[PyAPI] Tensor creation from Pillow

src/bindings/python/requirements_test.txt

@@ -25,6 +25,7 @@ flake8_pep3101<=2.1.0
 flake8_quotes<=3.4.0
 mypy
 Pep8-naming
+pillow
 pydocstyle
 pytest-forked; sys_platform != 'win32'
 pytest-xdist

src/bindings/python/src/pyopenvino/core/tensor.cpp

@@ -214,6 +214,31 @@ void regclass_Tensor(py::module m) {
             py::arg("begin"),
             py::arg("end"));
 
+    cls.def(py::init([](py::object& image) {
+                if (!py::isinstance(image, py::module::import("PIL.Image").attr("Image"))) {
+                    throw py::type_error("Input must be a PIL.Image.Image object");
+                }
+                auto np_array = py::module::import("numpy").attr("array")(image);
+                py::array array = np_array.cast<py::array>();
+
+                return Common::object_from_data<ov::Tensor>(array, false);
+            }),
+            py::arg("image"),
+            R"(
+                Constructs Tensor from a Pillow Image.
+
+                :param image: Pillow Image to create the tensor from.
+                :type image: PIL.Image.Image
+                :Example:
+                .. code-block:: python
+
+                    from PIL import Image
+                    import openvino as ov
+
+                    img = Image.open("example.jpg")
+                    tensor = ov.Tensor(img)
+            )");
+
     cls.def("get_element_type",
             &ov::Tensor::get_element_type,
             R"(

src/bindings/python/src/pyopenvino/utils/utils.cpp

@@ -192,8 +192,7 @@ py::object from_ov_any(const ov::Any& any) {
             std::string property_name = it;
             auto mutability = it.get_mutability();
             std::string mutability_str;
-            switch (mutability)
-            {
+            switch (mutability) {
             case ov::PropertyMutability::RW:
                 mutability_str = "RW";
                 break;

src/bindings/python/tests/test_runtime/test_tensor.py

@@ -640,3 +640,19 @@ def test_copy_and_deepcopy(copy_func, should_share_data):
         assert tensor_copy.data[0, 0] == outlier
     else:
         assert tensor_copy.data[0, 0] == value
+
+
+def test_tensor_from_pillow():
+    from PIL import Image
+
+    shape = (224, 224, 3)
+    numpy_dtype = np.uint8
+    arr = generate_image(shape).astype(numpy_dtype)
+    img = Image.fromarray(arr)
+
+    tensor = ov.Tensor(img)
+    assert tensor.shape == shape
+    assert tensor.element_type == ov.Type(numpy_dtype)
+    assert isinstance(tensor.data, np.ndarray)
+    assert tensor.data.dtype == numpy_dtype
+    assert tensor.data.shape == shape