Merge branch 'dev' into fix-he-stain-order

ericspod · web-flow · commit bf720991eb75 · 2025-11-04T13:42:44.000Z
diff --git a/.github/workflows/codeql-analysis.yml b/.github/workflows/codeql-analysis.yml
@@ -42,7 +42,7 @@ jobs:
 
     # Initializes the CodeQL tools for scanning.
     - name: Initialize CodeQL
-      uses: github/codeql-action/init@v3
+      uses: github/codeql-action/init@v4
       with:
         languages: ${{ matrix.language }}
         # If you wish to specify custom queries, you can do so here or in a config file.
@@ -72,4 +72,4 @@ jobs:
         BUILD_MONAI=1 ./runtests.sh --build
 
     - name: Perform CodeQL Analysis
-      uses: github/codeql-action/analyze@v3
+      uses: github/codeql-action/analyze@v4
diff --git a/.github/workflows/docker.yml b/.github/workflows/docker.yml
@@ -37,7 +37,7 @@ jobs:
           python setup.py build
           cat build/lib/monai/_version.py
       - name: Upload version
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v5
         with:
           name: _version.py
           path: build/lib/monai/_version.py
@@ -57,7 +57,7 @@ jobs:
       with:
         ref: dev
     - name: Download version
-      uses: actions/download-artifact@v5
+      uses: actions/download-artifact@v6
       with:
         name: _version.py
     - name: docker_build
diff --git a/.github/workflows/integration.yml b/.github/workflows/integration.yml
@@ -74,7 +74,7 @@ jobs:
       run: ./runtests.sh --build --net
 
     - name: Add reaction
-      uses: peter-evans/create-or-update-comment@v4
+      uses: peter-evans/create-or-update-comment@v5
       with:
         token: ${{ secrets.PR_MAINTAIN }}
         repository: ${{ github.event.client_payload.github.payload.repository.full_name }}
@@ -154,7 +154,7 @@ jobs:
         python -m tests.test_integration_gpu_customization
 
     - name: Add reaction
-      uses: peter-evans/create-or-update-comment@v4
+      uses: peter-evans/create-or-update-comment@v5
       with:
         token: ${{ secrets.PR_MAINTAIN }}
         repository: ${{ github.event.client_payload.github.payload.repository.full_name }}
diff --git a/.github/workflows/pythonapp-min.yml b/.github/workflows/pythonapp-min.yml
@@ -88,6 +88,7 @@ jobs:
       run: |
         which python
         python -m pip install --user --upgrade pip setuptools wheel
+        python -m pip install --user more-itertools>=8.0
     - name: cache weekly timestamp
       id: pip-cache
       run: |
diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
@@ -66,7 +66,7 @@ jobs:
 
     - if: matrix.python-version == '3.9' && startsWith(github.ref, 'refs/tags/')
       name: Upload artifacts
-      uses: actions/upload-artifact@v4
+      uses: actions/upload-artifact@v5
       with:
         name: dist
         path: dist/
@@ -109,7 +109,7 @@ jobs:
           python setup.py build
           cat build/lib/monai/_version.py
       - name: Upload version
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v5
         with:
           name: _version.py
           path: build/lib/monai/_version.py
@@ -127,7 +127,7 @@ jobs:
     steps:
       - uses: actions/checkout@v5
       - name: Download version
-        uses: actions/download-artifact@v5
+        uses: actions/download-artifact@v6
         with:
           name: _version.py
       - name: Set tag
diff --git a/docs/source/transforms.rst b/docs/source/transforms.rst
@@ -37,6 +37,11 @@ Generic Interfaces
 .. autoclass:: MultiSampleTrait
     :members:
 
+`ReduceTrait`
+^^^^^^^^^^^^^^^^^^
+.. autoclass:: ReduceTrait
+    :members:
+
 `Randomizable`
 ^^^^^^^^^^^^^^
 .. autoclass:: Randomizable
@@ -1252,6 +1257,12 @@ Utility
     :members:
     :special-members: __call__
 
