from typing import Callable, Dict, Optional, Tuple
import spikingjelly.datasets as sjds
import scipy.io
from torchvision.datasets.utils import extract_archive
import os
import multiprocessing
from concurrent.futures import ThreadPoolExecutor
import time
import shutil
from .. import configure
from ..datasets import np_savez
[文档]class ASLDVS(sjds.NeuromorphicDatasetFolder):
def __init__(
self,
root: str,
data_type: str = 'event',
frames_number: int = None,
split_by: str = None,
duration: int = None,
custom_integrate_function: Callable = None,
custom_integrated_frames_dir_name: str = None,
transform: Optional[Callable] = None,
target_transform: Optional[Callable] = None,
) -> None:
"""
The ASL-DVS dataset, which is proposed by `Graph-based Object Classification for Neuromorphic Vision Sensing <https://openaccess.thecvf.com/content_ICCV_2019/html/Bi_Graph-Based_Object_Classification_for_Neuromorphic_Vision_Sensing_ICCV_2019_paper.html>`_.
Refer to :class:`spikingjelly.datasets.NeuromorphicDatasetFolder` for more details about params information.
"""
super().__init__(root, None, data_type, frames_number, split_by, duration, custom_integrate_function, custom_integrated_frames_dir_name, transform,
target_transform)
[文档] @staticmethod
def resource_url_md5() -> list:
'''
:return: A list ``url`` that ``url[i]`` is a tuple, which contains the i-th file's name, download link, and MD5
:rtype: list
'''
print('The ICCV2019_DVS_dataset.zip is packed by dropbox. We find that the MD5 of this zip file can change. So, MD5 check will not be used for this ASL-DVS dataset.')
url = 'https://www.dropbox.com/sh/ibq0jsicatn7l6r/AACNrNELV56rs1YInMWUs9CAa?dl=0'
return [
('ICCV2019_DVS_dataset.zip', url, None)
]
[文档] @staticmethod
def downloadable() -> bool:
'''
:return: Whether the dataset can be directly downloaded by python codes. If not, the user have to download it manually
:rtype: bool
'''
return False
[文档] @staticmethod
def load_origin_data(file_name: str) -> Dict:
'''
:param file_name: path of the events file
:type file_name: str
:return: a dict whose keys are ``['t', 'x', 'y', 'p']`` and values are ``numpy.ndarray``
:rtype: Dict
This function defines how to read the origin binary data.
'''
events = scipy.io.loadmat(file_name)
events = {
't': events['ts'].squeeze(),
'x': 239 - events['x'].squeeze(),
'y': 179 - events['y'].squeeze(),
'p': events['pol'].squeeze()
}
return events
[文档] @staticmethod
def get_H_W() -> Tuple:
'''
:return: A tuple ``(H, W)``, where ``H`` is the height of the data and ``W` is the weight of the data.
For example, this function returns ``(128, 128)`` for the DVS128 Gesture dataset.
:rtype: tuple
'''
return 180, 240
[文档] @staticmethod
def read_mat_save_to_np(mat_file: str, np_file: str):
events = ASLDVS.load_origin_data(mat_file)
np_savez(np_file,
t=events['t'],
x=events['x'],
y=events['y'],
p=events['p']
)
print(f'Save [{mat_file}] to [{np_file}].')
[文档] @staticmethod
def create_events_np_files(extract_root: str, events_np_root: str):
'''
:param extract_root: Root directory path which saves extracted files from downloaded files
:type extract_root: str
:param events_np_root: Root directory path which saves events files in the ``npz`` format
:type events_np_root:
:return: None
This function defines how to convert the origin binary data in ``extract_root`` to ``npz`` format and save converted files in ``events_np_root``.
'''
t_ckp = time.time()
with ThreadPoolExecutor(max_workers=min(multiprocessing.cpu_count(), configure.max_threads_number_for_datasets_preprocess)) as tpe:
sub_threads = []
for class_name in os.listdir(extract_root):
mat_dir = os.path.join(extract_root, class_name)
np_dir = os.path.join(events_np_root, class_name)
os.mkdir(np_dir)
print(f'Mkdir [{np_dir}].')
for bin_file in os.listdir(mat_dir):
source_file = os.path.join(mat_dir, bin_file)
target_file = os.path.join(np_dir, os.path.splitext(bin_file)[0] + '.npz')
print(f'Start to convert [{source_file}] to [{target_file}].')
sub_threads.append(tpe.submit(ASLDVS.read_mat_save_to_np, source_file,
target_file))
for sub_thread in sub_threads:
if sub_thread.exception():
print(sub_thread.exception())
exit(-1)
print(f'Used time = [{round(time.time() - t_ckp, 2)}s].')