2122 - fixes subprocess transforms

monai/transforms/__init__.py

@@ -354,6 +354,8 @@
     RepeatChannelD,
     RepeatChannelDict,
     SelectItemsd,
+    SelectItemsD,
+    SelectItemsDict,
     SimulateDelayd,
     SimulateDelayD,
     SimulateDelayDict,
@@ -395,6 +397,7 @@
     img_bounds,
     in_bounds,
     is_empty,
+    is_positive,
     map_binary_to_indices,
     map_spatial_axes,
     rand_choice,

monai/transforms/croppad/array.py

@@ -26,6 +26,7 @@
     compute_divisible_spatial_size,
     generate_pos_neg_label_crop_centers,
     generate_spatial_bounding_box,
+    is_positive,
     map_binary_to_indices,
     weighted_patch_samples,
 )
@@ -400,7 +401,14 @@ class CropForeground(Transform):
               [0, 1, 3, 2, 0],
               [0, 1, 2, 1, 0],
               [0, 0, 0, 0, 0]]])  # 1x5x5, single channel 5x5 image
-        cropper = CropForeground(select_fn=lambda x: x > 1, margin=0)
+
+
+        def threshold_at_one(x):
+            # threshold at 1
+            return x > 1
+
+
+        cropper = CropForeground(select_fn=threshold_at_one, margin=0)
         print(cropper(image))
         [[[2, 1],
           [3, 2],
@@ -410,7 +418,7 @@ class CropForeground(Transform):
 
     def __init__(
         self,
-        select_fn: Callable = lambda x: x > 0,
+        select_fn: Callable = is_positive,
         channel_indices: Optional[IndexSelection] = None,
         margin: Union[Sequence[int], int] = 0,
         return_coords: bool = False,
@@ -725,7 +733,7 @@ class BoundingRect(Transform):
         select_fn: function to select expected foreground, default is to select values > 0.
     """
 
-    def __init__(self, select_fn: Callable = lambda x: x > 0) -> None:
+    def __init__(self, select_fn: Callable = is_positive) -> None:
         self.select_fn = select_fn
 
     def __call__(self, img: np.ndarray) -> np.ndarray:

monai/transforms/croppad/dictionary.py

@@ -37,7 +37,12 @@
 )
 from monai.transforms.inverse import InvertibleTransform
 from monai.transforms.transform import MapTransform, Randomizable
-from monai.transforms.utils import generate_pos_neg_label_crop_centers, map_binary_to_indices, weighted_patch_samples
+from monai.transforms.utils import (
+    generate_pos_neg_label_crop_centers,
+    is_positive,
+    map_binary_to_indices,
+    weighted_patch_samples,
+)
 from monai.utils import ImageMetaKey as Key
 from monai.utils import Method, NumpyPadMode, ensure_tuple, ensure_tuple_rep, fall_back_tuple
 from monai.utils.enums import InverseKeys
@@ -572,7 +577,7 @@ def __init__(
         self,
         keys: KeysCollection,
         source_key: str,
-        select_fn: Callable = lambda x: x > 0,
+        select_fn: Callable = is_positive,
         channel_indices: Optional[IndexSelection] = None,
         margin: int = 0,
         k_divisible: Union[Sequence[int], int] = 1,
@@ -948,7 +953,7 @@ def __init__(
         self,
         keys: KeysCollection,
         bbox_key_postfix: str = "bbox",
-        select_fn: Callable = lambda x: x > 0,
+        select_fn: Callable = is_positive,
         allow_missing_keys: bool = False,
     ):
         super().__init__(keys, allow_missing_keys)

monai/transforms/intensity/dictionary.py

@@ -102,6 +102,8 @@
     "RandGaussianSharpenDict",
     "RandHistogramShiftD",
     "RandHistogramShiftDict",
+    "RandRicianNoiseD",
+    "RandRicianNoiseDict",
 ]
 
 

monai/transforms/post/array.py

@@ -33,6 +33,7 @@
     "LabelToContour",
     "MeanEnsemble",
     "VoteEnsemble",
+    "ProbNMS",
 ]
 
 
@@ -74,7 +75,7 @@ def __call__(
             softmax: whether to execute softmax function on model output before transform.
                 Defaults to ``self.softmax``.
             other: callable function to execute other activation layers, for example:
-                `other = lambda x: torch.tanh(x)`. Defaults to ``self.other``.
+                `other = torch.tanh`. Defaults to ``self.other``.
 
