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Source code for eisen.datasets.json

import os
import copy

from torch.utils.data import Dataset
from eisen.utils import read_json_from_file


[docs]class JsonDataset(Dataset): """ This object implements the capability of reading arbitrary data contained in properly structured JSON file into Eisen. The expected JSON file structure is a list of dictionaries. Each entry of the list contains one element of the dataset. Each key of the dictionary stores different information about that data point. Example of JSON structure: .. code-block:: json [ {'image': 'image_file1.png', 'label': 'label_file1.png'}, {'image': 'image_file2.png', 'label': 'label_file2.png'} ] .. note:: This dataset will generate data entries with fields corresponding to what is stored in each entry of the json dataset list. .. code-block:: python from eisen.datasets import JsonDataset dset = JsonDataset('/abs/path/to/data', '/abs/path/to/file.json', transform) """
[docs] def __init__(self, data_dir, json_file, transform=None): """ :param data_dir: the base directory where the data is located :type data_dir: str :param json_file: the name of the json file containing the data :type json_file: str :param transform: a transform object (can be the result of a composition of transforms) :type transform: callable .. code-block:: python from eisen.datasets import JsonDataset dset = JsonDataset( data_dir='/abs/path/to/data', json_file='/abs/path/to/file.json', transform=transform ) <json> [ {"name": "json_file", "type": "string", "value": ""} ] </json> """ json_file = os.path.join(data_dir, json_file) self.json_dataset = read_json_from_file(json_file) self.transform = transform
def __len__(self): return len(self.json_dataset) def __getitem__(self, idx): item = copy.deepcopy(self.json_dataset[idx]) if self.transform: item = self.transform(item) return item

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