def __init__(self,
args,
root,
split,
label_path,
cachedir,
transform=None,
target_transform=None,
input_size=224,
test_gap=50,
train_gap=4,
fps=24,
num_classes=157,
ext='jpg'):
super(DatasetJPG, self).__init__(test_gap, split)
self.num_classes = num_classes
self.transform = transform
self.target_transform = target_transform
self.root = root
self.input_size = input_size
self.fps = fps
self.train_gap = train_gap
self.ext = ext
self.cls2int = self.get_label_map(args.label_file)
self.labels = self.get_labels(label_path, split, self.cls2int)
cachename = '{}/{}_{}.pkl'.format(cachedir, self.__class__.__name__,
split)
self._data = cache(cachename)(self._prepare)(root, self.labels, split)
def __init__(self, args, root, split, labelpath, cachedir, transform=None, target_transform=None, test_gap=50):
Dataset.__init__(self, test_gap, split)
self.num_classes = 174
self.transform = transform
self.target_transform = target_transform
self.cls2int = self.parse_something_labels(args.label_file)
self.labels = self.parse_something_json(labelpath, self.cls2int)
self.root = root
cachename = '{}/{}_{}.pkl'.format(cachedir, self.__class__.__name__, split)
self._data = cache(cachename)(self._prepare)(root, self.labels, split)
def __init__(self, args, root, split, labelpath, cachedir, transform=None, target_transform=None, test_gap=50):
self.num_classes = 27
self.transform = transform
self.target_transform = target_transform
self.cls2int = self.parse_jester_labels(args.label_file)
self.labels = self.parse_jester_csv(labelpath, self.cls2int)
self.root = root
self.test_gap = test_gap
cachename = '{}/{}_{}.pkl'.format(cachedir, self.__class__.__name__, split)
self.data = cache(cachename)(self._prepare)(root, self.labels, split)
def __init__(self, args, root, split, labelpath, cachedir,
transform=None, target_transform=None, input_size=224, test_gap=50):
self.num_classes = 157
self.transform = transform
self.target_transform = target_transform
self.labels = self.parse_charades_csv(labelpath)
self.labels = self.labels[:100]
self.root = root
self.test_gap = test_gap
cachename = '{}/{}_{}.pkl'.format(cachedir, self.__class__.__name__, split)
self._data = cache(cachename)(self._prepare)(root, self.labels, split)
def __init__(self,
args,
root,
split,
labelpath,
cachedir,
transform=None,
target_transform=None,
input_size=224,
test_gap=10):
Dataset.__init__(self, test_gap, split)
self.num_classes = 80
self.transform = transform
self.target_transform = target_transform
self.cls2int = dict((str(x + 1), x) for x in range(80))
self.labels = self.parse_ava_csv(labelpath, self.cls2int)
self.root = root
self.train_gap = 64
self.input_size = input_size
cachename = '{}/{}_{}.pkl'.format(cachedir, self.__class__.__name__,
split)
self._data = cache(cachename)(self._prepare)(root, self.labels, split)
def __init__(self,
args,
root,
split,
label_path,
cachedir,
transform=None,
target_transform=None,
input_size=224,
test_gap=25,
train_gap=4):
Dataset.__init__(self, test_gap, split)
self.num_classes = 400
self.transform = transform
self.target_transform = target_transform
self.cls2int = self.parse_kinetics_labels(args.train_file)
self.labels = self.parse_kinetics_csv(label_path, self.cls2int)
self.root = root
self.train_gap = train_gap
self.input_size = input_size
cachename = '{}/{}_{}.pkl'.format(cachedir, self.__class__.__name__,
split)
self._data = cache(cachename)(self._prepare)(root, self.labels, split)
def __init__(self,
args,
root,
split,
label_path,
cachedir,
transform=None,
target_transform=None,
input_size=224,
test_gap=50,
train_gap=4,
fps=24):
super(Charades, self).__init__(test_gap, split)
self.num_classes = 157
self.transform = transform
self.target_transform = target_transform
self.labels = self.parse_charades_csv(label_path)
self.root = root
self.input_size = input_size
self.fps = fps
self.train_gap = train_gap
cachename = '{}/{}_{}.pkl'.format(cachedir, self.__class__.__name__,
split)
self._data = cache(cachename)(self._prepare)(root, self.labels, split)