| import numpy as np | |
| import os | |
| from batchgenerators.utilities.file_and_folder_operations import isfile, subfiles | |
| import multiprocessing | |
| def _convert_to_npy(npz_file: str, unpack_segmentation: bool = True, overwrite_existing: bool = False) -> None: | |
| # try: | |
| a = np.load(npz_file) # inexpensive, no compression is done here. This just reads metadata | |
| if overwrite_existing or not isfile(npz_file[:-3] + "npy"): | |
| np.save(npz_file[:-3] + "npy", a['data']) | |
| if unpack_segmentation and (overwrite_existing or not isfile(npz_file[:-4] + "_seg.npy")): | |
| np.save(npz_file[:-4] + "_seg.npy", a['seg']) | |
| def unpack_dataset(folder: str, unpack_segmentation: bool = True, overwrite_existing: bool = False, | |
| num_processes: int = 8): | |
| """ | |
| all npz files in this folder belong to the dataset, unpack them all | |
| """ | |
| with multiprocessing.get_context("spawn").Pool(num_processes) as p: | |
| npz_files = subfiles(folder, True, None, ".npz", True) | |
| p.starmap(_convert_to_npy, zip(npz_files, | |
| [unpack_segmentation] * len(npz_files), | |
| [overwrite_existing] * len(npz_files)) | |
| ) | |