utils.datasets.PropheseeDataModule

utils.datasets.PropheseeDataModule#

class PropheseeDataModule(name: str, root='./data', batch_size=4, num_steps=128, time_step=16, num_load_file=8, num_workers=4)[source]#

Bases: DataModule

Base class for Prophesee dataset data modules

Warning

This class can only be used as a base class for inheritance.

The create_dataset method must be overridden in the child class.

Parameters:

  • name (str) – The name of the dataset to download. Supported gen1 and 1mpx.

  • root (str, optional) – The directory where datasets are stored. Defaults to “./data”.

  • batch_size (int, optional) – Number of elements in a batch. Defaults to 4.

  • num_steps (int, optional) – Number of frames. Defaults to 16.

  • time_step (int, optional) – Time between frames. Defaults to 16.

  • num_load_file (int, optional) – Number of concurrently open files in each thread. Defaults to 8.

  • num_workers (int, optional) – A positive integer will turn on multi-process data loading with the specified number of loader worker processes. Defaults to 4.

Raises:

ValueError – Invalid dataset name.

Methods

create_dataset

Initializes dataset

get_labels

Returns a list of class names

read_data

Read the dataset images and labels
create_dataset(gt_files: List[str], data_files: List[str]) → IterableDataset[source]#

Initializes dataset

Parameters:

  • gt_files (List[str]) – List of files with targets

  • data_files (List[str]) – List of files with records

Returns:

Ready dataset

Return type:

IterableDataset

get_labels()[source]#

Returns a list of class names

read_data(split: str)[source]#

Read the dataset images and labels

Parameters:

split (str) – “train”, “test” or “val”