+`FlattenSequence`
+""""""""""""""""""""""""
+.. autoclass:: FlattenSequence
+    :members:
+    :special-members: __call__
+
 Dictionary Transforms
 ---------------------
 
@@ -2337,6 +2348,12 @@ Utility (Dict)
     :members:
     :special-members: __call__
 
+`FlattenSequenced`
+"""""""""""""""""""""""""
+.. autoclass:: FlattenSequenced
+    :members:
+    :special-members: __call__
+
 
 MetaTensor
 ^^^^^^^^^^
diff --git a/monai/data/box_utils.py b/monai/data/box_utils.py
@@ -826,7 +826,10 @@ def box_iou(boxes1: NdarrayOrTensor, boxes2: NdarrayOrTensor) -> NdarrayOrTensor
         boxes2: bounding boxes, Mx4 or Mx6 torch tensor or ndarray. The box mode is assumed to be ``StandardMode``
 
     Returns:
-        IoU, with size of (N,M) and same data type as ``boxes1``
+        An array/tensor matching the container type of ``boxes1`` (NumPy ndarray or Torch tensor), always
+        floating-point with size ``(N, M)``:
+        - if ``boxes1`` has a floating-point dtype, the same dtype is used.
+        - if ``boxes1`` has an integer dtype, the result is returned as ``torch.float32``.
 
     """
 
@@ -842,16 +845,18 @@ def box_iou(boxes1: NdarrayOrTensor, boxes2: NdarrayOrTensor) -> NdarrayOrTensor
 
     inter, union = _box_inter_union(boxes1_t, boxes2_t, compute_dtype=COMPUTE_DTYPE)
 
-    # compute IoU and convert back to original box_dtype
+    # compute IoU and convert back to original box_dtype or torch.float32
     iou_t = inter / (union + torch.finfo(COMPUTE_DTYPE).eps)  # (N,M)
+    if not box_dtype.is_floating_point:
+        box_dtype = COMPUTE_DTYPE
     iou_t = iou_t.to(dtype=box_dtype)
 
     # check if NaN or Inf
     if torch.isnan(iou_t).any() or torch.isinf(iou_t).any():
         raise ValueError("Box IoU is NaN or Inf.")
 
     # convert tensor back to numpy if needed
-    iou, *_ = convert_to_dst_type(src=iou_t, dst=boxes1)
+    iou, *_ = convert_to_dst_type(src=iou_t, dst=boxes1, dtype=box_dtype)
     return iou
 
 
@@ -867,7 +872,10 @@ def box_giou(boxes1: NdarrayOrTensor, boxes2: NdarrayOrTensor) -> NdarrayOrTenso
         boxes2: bounding boxes, Mx4 or Mx6 torch tensor or ndarray. The box mode is assumed to be ``StandardMode``
 
     Returns:
-        GIoU, with size of (N,M) and same data type as ``boxes1``
+        An array/tensor matching the container type of ``boxes1`` (NumPy ndarray or Torch tensor), always
+        floating-point with size ``(N, M)``:
+        - if ``boxes1`` has a floating-point dtype, the same dtype is used.
+        - if ``boxes1`` has an integer dtype, the result is returned as ``torch.float32``.
 
     Reference:
         https://giou.stanford.edu/GIoU.pdf
@@ -904,12 +912,15 @@ def box_giou(boxes1: NdarrayOrTensor, boxes2: NdarrayOrTensor) -> NdarrayOrTenso
 
     # GIoU
     giou_t = iou - (enclosure - union) / (enclosure + torch.finfo(COMPUTE_DTYPE).eps)
+    if not box_dtype.is_floating_point:
+        box_dtype = COMPUTE_DTYPE
     giou_t = giou_t.to(dtype=box_dtype)
+
     if torch.isnan(giou_t).any() or torch.isinf(giou_t).any():
         raise ValueError("Box GIoU is NaN or Inf.")
 
