feat: use numeric dtype for MatLike instead of generic

modules/core/misc/python/package/mat_wrapper/__init__.py

@@ -4,15 +4,16 @@ import numpy as np
 import cv2 as cv
 from typing import TYPE_CHECKING, Any
 
-# Same as cv2.typing.NumPyArrayGeneric, but avoids circular dependencies
+# Same as cv2.typing.NumPyArrayNumeric, but avoids circular dependencies
 if TYPE_CHECKING:
-    _NumPyArrayGeneric = np.ndarray[Any, np.dtype[np.generic]]
+    _NumPyArrayNumeric = np.ndarray[Any, np.dtype[np.integer[Any] | np.floating[Any]]]
 else:
-    _NumPyArrayGeneric = np.ndarray
+    _NumPyArrayNumeric = np.ndarray
 
 # NumPy documentation: https://numpy.org/doc/stable/user/basics.subclassing.html
 
-class Mat(_NumPyArrayGeneric):
+
+class Mat(_NumPyArrayNumeric):
     '''
     cv.Mat wrapper for numpy array.
 

modules/python/src2/typing_stubs_generation/predefined_types.py

@@ -34,7 +34,10 @@ _PREDEFINED_TYPES = (
     PrimitiveTypeNode.str_("char"),
     PrimitiveTypeNode.str_("String"),
     PrimitiveTypeNode.str_("c_string"),
-    ConditionalAliasTypeNode.numpy_array_("NumPyArrayGeneric"),
+    ConditionalAliasTypeNode.numpy_array_(
+        "NumPyArrayNumeric",
+        dtype="numpy.integer[_typing.Any] | numpy.floating[_typing.Any]"
+    ),
     ConditionalAliasTypeNode.numpy_array_("NumPyArrayFloat32", dtype="numpy.float32"),
     ConditionalAliasTypeNode.numpy_array_("NumPyArrayFloat64", dtype="numpy.float64"),
     NoneTypeNode("void"),
@@ -42,7 +45,7 @@ _PREDEFINED_TYPES = (
     AliasTypeNode.union_(
         "Mat",
         items=(ASTNodeTypeNode("Mat", module_name="cv2.mat_wrapper"),
-               AliasRefTypeNode("NumPyArrayGeneric")),
+               AliasRefTypeNode("NumPyArrayNumeric")),
         export_name="MatLike"
     ),
     AliasTypeNode.sequence_("MatShape", PrimitiveTypeNode.int_()),