WIP: PEP 688 demonstration

Modules/Bridge/NumPy/include/itkPyBuffer.h

@@ -72,6 +72,12 @@ class PyBuffer
   static PyObject *
   _GetArrayViewFromImage(ImageType * image);
 
+  /**
+   * Get an 1-D byte MemoryView of the container's buffer
+   */
+  static PyObject *
+  _GetMemoryViewFromImportImageContainer(typename ImageType::PixelContainer * container);
+
   /**
    * Get an ITK image from a contiguous Python array. Internal helper function for the implementation of
    * `itkPyBuffer.GetImageViewFromArray`.

Modules/Bridge/NumPy/include/itkPyBuffer.hxx

@@ -50,6 +50,38 @@ PyBuffer<TImage>::_GetArrayViewFromImage(ImageType * image)
   return PyMemoryView_FromBuffer(&pyBuffer);
 }
 
+template <class TImage>
+PyObject *
+PyBuffer<TImage>::_GetMemoryViewFromImportImageContainer(typename ImageType::PixelContainer * container)
+{
+  using ContainerType = typename ImageType::PixelContainer;
+  Py_buffer pyBuffer{};
+
+  if (!container)
+  {
+    throw std::runtime_error("Input container is null");
+  }
+
+  void * const buffer = container->GetBufferPointer();
+
+  if (!buffer)
+  {
+    throw std::runtime_error("Container buffer pointer is null");
+  }
+
+  // If the container does not own the buffer then issue a warning
+  if (!container->GetContainerManageMemory())
+  {
+    PyErr_WarnEx(PyExc_RuntimeWarning, "The ImportImageContainer does not own the exported buffer.", 1);
+  }
+
+  const SizeValueType size = container->Size();
+  const auto          len = static_cast<Py_ssize_t>(size * sizeof(typename ContainerType::Element));
+
+  PyBuffer_FillInfo(&pyBuffer, nullptr, buffer, len, 0, PyBUF_CONTIG);
+  return PyMemoryView_FromBuffer(&pyBuffer);
+}
+
 template <class TImage>
 auto
 PyBuffer<TImage>::_get_image_view_from_contiguous_array(PyObject * arr, PyObject * shape, PyObject * numOfComponent)

Modules/Bridge/NumPy/wrapping/PyBuffer.i.init

@@ -29,6 +29,53 @@ else:
         loads = dask_deserialize.dispatch(np.ndarray)
         return NDArrayITKBase(loads(header, frames))
 
+def _get_formatstring(itk_Image_type) -> str:
+    """Returns the struct format string for a given ITK image type.
+
+    Format characters from Python's struct module:
+    - 'b': signed char (int8)
+    - 'B': unsigned char (uint8)
+    - 'h': short (int16)
+    - 'H': unsigned short (uint16)
+    - 'i': int (int32)
+    - 'I': unsigned int (uint32)
+    - 'l': long (platform dependent)
+    - 'L': unsigned long (platform dependent)
+    - 'q': long long (int64)
+    - 'Q': unsigned long long (uint64)
+    - 'f': float (float32)
+    - 'd': double (float64)
+    """
+
+    # Mapping from ITK pixel type codes to struct format strings
+    _format_map = {
+        "UC": "B",   # unsigned char
+        "US": "H",   # unsigned short
+        "UI": "I",   # unsigned int
+        "UL": "L",   # unsigned long
+        "ULL": "Q",  # unsigned long long
+        "SC": "b",   # signed char
+        "SS": "h",   # signed short
+        "SI": "i",   # signed int
+        "SL": "l",   # signed long
+        "SLL": "q",  # signed long long
+        "F": "f",    # float
+        "D": "d",    # double
+        "PF2": "f",  # Point<float, 2> - use float for components
+        "PF3": "f",  # Point<float, 3> - use float for components
+    }
+
+    import os
+    # Platform-specific adjustments for Windows
+    if os.name == 'nt':
+        _format_map['UL'] = 'I'  # unsigned int on Windows
+        _format_map['SL'] = 'i'  # signed int on Windows
+
+    try:
+        return _format_map[itk_Image_type]
+    except KeyError as e:
+        raise ValueError(f"Unknown ITK image type: {itk_Image_type}") from e
+
 def _get_numpy_pixelid(itk_Image_type) -> np.dtype:
     """Returns a ITK PixelID given a numpy array."""
 

