warning about the upcoming change of default image_only=True in LoadImage and remove deprecated transform args

monai/data/grid_dataset.py

@@ -21,7 +21,7 @@
 from monai.data.iterable_dataset import IterableDataset
 from monai.data.utils import iter_patch
 from monai.transforms import apply_transform
-from monai.utils import NumpyPadMode, deprecated_arg, ensure_tuple, first, look_up_option
+from monai.utils import NumpyPadMode, ensure_tuple, first, look_up_option
 
 __all__ = ["PatchDataset", "GridPatchDataset", "PatchIter", "PatchIterd"]
 
@@ -175,7 +175,6 @@ class GridPatchDataset(IterableDataset):
 
     """
 
-    @deprecated_arg(name="dataset", new_name="data", since="0.8", msg_suffix="please use `data` instead.")
     def __init__(
         self,
         data: Iterable | Sequence,
@@ -244,7 +243,6 @@ class PatchDataset(Dataset):
 
     """
 
-    @deprecated_arg(name="dataset", new_name="data", since="0.8", msg_suffix="please use `data` instead.")
     def __init__(
         self, data: Sequence, patch_func: Callable, samples_per_image: int = 1, transform: Callable | None = None
     ) -> None:

monai/data/image_writer.py

@@ -270,7 +270,9 @@ def resample_if_needed(
         if affine is not None:
             data_array.affine = convert_to_tensor(affine, track_meta=False)  # type: ignore
         resampler = SpatialResample(mode=mode, padding_mode=padding_mode, align_corners=align_corners, dtype=dtype)
-        output_array = resampler(data_array[None], dst_affine=target_affine, spatial_size=output_spatial_shape)
+        output_array = resampler(
+            data_array[None], dst_affine=target_affine, spatial_size=output_spatial_shape  # type: ignore
+        )
         # convert back at the end
         if isinstance(output_array, MetaTensor):
             output_array.applied_operations = []

monai/data/iterable_dataset.py

@@ -20,7 +20,7 @@
 from monai.data.utils import convert_tables_to_dicts
 from monai.transforms import apply_transform
 from monai.transforms.transform import Randomizable
-from monai.utils import deprecated_arg, optional_import
+from monai.utils import optional_import
 
 pd, _ = optional_import("pandas")
 
@@ -200,7 +200,6 @@ class CSVIterableDataset(IterableDataset):
 
     """
 
-    @deprecated_arg(name="filename", new_name="src", since="0.8", msg_suffix="please use `src` instead.")
     def __init__(
         self,
         src: str | Sequence[str] | Iterable | Sequence[Iterable],
@@ -231,7 +230,6 @@ def __init__(
         self.iters: list[Iterable] = self.reset()
         super().__init__(data=None, transform=transform)  # type: ignore
 
-    @deprecated_arg(name="filename", new_name="src", since="0.8", msg_suffix="please use `src` instead.")
     def reset(self, src: str | Sequence[str] | Iterable | Sequence[Iterable] | None = None):
         """
         Reset the pandas `TextFileReader` iterable object to read data. For more details, please check:

monai/transforms/io/array.py

@@ -44,7 +44,14 @@
 from monai.transforms.utility.array import EnsureChannelFirst
 from monai.utils import GridSamplePadMode
 from monai.utils import ImageMetaKey as Key
-from monai.utils import OptionalImportError, convert_to_dst_type, ensure_tuple, look_up_option, optional_import
+from monai.utils import (
+    OptionalImportError,
+    convert_to_dst_type,
+    deprecated_arg_default,
+    ensure_tuple,
+    look_up_option,
+    optional_import,
+)
 
 nib, _ = optional_import("nibabel")
 Image, _ = optional_import("PIL.Image")
@@ -119,6 +126,7 @@ class LoadImage(Transform):
 
     """
 
+    @deprecated_arg_default("image_only", False, True, since="1.1", replaced="1.3")
     def __init__(
         self,
         reader=None,

monai/transforms/io/dictionary.py

@@ -27,6 +27,7 @@
 from monai.transforms.io.array import LoadImage, SaveImage
 from monai.transforms.transform import MapTransform
 from monai.utils import GridSamplePadMode, ensure_tuple, ensure_tuple_rep
+from monai.utils.deprecate_utils import deprecated_arg_default
 from monai.utils.enums import PostFix
 
 __all__ = ["LoadImaged", "LoadImageD", "LoadImageDict", "SaveImaged", "SaveImageD", "SaveImageDict"]
@@ -69,6 +70,7 @@ class LoadImaged(MapTransform):
 
     """
 
