skainet-data-media/sk.ainet.data.media/ImageLayout

ImageLayout

enum ImageLayout : Enum<ImageLayout> (source)

Memory layout for image tensor data.

Different frameworks use different conventions for storing image data:

PyTorch typically uses CHW (channels first)
TensorFlow typically uses HWC (channels last)
Batched versions add a batch dimension at the front

Entries

Height × Width × Channels (e.g., OpenCV, TensorFlow default). Shape: H, W, C

Channels × Height × Width (e.g., PyTorch default). Shape: C, H, W

Batch × Height × Width × Channels (e.g., TensorFlow batched). Shape: N, H, W, C

Batch × Channels × Height × Width (e.g., PyTorch batched). Shape: N, C, H, W

Properties

val channelAxis: Int

Index of the channel dimension in the shape array.

val entries: EnumEntries<ImageLayout>

Returns a representation of an immutable list of all enum entries, in the order they're declared.

val expectedRank: Int

Expected tensor rank for this layout.

val heightAxis: Int

Index of the height dimension in the shape array.

val isBatched: Boolean

Whether this layout includes a batch dimension.

isChannelsFirst

val isChannelsFirst: Boolean

Whether channels are the first spatial dimension (after batch if present).

val widthAxis: Int

Index of the width dimension in the shape array.

Functions

fun batched(): ImageLayout

Convert to batched version of this layout.

fun unbatched(): ImageLayout

Convert to unbatched version of this layout.

fun valueOf(value: String): ImageLayout

Returns the enum constant of this type with the specified name. The string must match exactly an identifier used to declare an enum constant in this type. (Extraneous whitespace characters are not permitted.)

fun values(): Array<ImageLayout>

Returns an array containing the constants of this enum type, in the order they're declared.