Modules/Core/Common/wrapping/test/itkImageTest.py

@@ -17,6 +17,7 @@
 # ==========================================================================
 import itk
 import numpy as np
+import sys
 
 Dimension = 2
 PixelType = itk.UC
@@ -30,12 +31,19 @@
 image.Allocate()
 image.FillBuffer(4)
 
-array = image.__array__()
+if sys.version_info >= (3, 12):
+    array = np.array(image)
+else:
+    array = np.array(image.__buffer__())
+
 assert array[0, 0] == 4
 assert array[0, 1] == 4
 assert isinstance(array, np.ndarray)
 
-array = np.asarray(image)
+if sys.version_info >= (3, 12):
+    array = np.asarray(image)
+else:
+    array = np.asarray(image.__buffer__())
 assert array[0, 0] == 4
 assert array[0, 1] == 4
 assert isinstance(array, np.ndarray)

Modules/Core/Transform/wrapping/test/itkTransformSerializationTest.py

@@ -174,14 +174,28 @@
 convert_filter.SetReferenceImage(fixed_image)
 convert_filter.Update()
 field1 = convert_filter.GetOutput()
+field1.Update()
 field1 = np.array(field1)
 
+print(field1)
+
 convert_filter = itk.TransformToDisplacementFieldFilter.IVF22D.New()
 convert_filter.SetTransform(serialize_deserialize)
 convert_filter.UseReferenceImageOn()
 convert_filter.SetReferenceImage(fixed_image)
 convert_filter.Update()
 field2 = convert_filter.GetOutput()
+field2.Update()
 field2 = np.array(field2)
 
-assert np.array_equal(np.array(field1), np.array(field2))
+
+if not np.array_equal(field1, field2):
+    print(f"Field1 shape: {field1.shape}, dtype: {field1.dtype}")
+    print(f"Field2 shape: {field2.shape}, dtype: {field2.dtype}")
+    print(f"Field1 min: {field1.min()}, max: {field1.max()}, mean: {field1.mean()}")
+    print(f"Field2 min: {field2.min()}, max: {field2.max()}, mean: {field2.mean()}")
+    print(f"Max absolute difference: {np.abs(field1 - field2).max()}")
+    print(f"Number of different elements: {np.sum(field1 != field2)}")
+    if field1.shape == field2.shape:
+        print(f"Are they close (atol=1e-6)? {np.allclose(field1, field2, atol=1e-6)}")
+assert np.array_equal(field1, field2)

Wrapping/Generators/Python/PyBase/pyBase.i

@@ -682,13 +682,67 @@ str = str
 
 %define DECL_PYTHON_IMAGE_CLASS(swig_name)
   %extend swig_name {
-      %pythoncode {
-          def __array__(self, dtype=None):
+      %pythoncode %{
+          def __buffer__(self, flags = 0, / ) -> memoryview:
               import itk
-              import numpy as np
-              array = itk.array_from_image(self)
-              return np.asarray(array, dtype=dtype)
-      }
+              from itk.itkPyBufferPython import _get_formatstring
+
+              itksize = self.GetBufferedRegion().GetSize()
+
+              shape = list(itksize)
+              if self.GetNumberOfComponentsPerPixel() > 1 or isinstance(self, itk.VectorImage):
+                shape = shape.append(self.GetNumberOfComponentsPerPixel())
+
+              shape.reverse()
+
+              container_template = itk.template(self)
+              if container_template is None:
+                  raise BufferError("Cannot determine template parameters for ImportImageContainer")
+
+              # Extract pixel type (second template parameter)
+              pixel_code = container_template[1][0].short_name
+              format = _get_formatstring(pixel_code)
+
+              memview = memoryview(self.GetPixelContainer())
+
+              return memview.cast(format, shape=shape)
+
+      %}
+  }
+%enddef
+
+%define DECL_PYTHON_IMPORTIMAGECONTAINER_CLASS(swig_name)
+  %extend swig_name {
+      %pythoncode %{
+          def __buffer__(self, flags = 0, / ) -> memoryview:
+              """Return a buffer interface for the container.
+
+              This allows ImportImageContainer to be used with Python's buffer protocol,
+              enabling direct memory access from NumPy and other buffer-aware libraries.
+              """
+              import itk
+              # Get the pixel type from the container template parameters
+              # The container is templated as ImportImageContainer<IdentifierType, PixelType>
+              container_template = itk.template(self)
+              if container_template is None:
+                  raise BufferError("Cannot determine template parameters for ImportImageContainer")
+
+              # Extract pixel type (second template parameter)
+              pixel_type = container_template[1][1]
+
+
+              # Call the PyBuffer method to get the memory view
+              # We need to determine the appropriate PyBuffer type
+              try:
+                  # Try to get the PyBuffer class for this pixel type
+                  # PyBuffer is templated over Image types, but we can use a dummy 1D image type
+                  ImageType = itk.Image[pixel_type, 2]
+                  PyBufferType = itk.PyBuffer[ImageType]
+
+                  return PyBufferType._GetMemoryViewFromImportImageContainer(self)
+              except (AttributeError, KeyError) as e:
+                  raise BufferError(f"PyBuffer not available for this pixel type: {e}")
+      %}
   }
 %enddef