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Types & classes54 in github.com/ahmetgunduz/Real-time-GesRec

⨍ Functions 324◇ Types & classes 54
↓ 25 callersClassAverageMeter
Computes and stores the average and current value
utils.py:9
↓ 21 callersClassNormalize
Normalize an tensor image with mean and standard deviation. Given mean: (R, G, B) and std: (R, G, B), will normalize each channel of the torch
spatial_transforms.py:95
↓ 16 callersClassFire
models/squeezenet.py:17
↓ 9 callersClassCompose
target_transforms.py:5
↓ 9 callersClassToTensor
Convert a ``PIL.Image`` or ``numpy.ndarray`` to tensor. Converts a PIL.Image or numpy.ndarray (H x W x C) in the range [0, 255] to a torch.Flo
spatial_transforms.py:40
↓ 8 callersClassScale
Rescale the input PIL.Image to the given size. Args: size (sequence or int): Desired output size. If size is a sequence like (
spatial_transforms.py:126
↓ 7 callersClassCenterCrop
Crops the given PIL.Image at the center. Args: size (sequence or int): Desired output size of the crop. If size is an int inst
spatial_transforms.py:171
↓ 7 callersClassClassLabel
target_transforms.py:17
↓ 7 callersClassResNet
models/resnet.py:109
↓ 6 callersClassLogger
utils.py:28
↓ 6 callersClassQueue
utils.py:51
↓ 4 callersClassTemporalCenterCrop
Temporally crop the given frame indices at a center. If the number of frames is less than the size, loop the indices as many times as necessa
temporal_transforms.py:56
↓ 4 callersClassTemporalRandomCrop
Temporally crop the given frame indices at a random location. If the number of frames is less than the size, loop the indices as many times a
temporal_transforms.py:96
↓ 3 callersClassEgoGesture
Args: root (string): Root directory path. spatial_transform (callable, optional): A function/transform that takes in an PIL imag
datasets/egogesture.py:176
↓ 3 callersClassJester
Args: root (string): Root directory path. spatial_transform (callable, optional): A function/transform that takes in an PIL imag
datasets/jester.py:143
↓ 3 callersClassKinetics
Args: root (string): Root directory path. spatial_transform (callable, optional): A function/transform that takes in an PIL imag
datasets/kinetics.py:163
↓ 3 callersClassNV
Args: root (string): Root directory path. spatial_transform (callable, optional): A function/transform that takes in an PIL imag
datasets/nv.py:177
↓ 3 callersClassResNeXt
models/resnext.py:83
↓ 3 callersClassUCF101
Args: root (string): Root directory path. spatial_transform (callable, optional): A function/transform that takes in an PIL imag
datasets/ucf101.py:139
↓ 2 callersClassMultiScaleCornerCrop
Crop the given PIL.Image to randomly selected size. A crop of size is selected from scales of the original size. A position of cropping is ran
spatial_transforms.py:273
↓ 2 callersClassSqueezeNet
models/squeezenet.py:54
↓ 1 callersClassBlock
Depthwise conv + Pointwise conv
models/mobilenet.py:19
↓ 1 callersClassBottleneck
models/shufflenet.py:34
↓ 1 callersClassC3D
models/c3d.py:19
↓ 1 callersClassCornerCrop
spatial_transforms.py:202
↓ 1 callersClassEgoGestureOnline
Args: root (string): Root directory path. spatial_transform (callable, optional): A function/transform that takes in an PIL imag
datasets/egogesture_online.py:176
↓ 1 callersClassInvertedResidual
models/shufflenetv2.py:42
↓ 1 callersClassKINETICSclassification
utils/eval_kinetics.py:6
↓ 1 callersClassMobileNet
models/mobilenet.py:34
↓ 1 callersClassMobileNetV2
models/mobilenetv2.py:70
↓ 1 callersClassMultiScaleRandomCrop
spatial_transforms.py:342
↓ 1 callersClassNVOnline
Args: root (string): Root directory path. spatial_transform (callable, optional): A function/transform that takes in an PIL imag
datasets/nv_online.py:172
↓ 1 callersClassResNetL
models/resnetl.py:108
↓ 1 callersClassShuffleNet
models/shufflenet.py:69
↓ 1 callersClassShuffleNetV2
models/shufflenetv2.py:106
↓ 1 callersClassVideoID
target_transforms.py:23
ClassBasicBlock
models/resnetl.py:37
ClassBasicBlock
models/resnet.py:38
ClassBottleneck
models/resnetl.py:69
ClassBottleneck
models/resnet.py:70
ClassCompose
Composes several transforms together. Args: transforms (list of ``Transform`` objects): list of transforms to compose. Example:
spatial_transforms.py:16
ClassDropout
spatial_transforms.py:516
ClassGaussian_blur
spatial_transforms.py:471
ClassInvertedResidual
models/mobilenetv2.py:30
ClassLoopPadding
temporal_transforms.py:5
ClassMultiplyValues
spatial_transforms.py:544
ClassRandomHorizontalFlip
Horizontally flip the given PIL.Image randomly with a probability of 0.5.
spatial_transforms.py:255
ClassRandomResize
spatial_transforms.py:454
ClassRandomRotate
spatial_transforms.py:439
ClassResNeXtBottleneck
models/resnext.py:35
ClassSaltImage
spatial_transforms.py:488
ClassSpatialElasticDisplacement
spatial_transforms.py:378
ClassTemporalBeginCrop
Temporally crop the given frame indices at a beginning. If the number of frames is less than the size, loop the indices as many times as nece
temporal_transforms.py:26
ClassUCFclassification
utils/eval_ucf101.py:6