mmagic.models.base_models.basic_interpolator

Module Contents

Classes

BasicInterpolator

Basic model for video interpolation.

class mmagic.models.base_models.basic_interpolator.BasicInterpolator(generator: dict, pixel_loss: dict, train_cfg: Optional[dict] = None, test_cfg: Optional[dict] = None, required_frames: int = 2, step_frames: int = 1, init_cfg: Optional[dict] = None, data_preprocessor: Optional[dict] = None)

Bases: mmagic.models.base_models.base_edit_model.BaseEditModel

Basic model for video interpolation.

It must contain a generator that takes frames as inputs and outputs an interpolated frame. It also has a pixel-wise loss for training.

Parameters

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

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

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

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

• required_frames (int) – Required frames in each process. Default: 2

• step_frames (int) – Step size of video frame interpolation. Default: 1

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

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

init_cfg

Initialization config dict.

Type

dict, optional

data_preprocessor

Used for pre-processing data sampled by dataloader to the format accepted by forward().

Type

BaseDataPreprocessor

split_frames(input_tensors: torch.Tensor) → torch.Tensor

split input tensors for inference.

Parameters

input_tensors (Tensor) – Tensor of input frames with shape [1, t, c, h, w]

Returns

Split tensor with shape [t-1, 2, c, h, w]

Return type

Tensor

static merge_frames(input_tensors: torch.Tensor, output_tensors: torch.Tensor) → list

merge input frames and output frames.

Interpolate a frame between the given two frames.

Merged from

[[in1, in2], [in2, in3], [in3, in4], …] [[out1], [out2], [out3], …]

to

[in1, out1, in2, out2, in3, out3, in4, …]

Parameters

• input_tensors (Tensor) – The input frames with shape [n, 2, c, h, w]

• output_tensors (Tensor) – The output frames with shape [n, 1, c, h, w].

Returns

The final frames.

Return type

list[np.array]