VideoExtractionResult
Description
VideoExtractionResult is the frozen dataclass returned by the in-memory methods of CosmosVideoExtractor. All tensors retain their batch dimension.
VideoExtractionResult(
latent,
decoder_input,
representation,
reconstruction,
input_shape_bcthw,
padded_shape_bcthw,
pad_bottom,
pad_right,
original_num_frames,
selected_frame_indices,
temporal_pooling,
)
Attributes
latent(torch.Tensor): deterministic encoder latent with shape[B, C_latent, D_latent, H_latent, W_latent].decoder_input(torch.Tensor): unpooled tensor immediately before the decoder, with shape[B, C, D, H, W].representation(torch.Tensor):[B, C, H, W]with temporal-mean pooling or[B, C, D, H, W]without pooling.reconstruction(torch.Tensor or None): reconstructed[B, 3, T, H, W]video, orNonewhen only encoding was requested.input_shape_bcthw(tuple of int): shape after frame sampling, normalization, and optional resizing, before spatial padding.padded_shape_bcthw(tuple): model-input shape after spatial padding.pad_bottomandpad_right(int): padding applied to the bottom and right edges.original_num_frames(int): number of frames before sampling.selected_frame_indices(tuple of int): zero-based original frame indices retained for the model.temporal_pooling(str): pooling rule used to createrepresentation.pre_decoder_hidden(torch.Tensor): read-only compatibility property that returns the same tensor asdecoder_input.
encode_video fills every field except reconstruction. reconstruct_video and transform_video additionally decode the latent and fill that field.
Example Usage
result = extractor.encode_video(frames)
representation = result.representation
selected = result.selected_frame_indices