     # convert tensor back to numpy if needed
-    giou, *_ = convert_to_dst_type(src=giou_t, dst=boxes1)
+    giou, *_ = convert_to_dst_type(src=giou_t, dst=boxes1, dtype=box_dtype)
     return giou
 
 
@@ -925,7 +936,10 @@ def box_pair_giou(boxes1: NdarrayOrTensor, boxes2: NdarrayOrTensor) -> NdarrayOr
         boxes2: bounding boxes, same shape with boxes1. The box mode is assumed to be ``StandardMode``
 
     Returns:
-        paired GIoU, with size of (N,) and same data type as ``boxes1``
+        An array/tensor matching the container type of ``boxes1`` (NumPy ndarray or Torch tensor), always
+        floating-point with size ``(N, )``:
+        - if ``boxes1`` has a floating-point dtype, the same dtype is used.
+        - if ``boxes1`` has an integer dtype, the result is returned as ``torch.float32``.
 
     Reference:
         https://giou.stanford.edu/GIoU.pdf
@@ -982,12 +996,15 @@ def box_pair_giou(boxes1: NdarrayOrTensor, boxes2: NdarrayOrTensor) -> NdarrayOr
     enclosure = torch.prod(wh, dim=-1, keepdim=False)  # (N,)
 
     giou_t: torch.Tensor = iou - (enclosure - union) / (enclosure + torch.finfo(COMPUTE_DTYPE).eps)  # type: ignore
+    if not box_dtype.is_floating_point:
+        box_dtype = COMPUTE_DTYPE
     giou_t = giou_t.to(dtype=box_dtype)  # (N,spatial_dims)
+
     if torch.isnan(giou_t).any() or torch.isinf(giou_t).any():
         raise ValueError("Box GIoU is NaN or Inf.")
 
     # convert tensor back to numpy if needed
-    giou, *_ = convert_to_dst_type(src=giou_t, dst=boxes1)
+    giou, *_ = convert_to_dst_type(src=giou_t, dst=boxes1, dtype=box_dtype)
     return giou
 
 
diff --git a/monai/transforms/__init__.py b/monai/transforms/__init__.py
@@ -506,7 +506,7 @@
     ZoomDict,
 )
 from .spatial.functional import spatial_resample
-from .traits import LazyTrait, MultiSampleTrait, RandomizableTrait, ThreadUnsafe
+from .traits import LazyTrait, MultiSampleTrait, RandomizableTrait, ReduceTrait, ThreadUnsafe
 from .transform import LazyTransform, MapTransform, Randomizable, RandomizableTransform, Transform, apply_transform
 from .utility.array import (
     AddCoordinateChannels,
@@ -521,6 +521,7 @@
     EnsureChannelFirst,
     EnsureType,
     FgBgToIndices,
+    FlattenSequence,
     Identity,
     ImageFilter,
     IntensityStats,
@@ -593,6 +594,9 @@
     FgBgToIndicesd,
     FgBgToIndicesD,
     FgBgToIndicesDict,
+    FlattenSequenced,
+    FlattenSequenceD,
+    FlattenSequenceDict,
     FlattenSubKeysd,
     FlattenSubKeysD,
     FlattenSubKeysDict,
diff --git a/monai/transforms/traits.py b/monai/transforms/traits.py
@@ -14,7 +14,7 @@
 
 from __future__ import annotations
 
-__all__ = ["LazyTrait", "InvertibleTrait", "RandomizableTrait", "MultiSampleTrait", "ThreadUnsafe"]
+__all__ = ["LazyTrait", "InvertibleTrait", "RandomizableTrait", "MultiSampleTrait", "ThreadUnsafe", "ReduceTrait"]
 
 from typing import Any
 
@@ -99,3 +99,14 @@ class ThreadUnsafe:
     """
 
