0.4.2

Maintenance release.

• Modified spatial.ImageTransformer to allow target grid domain to differ from transform.grid() domain.
• Change image tensor creation functions to return non-batched image tensor when num=0 is passed.
• Fix assertion condition when comparing data tensor shape to MetaImage DimSize metadata.
• Fix torch.from_numpy() warning that NumPy array is read-only when reading MetaImage from data blob.
• Fix circle_image() and cshape_image() functions used to create synthetic 2D registration example images.

0.4.1

Minor refactoring of deepali.core and deepali.utils with a few breaking changes.

• Renamed deepali.core.path to deepali.core.pathlib
  • Moved functions make_temp_dir(), temp_dir(), and temp_file() to deepali.core.tempfile.
• Renamed deepali.core.types to deepali.core.typing.
  • Moved TensorCollections related functions to deepali.core.collections.
• Move deepali.utils.cli modules to deepali.core such as
  • deepali.core.argparse
  • deepali.core.environ
  • deepali.core.logging
• Added deepali.utils.imageio library.
  • If installed, use nibabel to read/write NIfTI images instead of SimpleITK.
  • Support direct streaming of .mha MetaImage files from cloud storage (AWS S3).
  • Keep using SimpleITK for all other image file formats.
• Modified Image.read() and Image.write() methods to use deepali.utils.imageio library.
• Use absolute imports between deepali.* packages, relative imports only within.
• Added software citation using Zenodo.

0.3.2

Maintenance release with fix of ImageBatch.__getitem__ handling of int index along channel dimension. Includes support of more batch tensor indexing. Added an introductory tutorial notebook to walk through an image registration with different spatial transforms.

0.3.1

First release of the deepali library with upload of hf-deepali package to PyPI.