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github.com/NVlabs/few-shot-vid2vid
/ types & classes
Types & classes
95 in github.com/NVlabs/few-shot-vid2vid
⨍
Functions
455
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Types & classes
95
↓ 15 callers
Class
Resample2d
models/networks/flownet2_pytorch/networks/resample2d_package/resample2d.py:38
↓ 8 callers
Class
tofp16
models/networks/flownet2_pytorch/networks/submodules.py:40
↓ 8 callers
Class
tofp32
models/networks/flownet2_pytorch/networks/submodules.py:48
↓ 6 callers
Class
SPADEConv2d
models/networks/architecture.py:57
↓ 5 callers
Class
StaticCenterCrop
models/networks/flownet2_pytorch/datasets.py:23
↓ 5 callers
Class
StaticRandomCrop
models/networks/flownet2_pytorch/datasets.py:13
↓ 3 callers
Class
ChannelNorm
models/networks/flownet2_pytorch/networks/channelnorm_package/channelnorm.py:31
↓ 3 callers
Class
LabelEmbedder
models/networks/generator.py:506
↓ 2 callers
Class
Correlation
models/networks/flownet2_pytorch/networks/correlation_package/correlation.py:55
↓ 2 callers
Class
FlowGenerator
models/networks/generator.py:456
↓ 2 callers
Class
L1
models/networks/flownet2_pytorch/losses.py:14
↓ 2 callers
Class
L2
models/networks/flownet2_pytorch/losses.py:21
↓ 2 callers
Class
NLayerDiscriminator
models/networks/discriminator.py:61
↓ 2 callers
Class
SPADEResnetBlock
models/networks/architecture.py:71
↓ 2 callers
Class
SynchronizedBatchNorm2d
r"""Applies Batch Normalization over a 4d input that is seen as a mini-batch of 3d inputs .. math:: y = \frac{x - mean[x]}{ \sqrt{Va
models/networks/sync_batchnorm/batchnorm.py:191
↓ 2 callers
Class
Visualizer
util/visualizer.py:19
↓ 1 callers
Class
AdaptiveDiscriminator
models/networks/discriminator.py:104
↓ 1 callers
Class
CallbackContext
models/networks/sync_batchnorm/replicate.py:30
↓ 1 callers
Class
Colorize
util/util.py:208
↓ 1 callers
Class
CustomDatasetDataLoader
data/custom_dataset_data_loader.py:12
↓ 1 callers
Class
DataParallelWithCallback
Data Parallel with a replication callback. An replication callback `__data_parallel_replicate__` of each module will be invoked after being
models/networks/sync_batchnorm/replicate.py:57
↓ 1 callers
Class
FaceRefineModel
models/face_refiner.py:12
↓ 1 callers
Class
FewShotGenerator
models/networks/generator.py:20
↓ 1 callers
Class
FlowNet
models/flownet.py:15
↓ 1 callers
Class
FutureResult
A thread-safe future implementation. Used only as one-to-one pipe.
models/networks/sync_batchnorm/comm.py:18
↓ 1 callers
Class
HTML
util/html.py:13
↓ 1 callers
Class
ImagePool
util/image_pool.py:10
↓ 1 callers
Class
LossCollector
models/loss_collector.py:15
↓ 1 callers
Class
ModelAndLoss
models/networks/flownet2_pytorch/main.py:161
↓ 1 callers
Class
MultiscaleDiscriminator
models/networks/discriminator.py:16
↓ 1 callers
Class
MyDict
models/networks/flownet2_pytorch/models.py:19
↓ 1 callers
Class
MyModel
models/models.py:79
↓ 1 callers
Class
MyPlaylist
data/preprocess/download_youTube_playlist.py:6
↓ 1 callers
Class
SlavePipe
Pipe for master-slave communication.
