Source code for pywick.datasets.ClonedFolderDataset

import random
from .FolderDataset import FolderDataset

[docs]class ClonedFolderDataset(FolderDataset): """ Dataset that can be initialized with a dictionary of internal parameters (useful when trying to clone a FolderDataset) :param data: (list): list of data on which the dataset operates :param meta_data: (dict): parameters that correspond to the target dataset's attributes :param kwargs: (args): variable set of key-value pairs to set as attributes for the dataset """ def __init__(self, data, meta_data, **kwargs): if len(data) == 0: raise (RuntimeError('No data provided')) print('Initializing with %i data items' % len(data)) = data # Source: # generic way of initializing the object for key in meta_data: setattr(self, key, meta_data[key]) for key in kwargs: setattr(self, key, kwargs[key])
[docs]def random_split_dataset(orig_dataset, splitRatio=0.8, random_seed=None): ''' Randomly split the given dataset into two datasets based on the provided ratio :param orig_dataset: (UsefulDataset): dataset to split (of type pywick.datasets.UsefulDataset) :param splitRatio: (float): ratio to use when splitting the data :param random_seed: (int): random seed for replicability of results :return: tuple of split ClonedFolderDatasets ''' random.seed(a=random_seed) # not cloning the dictionary at this point... maybe it should be? orig_dict = orig_dataset.getmeta_data() part1 = [] part2 = [] for i, item in enumerate(orig_dataset.getdata()): if random.random() < splitRatio: part1.append(item) else: part2.append(item) return ClonedFolderDataset(part1, orig_dict), ClonedFolderDataset(part2, orig_dict)