     pass
+
+
+class ReduceTrait:
+    """
+    An interface to indicate that the transform has the capability to reduce multiple samples
+    into a single sample.
+    This interface can be extended from by people adapting transforms to the MONAI framework as well
+    as by implementors of MONAI transforms.
+    """
+
+    pass
diff --git a/monai/transforms/transform.py b/monai/transforms/transform.py
@@ -25,7 +25,7 @@
 from monai import config, transforms
 from monai.config import KeysCollection
 from monai.data.meta_tensor import MetaTensor
-from monai.transforms.traits import LazyTrait, RandomizableTrait, ThreadUnsafe
+from monai.transforms.traits import LazyTrait, RandomizableTrait, ReduceTrait, ThreadUnsafe
 from monai.utils import MAX_SEED, ensure_tuple, first
 from monai.utils.enums import TransformBackends
 from monai.utils.misc import MONAIEnvVars
@@ -142,7 +142,7 @@ def apply_transform(
     """
     try:
         map_items_ = int(map_items) if isinstance(map_items, bool) else map_items
-        if isinstance(data, (list, tuple)) and map_items_ > 0:
+        if isinstance(data, (list, tuple)) and map_items_ > 0 and not isinstance(transform, ReduceTrait):
             return [
                 apply_transform(transform, item, map_items_ - 1, unpack_items, log_stats, lazy, overrides)
                 for item in data
@@ -482,8 +482,7 @@ def key_iterator(self, data: Mapping[Hashable, Any], *extra_iterables: Iterable
                 yield (key,) + tuple(_ex_iters) if extra_iterables else key
             elif not self.allow_missing_keys:
                 raise KeyError(
-                    f"Key `{key}` of transform `{self.__class__.__name__}` was missing in the data"
-                    " and allow_missing_keys==False."
+                    f"Key `{key}` of transform `{self.__class__.__name__}` was missing in the data and allow_missing_keys==False."
                 )
 
     def first_key(self, data: dict[Hashable, Any]):
diff --git a/monai/transforms/utility/array.py b/monai/transforms/utility/array.py
@@ -43,7 +43,7 @@
     median_filter,
 )
 from monai.transforms.inverse import InvertibleTransform, TraceableTransform
-from monai.transforms.traits import MultiSampleTrait
+from monai.transforms.traits import MultiSampleTrait, ReduceTrait
 from monai.transforms.transform import Randomizable, RandomizableTrait, RandomizableTransform, Transform
 from monai.transforms.utils import (
     apply_affine_to_points,
@@ -110,6 +110,7 @@
     "ImageFilter",
     "RandImageFilter",
     "ApplyTransformToPoints",
+    "FlattenSequence",
 ]
 
 
@@ -1950,3 +1951,39 @@ def inverse(self, data: torch.Tensor) -> torch.Tensor:
             data = inverse_transform(data, transform[TraceKeys.EXTRA_INFO]["image_affine"])
 
         return data
+
+
+class FlattenSequence(Transform, ReduceTrait):
+    """
+    Flatten a nested sequence (list or tuple) by one level.
+    If the input is a sequence of sequences, it will flatten them into a single sequence.
+    Non-nested sequences and other data types are returned unchanged.
+
+    For example:
+
+    .. code-block:: python
+
+        flatten = FlattenSequence()
+        data = [[1, 2], [3, 4], [5, 6]]
+        print(flatten(data))
+        [1, 2, 3, 4, 5, 6]
+
+    """
+
+    def __init__(self):
+        super().__init__()
+
+    def __call__(self, data: list | tuple | Any) -> list | tuple | Any:
+        """
+        Flatten a nested sequence by one level.
+        Args:
+            data: Input data, can be a nested sequence.
+        Returns:
+            Flattened list if input is a nested sequence, otherwise returns data unchanged.
+        """
+        if isinstance(data, (list, tuple)):
+            if len(data) == 0:
+                return data
+            if all(isinstance(item, (list, tuple)) for item in data):
+                return [item for sublist in data for item in sublist]
+        return data
diff --git a/monai/transforms/utility/dictionary.py b/monai/transforms/utility/dictionary.py
diff --git a/tests/data/test_box_utils.py b/tests/data/test_box_utils.py
diff --git a/tests/transforms/compose/test_compose.py b/tests/transforms/compose/test_compose.py
