Shortcuts

mmedit.models.editors.tdan.tdan

Module Contents

Classes

TDAN

TDAN model for video super-resolution.

class mmedit.models.editors.tdan.tdan.TDAN(generator, pixel_loss, lq_pixel_loss, train_cfg=None, test_cfg=None, init_cfg=None, data_preprocessor=None)[源代码]

Bases: mmedit.models.BaseEditModel

TDAN model for video super-resolution.

Paper:

TDAN: Temporally-Deformable Alignment Network for Video Super- Resolution, CVPR, 2020

参数
  • generator (dict) – Config for the generator structure.

  • pixel_loss (dict) – Config for pixel-wise loss.

  • lq_pixel_loss (dict) – Config for pixel-wise loss for the LQ images.

  • train_cfg (dict) – Config for training. Default: None.

  • test_cfg (dict) – Config for testing. Default: None.

  • init_cfg (dict, optional) – The weight initialized config for BaseModule.

  • data_preprocessor (dict, optional) – The pre-process config of BaseDataPreprocessor.

forward_train(inputs, data_samples=None, **kwargs)[源代码]

Forward training. Returns dict of losses of training.

参数
  • inputs (torch.Tensor) – batch input tensor collated by data_preprocessor.

  • data_samples (List[BaseDataElement], optional) – data samples collated by data_preprocessor.

返回

Dict of losses.

返回类型

dict

forward_tensor(inputs, data_samples=None, training=False, **kwargs)[源代码]

Forward tensor. Returns result of simple forward.

参数
  • inputs (torch.Tensor) – batch input tensor collated by data_preprocessor.

  • data_samples (List[BaseDataElement], optional) – data samples collated by data_preprocessor.

  • training (bool) – Whether is training. Default: False.

返回

results of forward inference and

forward train.

返回类型

(Tensor | List[Tensor])

Read the Docs v: latest
Versions
master
latest
stable
zyh-doc-notfound-extend
Downloads
pdf
epub
On Read the Docs
Project Home
Builds

Free document hosting provided by Read the Docs.