+    @deprecated_arg_default("image_only", False, True, since="1.1", replaced="1.3")
     def __init__(
         self,
         keys: KeysCollection,

monai/transforms/spatial/array.py

@@ -189,13 +189,9 @@ def _post_process(
     def update_meta(self, img, dst_affine):
         img.affine = dst_affine
 
-    @deprecated_arg(
-        name="src_affine", since="0.9", msg_suffix="img should be `MetaTensor`, so affine can be extracted directly."
-    )
     def __call__(
         self,
         img: torch.Tensor,
-        src_affine: NdarrayOrTensor | None = None,
         dst_affine: torch.Tensor | None = None,
         spatial_size: Sequence[int] | torch.Tensor | int | None = None,
         mode: str | int | None = None,
@@ -354,35 +350,19 @@ def update_meta(self, img: torch.Tensor, dst_affine=None, img_dst=None):
             img.meta = deepcopy(img_dst.meta)
             img.meta[Key.FILENAME_OR_OBJ] = original_fname  # keep the original name, the others are overwritten
 
-    @deprecated_arg(
-        name="src_meta", since="0.9", msg_suffix="img should be `MetaTensor`, so affine can be extracted directly."
-    )
-    @deprecated_arg(
-        name="dst_meta", since="0.9", msg_suffix="img_dst should be `MetaTensor`, so affine can be extracted directly."
-    )
-    def __call__(
+    def __call__(  # type: ignore
         self,
         img: torch.Tensor,
         img_dst: torch.Tensor,
-        src_meta: dict | None = None,
-        dst_meta: dict | None = None,
         mode: str | int | None = None,
         padding_mode: str | None = None,
         align_corners: bool | None = None,
         dtype: DtypeLike = None,
     ) -> torch.Tensor:
         """
         Args:
-            img: input image to be resampled to match ``dst_meta``. It currently supports channel-first arrays with
+            img: input image to be resampled to match ``img_dst``. It currently supports channel-first arrays with
                 at most three spatial dimensions.
-            src_meta: Dictionary containing the source affine matrix in the form ``{'affine':src_affine}``.
-                If ``affine`` is not specified, an identity matrix is assumed.  Defaults to ``None``.
-                See also:  https://docs.monai.io/en/stable/transforms.html#spatialresample
-            dst_meta: Dictionary containing the target affine matrix and target spatial shape in the form
-                ``{'affine':src_affine, 'spatial_shape':spatial_size}``. If ``affine`` is  not
-                specified, ``src_affine`` is assumed. If ``spatial_shape`` is not specified, spatial size is
-                automatically computed, containing the previous field of view.  Defaults to ``None``.
-                See also: https://docs.monai.io/en/stable/transforms.html#spatialresample
             mode: {``"bilinear"``, ``"nearest"``} or spline interpolation order 0-5 (integers).
                 Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
                 See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
@@ -402,8 +382,6 @@ def __call__(
                 ``np.float64`` (for best precision). If ``None``, use the data type of input data.
                 To be compatible with other modules, the output data type is always `float32`.
         Raises:
-            RuntimeError: When ``src_meta`` is missing.
-            RuntimeError: When ``dst_meta`` is missing.
             ValueError: When the affine matrix of the source image is not invertible.
         Returns:
             Resampled input tensor or MetaTensor.
@@ -608,7 +586,7 @@ def __call__(
         data_array = self.sp_resample(
             data_array,
             dst_affine=torch.as_tensor(new_affine),
-            spatial_size=actual_shape,
+            spatial_size=actual_shape,  # type: ignore
             mode=mode,
             padding_mode=padding_mode,
             align_corners=align_corners,

monai/transforms/spatial/dictionary.py

@@ -65,7 +65,6 @@
     ensure_tuple_rep,
     fall_back_tuple,
 )
-from monai.utils.deprecate_utils import deprecated_arg
 from monai.utils.enums import PytorchPadMode, TraceKeys
 from monai.utils.module import optional_import
 
@@ -159,19 +158,13 @@ class SpatialResampled(MapTransform, InvertibleTransform):
 
     backend = SpatialResample.backend
 
-    @deprecated_arg(name="meta_keys", since="0.9")
-    @deprecated_arg(name="meta_key_postfix", since="0.9")
-    @deprecated_arg(name="meta_src_keys", since="0.9")
     def __init__(
         self,
         keys: KeysCollection,
         mode: SequenceStr = GridSampleMode.BILINEAR,
         padding_mode: SequenceStr = GridSamplePadMode.BORDER,
         align_corners: Sequence[bool] | bool = False,
         dtype: Sequence[DtypeLike] | DtypeLike = np.float64,
-        meta_keys: KeysCollection | None = None,
-        meta_key_postfix: str = "meta_dict",
-        meta_src_keys: KeysCollection | None = "src_affine",
         dst_keys: KeysCollection | None = "dst_affine",
         allow_missing_keys: bool = False,
     ) -> None:
@@ -238,12 +231,10 @@ class ResampleToMatchd(MapTransform, InvertibleTransform):
 
