# Author: Bingxin Ke # Last modified: 2024-02-26 import os import tarfile from io import BytesIO import numpy as np import torch from .base_depth_dataset import BaseDepthDataset, DepthFileNameMode, DatasetMode class DIODEDataset(BaseDepthDataset): def __init__( self, **kwargs, ) -> None: super().__init__( # DIODE data parameter min_depth=0.6, max_depth=350, has_filled_depth=False, name_mode=DepthFileNameMode.id, **kwargs, ) def _read_npy_file(self, rel_path): if self.is_tar: if self.tar_obj is None: self.tar_obj = tarfile.open(self.dataset_dir) fileobj = self.tar_obj.extractfile("./" + rel_path) npy_path_or_content = BytesIO(fileobj.read()) else: npy_path_or_content = os.path.join(self.dataset_dir, rel_path) data = np.load(npy_path_or_content).squeeze()[np.newaxis, :, :] return data def _read_depth_file(self, rel_path): depth = self._read_npy_file(rel_path) return depth def _get_data_path(self, index): return self.filenames[index][0], self.filenames[index][1], self.filenames[index][2], self.filenames[index][3:] if len(self.filenames[index]) > 3 else 1 def _get_data_item(self, index): rgb_rel_path, depth_rel_path, mask_rel_path, prompt = self._get_data_path(index=index) rasters = {} # RGB data rasters.update(self._load_rgb_data(rgb_rel_path=rgb_rel_path)) # Depth data if DatasetMode.RGB_ONLY != self.mode: # load data depth_data = self._load_depth_data( depth_rel_path=depth_rel_path, filled_rel_path=None ) rasters.update(depth_data) # valid mask mask = self._read_npy_file(mask_rel_path).astype(bool) mask = torch.from_numpy(mask).bool() rasters["valid_mask_raw"] = mask.clone() rasters["valid_mask_filled"] = mask.clone() other = {"index": index, "rgb_relative_path": rgb_rel_path, "prompt": prompt} return rasters, other