places205Dataset#

class places205Dataset(classes=201, path='places205_data', **kwards)#

Bases: DatasetWrapper

A wrapper to the places205 dataset, available at http://places.csail.mit.edu/. The current wrapper class supplyes the required transformations, and also implements the required DatasetWrapper methods.

__init__(classes=201, path='places205_data', **kwards)#

Initializes the places205Dataset wrapper, providing an interface for handling the Places205 dataset. This class is registered under the name ‘Places205’ in the DSFactory.

Parameters:

classes (int, optional) – The number of classes in the dataset. Defaults to 201.
path (str, optional) – The directory where the dataset is stored. Defaults to ‘places205_data’.
**kwargs – Unused keyword arguments, included for compatibility with other dataset constructors.

Methods

`__init__`([classes, path])	Initializes the places205Dataset wrapper, providing an interface for handling the Places205 dataset.
`get_approximation_set`()	returns the approximation data set, to be used for range approximation
`get_class_labels_dict`()	Returns the class_name to index mapping
`get_samples_per_class`(dataset)	Returns the number of samples in each class or None (if the dataset is balanced - None is equivalent to a list with equal numbers) :param dataset: the dataset split :type dataset: Dataset
`get_test_data`()	Returns the test data
`get_train_data`()	Returns the training data
`get_train_pipe_ffcv`(args)	Returns the Dictionary defining for each field the sequence of ffcv Decoders and transforms to apply.
`get_val_data`()	Returns the validation data
`is_imbalanced`()	Always returns False - places205 dataset is balanced

get_test_data()#: Returns the test data

get_train_data()#: Returns the training data

get_val_data()#: Returns the validation data

is_imbalanced()#: Always returns False - places205 dataset is balanced