         Raises:
             ValueError: When ``sigmoid=True`` and ``softmax=True``. Incompatible values.

monai/transforms/post/dictionary.py

@@ -57,6 +57,9 @@
     "DecollateD",
     "DecollateDict",
     "Decollated",
+    "ProbNMSd",
+    "ProbNMSD",
+    "ProbNMSDict",
 ]
 
 
@@ -83,7 +86,7 @@ def __init__(
             softmax: whether to execute softmax function on model output before transform.
                 it also can be a sequence of bool, each element corresponds to a key in ``keys``.
             other: callable function to execute other activation layers,
-                for example: `other = lambda x: torch.tanh(x)`. it also can be a sequence of Callable, each
+                for example: `other = torch.tanh`. it also can be a sequence of Callable, each
                 element corresponds to a key in ``keys``.
             allow_missing_keys: don't raise exception if key is missing.
 

monai/transforms/utility/array.py

@@ -41,6 +41,7 @@
     "CastToType",
     "ToTensor",
     "ToNumpy",
+    "ToPIL",
     "Transpose",
     "SqueezeDim",
     "DataStats",

monai/transforms/utility/dictionary.py

@@ -53,84 +53,90 @@
 from monai.utils import ensure_tuple, ensure_tuple_rep
 
 __all__ = [
-    "Identityd",
-    "AsChannelFirstd",
-    "AsChannelLastd",
+    "AddChannelD",
+    "AddChannelDict",
     "AddChanneld",
-    "EnsureChannelFirstd",
-    "RepeatChanneld",
-    "RemoveRepeatedChanneld",
-    "SplitChanneld",
-    "CastToTyped",
-    "ToTensord",
-    "ToNumpyd",
-    "ToPILd",
-    "DeleteItemsd",
-    "SelectItemsd",
-    "SqueezeDimd",
-    "DataStatsd",
-    "SimulateDelayd",
-    "CopyItemsd",
-    "ConcatItemsd",
-    "Lambdad",
-    "RandLambdad",
-    "LabelToMaskd",
-    "FgBgToIndicesd",
-    "ConvertToMultiChannelBasedOnBratsClassesd",
+    "AddExtremePointsChannelD",
+    "AddExtremePointsChannelDict",
     "AddExtremePointsChanneld",
-    "TorchVisiond",
-    "RandTorchVisiond",
-    "MapLabelValued",
-    "IdentityD",
-    "IdentityDict",
     "AsChannelFirstD",
     "AsChannelFirstDict",
+    "AsChannelFirstd",
     "AsChannelLastD",
     "AsChannelLastDict",
-    "AddChannelD",
-    "AddChannelDict",
+    "AsChannelLastd",
+    "CastToTypeD",
+    "CastToTypeDict",
+    "CastToTyped",
+    "ConcatItemsD",
+    "ConcatItemsDict",
+    "ConcatItemsd",
+    "ConvertToMultiChannelBasedOnBratsClassesD",
+    "ConvertToMultiChannelBasedOnBratsClassesDict",
+    "ConvertToMultiChannelBasedOnBratsClassesd",
+    "CopyItemsD",
+    "CopyItemsDict",
+    "CopyItemsd",
+    "DataStatsD",
+    "DataStatsDict",
+    "DataStatsd",
+    "DeleteItemsD",
+    "DeleteItemsDict",
+    "DeleteItemsd",
     "EnsureChannelFirstD",
     "EnsureChannelFirstDict",
+    "EnsureChannelFirstd",
+    "FgBgToIndicesD",
+    "FgBgToIndicesDict",
+    "FgBgToIndicesd",
+    "IdentityD",
+    "IdentityDict",
+    "Identityd",
+    "LabelToMaskD",
+    "LabelToMaskDict",
+    "LabelToMaskd",
+    "LambdaD",
+    "LambdaDict",
+    "Lambdad",
+    "MapLabelValueD",
+    "MapLabelValueDict",
+    "MapLabelValued",
     "RandLambdaD",
     "RandLambdaDict",
-    "RepeatChannelD",
-    "RepeatChannelDict",
+    "RandLambdad",
+    "RandTorchVisionD",
+    "RandTorchVisionDict",
+    "RandTorchVisiond",
     "RemoveRepeatedChannelD",
     "RemoveRepeatedChannelDict",
+    "RemoveRepeatedChanneld",
+    "RepeatChannelD",
+    "RepeatChannelDict",
+    "RepeatChanneld",
+    "SelectItemsD",
+    "SelectItemsDict",
+    "SelectItemsd",
+    "SimulateDelayD",
+    "SimulateDelayDict",
+    "SimulateDelayd",
     "SplitChannelD",
     "SplitChannelDict",
-    "CastToTypeD",
-    "CastToTypeDict",
-    "ToTensorD",
-    "ToTensorDict",
-    "DeleteItemsD",
-    "DeleteItemsDict",
+    "SplitChanneld",
     "SqueezeDimD",
     "SqueezeDimDict",
-    "DataStatsD",
-    "DataStatsDict",
-    "SimulateDelayD",
-    "SimulateDelayDict",
-    "CopyItemsD",
-    "CopyItemsDict",
-    "ConcatItemsD",
-    "ConcatItemsDict",
-    "LambdaD",
-    "LambdaDict",
-    "LabelToMaskD",
-    "LabelToMaskDict",
-    "FgBgToIndicesD",
-    "FgBgToIndicesDict",
-    "ConvertToMultiChannelBasedOnBratsClassesD",
-    "ConvertToMultiChannelBasedOnBratsClassesDict",
-    "AddExtremePointsChannelD",
-    "AddExtremePointsChannelDict",
+    "SqueezeDimd",
+    "ToNumpyD",
+    "ToNumpyDict",
+    "ToNumpyd",
+    "ToPILD",
+    "ToPILDict",
+    "ToPILd",
+    "ToTensorD",
+    "ToTensorDict",
+    "ToTensord",
     "TorchVisionD",
     "TorchVisionDict",
-    "RandTorchVisionD",
-    "RandTorchVisionDict",
-    "MapLabelValueD",
-    "MapLabelValueDict",
+    "TorchVisiond",
 ]
 
