Code
Hub
Workspaces
Following
Trending
Connect
MCP
copy
Create free account
hub
/
github.com/MCG-NJU/VideoMAE
/ functions
Functions
287 in github.com/MCG-NJU/VideoMAE
⨍
Functions
287
◇
Types & classes
48
↓ 1 callers
Function
tensor_normalize
Normalize a given tensor by subtracting the mean and dividing the std. Args: tensor (tensor): tensor to normalize. mean (tens
ssv2.py:346
↓ 1 callers
Function
train_one_epoch
(model: torch.nn.Module, data_loader: Iterable, optimizer: torch.optim.Optimizer, device:
engine_for_pretraining.py:10
↓ 1 callers
Function
train_one_epoch
(model: torch.nn.Module, criterion: torch.nn.Module, data_loader: Iterable, optimizer: tor
engine_for_finetuning.py:24
↓ 1 callers
Function
transform
(x, y, matrix)
rand_augment.py:126
↓ 1 callers
Function
validation_one_epoch
(data_loader, model, device)
engine_for_finetuning.py:144
Method
__call__
Args: img (PIL Image): Image to be cropped and resized. Returns: PIL Image: Randomly cropped and resized imag
video_transforms.py:767
Method
__call__
(self, clip)
video_transforms.py:912
Method
__call__
Args: img (PIL.Image or numpy.ndarray): List of images to be cropped in format (h, w, c) in numpy.ndarray Returns:
video_transforms.py:923
Method
__call__
(self, clip)
video_transforms.py:958
Method
__call__
(self, clip)
video_transforms.py:988
Method
__call__
Args: img (PIL.Image or numpy.ndarray): List of images to be cropped in format (h, w, c) in numpy.ndarray Returns:
video_transforms.py:1007
Method
__call__
Args: img (PIL.Image or numpy.ndarray): List of images to be cropped in format (h, w, c) in numpy.ndarray Returns:
video_transforms.py:1051
Method
__call__
Args: img (PIL.Image or numpy.ndarray): List of images to be cropped in format (h, w, c) in numpy.ndarray Returns:
video_transforms.py:1107
Method
__call__
Args: img (PIL.Image or numpy.ndarray): List of images to be cropped in format (h, w, c) in numpy.ndarray Returns:
video_transforms.py:1141
Method
__call__
Args: clip (list): list of PIL.Image Returns: list PIL.Image : list of transformed PIL.Image
video_transforms.py:1216
Method
__call__
Args: clip (Tensor): Tensor clip of size (T, C, H, W) to be normalized. Returns: Tensor: Normalized Tensor cl
video_transforms.py:1271
Method
__call__
(self, img_tuple)
transforms.py:18
Method
__call__
(self, img_tuple)
transforms.py:43
Method
__call__
(self, tensor_tuple)
transforms.py:53
Method
__call__
(self, img_tuple)
transforms.py:69
Method
__call__
(self, img_tuple)
transforms.py:86
Method
__call__
(self, img_tuple)
transforms.py:101
Method
__call__
(self, img_tuple)
transforms.py:169
Method
__call__
(self, pic_tuple)
transforms.py:187
Method
__call__
(self, data)
transforms.py:205
Method
__call__
(self, loss, optimizer, clip_grad=None, parameters=None, create_graph=False, update_grad=True)
utils.py:347
Method
__call__
Args: clip (list of numpy.ndarray): clip (list of images) to be converted to tensor.
volume_transforms.py:26
Method
__call__
Args: clip (list of numpy.ndarray): clip (list of images) to be converted to tensor.
