color: float = 1.0): """Load and blend RGBA image to RGB with certain background, 0-1 scaled""" rgba = np.array(Image.open(smart_open(file_path, "rb"))) rgba = torch.from_numpy(rgba).float() / 255.0 rgba = rgba.permute(2, 0, 1).unsqueeze(0) rgb = rgba[:, :3, :, :] * rgba[:, 3:4, :, :] + bg_color * ( 1 - rgba[:, 3:, :, :] ) # rgba[:, :3, ...] * rgba[:, 3:, ...] + (1 - rgba[:, 3:, ...]) return rgb @staticmethod def _locate_datadir(root_dirs, uid, locator: str): for root_dir in root_dirs: datadir = smart_path_join(root_dir, uid, locator) if smart_exists(datadir): return root_dir raise FileNotFoundError(f"Cannot find valid data directory for uid {uid}")