 
@@ -1062,6 +1068,7 @@ def __call__(self, data: Mapping[Hashable, np.ndarray]) -> Dict[Hashable, np.nda
 ToNumpyD = ToNumpyDict = ToNumpyd
 ToPILD = ToPILDict = ToPILd
 DeleteItemsD = DeleteItemsDict = DeleteItemsd
+SelectItemsD = SelectItemsDict = SelectItemsd
 SqueezeDimD = SqueezeDimDict = SqueezeDimd
 DataStatsD = DataStatsDict = DataStatsd
 SimulateDelayD = SimulateDelayDict = SimulateDelayd

monai/transforms/utils.py

@@ -42,11 +42,13 @@
     "img_bounds",
     "in_bounds",
     "is_empty",
+    "is_positive",
     "zero_margins",
     "rescale_array",
     "rescale_instance_array",
     "rescale_array_int_max",
     "copypaste_arrays",
+    "compute_divisible_spatial_size",
     "resize_center",
     "map_binary_to_indices",
     "weighted_patch_samples",
@@ -97,6 +99,13 @@ def is_empty(img: Union[np.ndarray, torch.Tensor]) -> bool:
     return not (img.max() > img.min())  # use > instead of <= so that an image full of NaNs will result in True
 
 
+def is_positive(img):
+    """
+    Returns a boolean version of `img` where the positive values are converted into True, the other values are False.
+    """
+    return img > 0
+
+
 def zero_margins(img: np.ndarray, margin: int) -> bool:
     """
     Returns True if the values within `margin` indices of the edges of `img` in dimensions 1 and 2 are 0.
@@ -526,7 +535,7 @@ def create_translate(spatial_dims: int, shift: Union[Sequence[float], float]) ->
 
 def generate_spatial_bounding_box(
     img: np.ndarray,
-    select_fn: Callable = lambda x: x > 0,
+    select_fn: Callable = is_positive,
     channel_indices: Optional[IndexSelection] = None,
     margin: Union[Sequence[int], int] = 0,
 ) -> Tuple[List[int], List[int]]:

monai/utils/enums.py

@@ -30,6 +30,7 @@
     "Method",
     "InverseKeys",
     "CommonKeys",
+    "ForwardMode",
 ]