import os
from typing import Callable, Optional
import numpy as np
from tonic.dataset import Dataset
from tonic.download_utils import extract_archive
from tonic.io import read_aedat4
[docs]class CIFAR10DVS(Dataset):
"""`CIFAR10-DVS <https://www.frontiersin.org/articles/10.3389/fnins.2017.00309/full>`_
::
@article{li2017cifar10,
title={Cifar10-dvs: an event-stream dataset for object classification},
author={Li, Hongmin and Liu, Hanchao and Ji, Xiangyang and Li, Guoqi and Shi, Luping},
journal={Frontiers in neuroscience},
volume={11},
pages={309},
year={2017},
publisher={Frontiers}
}
Parameters:
save_to (string): Location to save files to on disk.
transform (callable, optional): A callable of transforms to apply to the data.
target_transform (callable, optional): A callable of transforms to apply to the targets/labels.
transforms (callable, optional): A callable of transforms that is applied to both data and
labels at the same time.
"""
url = "https://figshare.com/ndownloader/files/38023437"
filename = "CIFAR10DVS.zip"
file_md5 = "ce3a4a0682dc0943703bd8f749a7701c"
data_filename = [
"airplane.zip",
"automobile.zip",
"bird.zip",
"cat.zip",
"deer.zip",
"dog.zip",
"frog.zip",
"horse.zip",
"ship.zip",
"truck.zip",
]
folder_name = ""
dtype = np.dtype(
[("t", np.uint64), ("x", np.uint16), ("y", np.uint16), ("p", bool)]
)
ordering = dtype.names
sensor_size = (128, 128, 2)
classes = {
"airplane": 0,
"automobile": 1,
"bird": 2,
"cat": 3,
"deer": 4,
"dog": 5,
"frog": 6,
"horse": 7,
"ship": 8,
"truck": 9,
}
def __init__(
self,
save_to: str,
transform: Optional[Callable] = None,
target_transform: Optional[Callable] = None,
transforms: Optional[Callable] = None,
):
super().__init__(
save_to,
transform=transform,
target_transform=target_transform,
transforms=transforms,
)
if not self._check_exists():
self.download()
for filename in self.data_filename:
extract_archive(os.path.join(self.location_on_system, filename))
file_path = os.path.join(self.location_on_system, self.folder_name)
for path, dirs, files in os.walk(file_path):
dirs.sort()
for file in files:
if file.endswith("aedat4"):
self.data.append(os.path.join(path, file))
label_number = self.classes[os.path.basename(path)]
self.targets.append(label_number)
[docs] def __getitem__(self, index):
"""
Returns:
a tuple of (events, target) where target is the index of the target class.
"""
events = read_aedat4(self.data[index])
events.dtype.names = ["t", "x", "y", "p"]
target = self.targets[index]
if self.transform is not None:
events = self.transform(events)
if self.target_transform is not None:
target = self.target_transform(target)
if self.transforms is not None:
events, target = self.transforms(events, target)
return events, target
[docs] def __len__(self):
return len(self.data)
def _check_exists(self):
return (
self._is_file_present()
and self._folder_contains_at_least_n_files_of_type(1000, ".aedat4")
)
