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mmedit.models.editors.basicvsr.basicvsr

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Classes

BasicVSR

BasicVSR model for video super-resolution.

class mmedit.models.editors.basicvsr.basicvsr.BasicVSR(generator, pixel_loss, ensemble=None, train_cfg=None, test_cfg=None, init_cfg=None, data_preprocessor=None)[源代码]

Bases: mmedit.models.BaseEditModel

BasicVSR model for video super-resolution.

Note that this model is used for IconVSR.

Paper:

BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond, CVPR, 2021

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

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

  • ensemble (dict) – Config for ensemble. Default: None.

  • 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.

check_if_mirror_extended(lrs)[源代码]

Check whether the input is a mirror-extended sequence.

If mirror-extended, the i-th (i=0, …, t-1) frame is equal to the (t-1-i)-th frame.

参数

lrs (tensor) – Input LR images with shape (n, t, c, h, w)

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

Forward inference. Returns predictions of validation, testing.

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

predictions.

返回类型

List[EditDataSample]

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