models/networks/sync_batchnorm/comm.py:46
↓ 1 callers
Class
SyncMaster
An abstract `SyncMaster` object. - During the replication, as the data parallel will trigger an callback of each module, all slave devices should
models/networks/sync_batchnorm/comm.py:56
↓ 1 callers
Class
TestOptions
options/test_options.py:9
↓ 1 callers
Class
TrainOptions
options/train_options.py:9
↓ 1 callers
Class
Trainer
models/trainer.py:22
↓ 1 callers
Class
VGG_Activations
models/networks/vgg.py:45
↓ 1 callers
Class
Vid2VidModel
models/vid2vid_model.py:20
Class
AdaptiveConv2d
models/networks/architecture.py:31
Class
BaseDataLoader
data/base_data_loader.py:7
Class
BaseDataset
data/base_dataset.py:12
Class
BaseModel
models/base_model.py:15
Class
BaseNetwork
models/networks/base_network.py:73
Class
BaseOptions
options/base_options.py:17
Class
ChairsSDHom
models/networks/flownet2_pytorch/datasets.py:250
Class
ChairsSDHomTest
models/networks/flownet2_pytorch/datasets.py:316
Class
ChairsSDHomTrain
models/networks/flownet2_pytorch/datasets.py:312
Class
ChannelNormFunction
models/networks/flownet2_pytorch/networks/channelnorm_package/channelnorm.py:5
Class
ConvN
models/networks/discriminator.py:171
Class
CorrelationFunction
models/networks/flownet2_pytorch/networks/correlation_package/correlation.py:6
Class
DataParallel
models/networks/sync_batchnorm/replicate.py:24
Class
FewshotFaceDataset
data/fewshot_face_dataset.py:17
Class
FewshotPoseDataset
data/fewshot_pose_dataset.py:19
Class
FewshotStreetDataset
data/fewshot_street_dataset.py:16
Class
FlowNet2
models/networks/flownet2_pytorch/models.py:22
Class
FlowNet2C
models/networks/flownet2_pytorch/models.py:184
Class
FlowNet2CS
models/networks/flownet2_pytorch/models.py:350
Class
FlowNet2CSS
models/networks/flownet2_pytorch/models.py:415
Class
FlowNet2S
models/networks/flownet2_pytorch/models.py:252
Class
FlowNet2SD
models/networks/flownet2_pytorch/models.py:298
Class
FlowNetC
models/networks/flownet2_pytorch/networks/FlowNetC.py:13
Class
FlowNetFusion
models/networks/flownet2_pytorch/networks/FlowNetFusion.py:11
Class
FlowNetS
models/networks/flownet2_pytorch/networks/FlowNetS.py:15
Class
FlowNetSD
models/networks/flownet2_pytorch/networks/FlowNetSD.py:11
Class
FlyingChairs
models/networks/flownet2_pytorch/datasets.py:114
Class
FlyingThings
models/networks/flownet2_pytorch/datasets.py:175
Class
FlyingThingsClean
models/networks/flownet2_pytorch/datasets.py:242
Class
FlyingThingsFinal
models/networks/flownet2_pytorch/datasets.py:246
Class
GANLoss
models/networks/loss.py:17
Class
ImageFolder
data/image_folder.py:92
Class
ImagesFromFolder
models/networks/flownet2_pytorch/datasets.py:320
Class
IteratorTimer
models/networks/flownet2_pytorch/utils/tools.py:98
Class
KLDLoss
models/networks/loss.py:140
Class
L1Loss
models/networks/flownet2_pytorch/losses.py:28
Class
L2Loss
models/networks/flownet2_pytorch/losses.py:40
Class
LMDBDataset
data/lmdb_dataset.py:16
Class
MaskedL1Loss
models/networks/loss.py:130
Class
MpiSintel
models/networks/flownet2_pytorch/datasets.py:30
Class
MpiSintelClean
models/networks/flownet2_pytorch/datasets.py:106
Class
MpiSintelFinal
models/networks/flownet2_pytorch/datasets.py:110
Class
MultiScale
models/networks/flownet2_pytorch/losses.py:52
Class
NormalConv2d
models/networks/architecture.py:20
Class
NormalConvTranspose2d
models/networks/architecture.py:25
Class
NormalNorm
models/networks/architecture.py:50
Class
Resample2dFunction
models/networks/flownet2_pytorch/networks/resample2d_package/resample2d.py:5
Class
SPADE
models/networks/normalization.py:18
Class
SynchronizedBatchNorm1d
r"""Applies Synchronized Batch Normalization over a 2d or 3d input that is seen as a mini-batch. .. math:: y = \frac{x - mean[x]}{ \
models/networks/sync_batchnorm/batchnorm.py:128
Class
SynchronizedBatchNorm3d
r"""Applies Batch Normalization over a 5d input that is seen as a mini-batch of 4d inputs .. math:: y = \frac{x - mean[x]}{ \sqrt{Va
models/networks/sync_batchnorm/batchnorm.py:254
Class
TimerBlock
models/networks/flownet2_pytorch/utils/tools.py:24
Class
TorchTestCase
models/networks/sync_batchnorm/unittest.py:23
Class
VGGLoss
models/networks/loss.py:107
Class
Vgg19
models/networks/vgg.py:13
Class
_SynchronizedBatchNorm
models/networks/sync_batchnorm/batchnorm.py:38