volume_transforms.py:81
Method
__call__
(self, array)
volume_transforms.py:129
Method
__call__
(self, images)
datasets.py:26
Method
__call__
(self, x, target)
mixup.py:209
Method
__call__
(self, batch, _=None)
mixup.py:299
Method
__call__
(self)
masking_generator.py:17
Method
__call__
(self, images)
run_videomae_vis.py:37
Method
__call__
(self, img_list)
rand_augment.py:364
Method
__call__
(self, img)
rand_augment.py:468
Method
__call__
(self, input)
random_erasing.py:151
Method
__getattr__
(self, attr)
utils.py:97
Method
__getitem__
(self, index)
kinetics.py:82
Method
__getitem__
(self, index)
kinetics.py:471
Method
__getitem__
(self, index)
ssv2.py:79
Method
__init__
(self, anno_path, data_path, mode='train', clip_len=8, frame_sample_rate=2, crop_size=224, sh
kinetics.py:18
Method
__init__
(self, root, setting, train=True, test_mod
kinetics.py:425
Method
__init__
(self, drop_prob=None)
modeling_finetune.py:24
Method
__init__
( self, dim, num_heads=8, qkv_bias=False, qk_scale=None, attn_drop=0., proj_drop=0., a
modeling_finetune.py:56
Method
__init__
(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., dr
modeling_finetune.py:104
Method
__init__
(self, img_size=224, patch_size=16, in_chans=3, embed_dim=768, num_frames=16, tubelet_size=2)
modeling_finetune.py:137
Method
__init__
(self, img_size=224, patch_size=16, in_chans=3,
modeling_finetune.py:176
Method
__init__
( self, size, scale=(0.08, 1.0), ratio=(3.0 / 4.0, 4.0 / 3.0), interpo
video_transforms.py:705
Method
__init__
(self, transforms)
video_transforms.py:909
Method
__init__
(self, ratio=(3. / 4., 4. / 3.), interpolation='nearest')
video_transforms.py:954
Method
__init__
(self, size, interpolation='nearest')
video_transforms.py:984
Method
__init__
(self, size)
video_transforms.py:1001
Method
__init__
(self, size)
video_transforms.py:1045
Method
__init__
(self, degrees)
video_transforms.py:1094
Method
__init__
(self, size)
video_transforms.py:1135
Method
__init__
(self, brightness=0, contrast=0, saturation=0, hue=0)
video_transforms.py:1185
Method
__init__
(self, mean, std)
video_transforms.py:1267
Method
__init__
(self, anno_path, data_path, mode='train', clip_len=8, crop_size=224, short_side_size=256, new
ssv2.py:16
Method
__init__
(self, img_size=224, patch_size=16, in_chans=3, num_classes=0, embed_dim=768, depth=12, num_h
modeling_pretrain.py:29
Method
__init__
(self, patch_size=16, num_classes=768, embed_dim=768, depth=12, num_heads=12, mlp_ratio=4., q
modeling_pretrain.py:115
Method
__init__
(self, size)
transforms.py:12
Method
__init__
(self, size)
transforms.py:40
Method
__init__
(self, mean, std)
transforms.py:49
Method
__init__
(self, size)
transforms.py:66
Method
__init__
(self, size, interpolation=Image.BILINEAR)
transforms.py:83
Method
__init__
(self, input_size, scales=None, max_distort=1, fix_crop=True, more_fix_crop=True)
transforms.py:93
Method
__init__
(self, roll=False)
transforms.py:166
Method
__init__
(self, div=True)
transforms.py:184
Method
__init__
(self, window_size=20, fmt=None)
utils.py:26
Method
__init__
(self, delimiter="\t")
utils.py:84
Method
__init__
(self, log_dir)
utils.py:168
Method
__init__
(self)
utils.py:344
Method
__init__
(self, channel_nb=3, div_255=True, numpy=False)
volume_transforms.py:21
Method
__init__
(self, channel_nb=3, div_255=True, numpy=False)
volume_transforms.py:76
Method
__init__
(self, args)
datasets.py:10
Method
__init__
(self, mixup_alpha=1., cutmix_alpha=0., cutmix_minmax=None, prob=1.0, switch_prob=0.5, mode='
mixup.py:104
Method
__init__
(self, input_size, mask_ratio)
masking_generator.py:4
Method
__init__
(self, args)
run_videomae_vis.py:21
Method
__init__
(self, name, prob=0.5, magnitude=10, hparams=None)
rand_augment.py:342
Method
__init__
(self, ops, num_layers=2, choice_weights=None)
rand_augment.py:463
Method
__init__
(self, values)
optim_factory.py:39
Method
__init__
( self, probability=0.5, min_area=0.02, max_area=1 / 3, min_aspect=0.3
random_erasing.py:46
Method
__len__
(self)
kinetics.py:495
Method
__repr__
(self)
video_transforms.py:781
Method
__repr__
(self)
video_transforms.py:1280
Method
__repr__
(self)
datasets.py:30
Method
__repr__
(self)
masking_generator.py:11
Method
__repr__
(self)
run_videomae_vis.py:41
Method
__str__
(self)
utils.py:74
Method
__str__
(self)
utils.py:105
Function
_enhance_increasing_level_to_arg
(level, _hparams)
rand_augment.py:212
Function
_enhance_level_to_arg
(level, _hparams)
rand_augment.py:207
Method
_init_weights
(self, m)
modeling_finetune.py:238
Method
_init_weights
(self, m)
modeling_pretrain.py:65
Method
_init_weights
(self, m)
modeling_pretrain.py:140
Method
_init_weights
(self, m)
modeling_pretrain.py:255
Function
_posterize_increasing_level_to_arg
(level, hparams)
rand_augment.py:249
Function
_posterize_original_level_to_arg
(level, _hparams)
rand_augment.py:256
Function
_rotate_level_to_arg
(level, _hparams)
rand_augment.py:200
← previous
next →
101–200 of 287, ranked by callers