     backend = ResampleToMatch.backend
 
-    @deprecated_arg(name="template_key", since="0.9")
     def __init__(
         self,
         keys: KeysCollection,
         key_dst: str,
-        template_key: str | None = None,
         mode: SequenceStr = GridSampleMode.BILINEAR,
         padding_mode: SequenceStr = GridSamplePadMode.BORDER,
         align_corners: Sequence[bool] | bool = False,
@@ -323,8 +314,6 @@ class Spacingd(MapTransform, InvertibleTransform):
 
     backend = Spacing.backend
 
-    @deprecated_arg(name="meta_keys", since="0.9")
-    @deprecated_arg(name="meta_key_postfix", since="0.9")
     def __init__(
         self,
         keys: KeysCollection,
@@ -336,8 +325,6 @@ def __init__(
         dtype: Sequence[DtypeLike] | DtypeLike = np.float64,
         scale_extent: bool = False,
         recompute_affine: bool = False,
-        meta_keys: KeysCollection | None = None,
-        meta_key_postfix: str = "meta_dict",
         min_pixdim: Sequence[float] | float | None = None,
         max_pixdim: Sequence[float] | float | None = None,
         allow_missing_keys: bool = False,
@@ -444,16 +431,12 @@ class Orientationd(MapTransform, InvertibleTransform):
 
     backend = Orientation.backend
 
-    @deprecated_arg(name="meta_keys", since="0.9")
-    @deprecated_arg(name="meta_key_postfix", since="0.9")
     def __init__(
         self,
         keys: KeysCollection,
         axcodes: str | None = None,
         as_closest_canonical: bool = False,
         labels: Sequence[tuple[str, str]] | None = (("L", "R"), ("P", "A"), ("I", "S")),
-        meta_keys: KeysCollection | None = None,
-        meta_key_postfix: str = "meta_dict",
         allow_missing_keys: bool = False,
     ) -> None:
         """

monai/transforms/utility/array.py

@@ -59,7 +59,6 @@
     convert_to_numpy,
     convert_to_tensor,
     deprecated,
-    deprecated_arg,
     ensure_tuple,
     look_up_option,
     min_version,
@@ -1421,9 +1420,6 @@ class AddCoordinateChannels(Transform):
 
     backend = [TransformBackends.NUMPY]
 
-    @deprecated_arg(
-        name="spatial_channels", new_name="spatial_dims", since="0.8", msg_suffix="please use `spatial_dims` instead."
-    )
     def __init__(self, spatial_dims: Sequence[int]) -> None:
         self.spatial_dims = spatial_dims
 

monai/transforms/utility/dictionary.py

@@ -1728,9 +1728,6 @@ class AddCoordinateChannelsd(MapTransform):
 
     backend = AddCoordinateChannels.backend
 
-    @deprecated_arg(
-        name="spatial_channels", new_name="spatial_dims", since="0.8", msg_suffix="please use `spatial_dims` instead."
-    )
     def __init__(self, keys: KeysCollection, spatial_dims: Sequence[int], allow_missing_keys: bool = False) -> None:
         super().__init__(keys, allow_missing_keys)
         self.add_coordinate_channels = AddCoordinateChannels(spatial_dims=spatial_dims)

monai/utils/deprecate_utils.py

@@ -289,16 +289,16 @@ def deprecated_arg_default(
     def _decorator(func):
         argname = f"{func.__module__} {func.__qualname__}:{name}"
 
-        msg_prefix = f"Default of argument `{name}`"
+        msg_prefix = f" Current default value of argument `{name}={old_default}`"
 
         if is_replaced:
-            msg_infix = f"was replaced in version {replaced} from `{old_default}` to `{new_default}`."
+            msg_infix = f"was changed in version {replaced} from `{name}={old_default}` to `{name}={new_default}`."
         elif is_deprecated:
-            msg_infix = f"has been deprecated since version {since} from `{old_default}` to `{new_default}`."
+            msg_infix = f"has been deprecated since version {since}."
             if replaced is not None:
-                msg_infix += f" It will be replaced in version {replaced}."
+                msg_infix += f" It will be changed to `{name}={new_default}` in version {replaced}."
         else:
-            msg_infix = f"has been deprecated from `{old_default}` to `{new_default}`."
+            msg_infix = f"has been deprecated from `{name}={old_default}` to `{name}={new_default}`."
 
         msg = f"{msg_prefix} {msg_infix} {msg_suffix}".strip()