ToTensor3D Albumentations documentation

Convert 3D volume data and masks to PyTorch tensors (D,H,W,C or D,H,W -> C,D,H,W). For 3D medical imaging pipelines; p=1.0 by default.

This transform is designed for 3D medical imaging data. It converts numpy arrays to PyTorch tensors and ensures consistent channel positioning.

For all inputs (volume data and masks): - Input: (D, H, W, C) or (D, H, W) - depth, height, width, [channels] - Output: (C, D, H, W) - channels first format for PyTorch For single-channel input, adds C=1 dimension

Note: This transform always moves channels to first position as this is the standard PyTorch format. For masks that need to stay in DHWC format, use a different transform or handle the transposition after this transform.

This transform always moves channels to first position as this is the standard PyTorch format. For masks that need to stay in DHWC format, use a different transform or handle the transposition after this transform.