Normlize image by given mean and std.

Prepare sample for usage as network input.

Resize sample to given size (width, height).

Crop sample for batch-wise training. Image is of shape CxHxW

Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks).

Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks).

Residual convolution module.

Residual convolution module.

Feature fusion block.

Feature fusion block.

Normlize image by given mean and std.

Normlize image by given mean and std.

Prepare sample for usage as network input.

Prepare sample for usage as network input.

Resize sample to given size (width, height).

Resize sample to given size (width, height).

2D image to patch embedding: (B,C,H,W) -> (B,N,D) Args: img_size: Image size. patch_size: Patch token size. in_chans

2D image to patch embedding: (B,C,H,W) -> (B,N,D) Args: img_size: Image size. patch_size: Patch token size. in_chans