get_data_home#

deepinv.utils.get_data_home()[source]#

Return a folder to store deepinv datasets.

This folder can be specified by setting the environment variable``DEEPINV_DATA``, or XDG_DATA_HOME. By default, it is ./datasets.

Returns:

pathlib Path for data home

Return type:

Path

Examples using get_data_home:#

Imaging inverse problems with adversarial networks

Imaging inverse problems with adversarial networks

Bring your own dataset

Bring your own dataset

Loading scientific images

Loading scientific images

Training a reconstruction model

Training a reconstruction model

Tour of MRI functionality in DeepInverse

Tour of MRI functionality in DeepInverse

Remote sensing with satellite images

Remote sensing with satellite images

Self-supervised MRI reconstruction with Artifact2Artifact

Self-supervised MRI reconstruction with Artifact2Artifact

Image transformations for Equivariant Imaging

Image transformations for Equivariant Imaging

Self-supervised learning with Equivariant Imaging for MRI.

Self-supervised learning with Equivariant Imaging for MRI.

Self-supervised learning with Equivariant Splitting

Self-supervised learning with Equivariant Splitting

Low-field MRI denoising without ground truth

Low-field MRI denoising without ground truth

Self-supervised learning from incomplete measurements of multiple operators.

Self-supervised learning from incomplete measurements of multiple operators.

Self-supervised denoising with the Neighbor2Neighbor loss.

Self-supervised denoising with the Neighbor2Neighbor loss.

Self-supervised denoising with the Generalized R2R loss.

Self-supervised denoising with the Generalized R2R loss.

Scan-specific zero-shot SSDU for MRI

Scan-specific zero-shot SSDU for MRI

Self-supervised learning with measurement splitting

Self-supervised learning with measurement splitting

Self-supervised denoising with the SURE loss.

Self-supervised denoising with the SURE loss.

Self-supervised denoising with the UNSURE loss.

Self-supervised denoising with the UNSURE loss.

Learned Iterative Soft-Thresholding Algorithm (LISTA) for compressed sensing

Learned Iterative Soft-Thresholding Algorithm (LISTA) for compressed sensing

Learned iterative custom prior

Learned iterative custom prior

Vanilla Unfolded algorithm for super-resolution

Vanilla Unfolded algorithm for super-resolution