Removed WA for CPU interpolate NHWC (#8686)

samples/cpp/classification_sample_async/main.cpp

@@ -27,8 +27,6 @@
 #include "classification_sample_async.h"
 #include "openvino/openvino.hpp"
 
-using namespace ov::preprocess;
-
 /**
  * @brief Checks input args
  * @param argc number of args
@@ -104,9 +102,9 @@ int main(int argc, char* argv[]) {
         // -------- Step 3. Apply preprocessing --------
         const ov::Layout tensor_layout{"NHWC"};
 
-        PrePostProcessor proc(model);
+        ov::preprocess::PrePostProcessor proc(model);
         // 1) input() with no args assumes a model has a single input
-        InputInfo& input_info = proc.input();
+        ov::preprocess::InputInfo& input_info = proc.input();
         // 2) Set input tensor information:
         // - precision of tensor is supposed to be 'u8'
         // - layout of data is 'NHWC'

samples/cpp/hello_classification/main.cpp

@@ -17,8 +17,6 @@
 #include "format_reader_ptr.h"
 // clang-format on
 
-using namespace ov::preprocess;
-
 /**
  * @brief Main with support Unicode paths, wide strings
  */
@@ -71,38 +69,29 @@ int tmain(int argc, tchar* argv[]) {
 
         // -------- Step 4. Apply preprocessing --------
 
-        // clang-format off
+        ov::preprocess::PrePostProcessor preproc(model);
-        model = PrePostProcessor(model).
+        // 1) Set input tensor information:
-            // 1) InputInfo() with no args assumes a model has a single input
+        // - input() provides information about a single model input
-            input(InputInfo().
-                // 2) Set input tensor information:
         // - precision of tensor is supposed to be 'u8'
         // - layout of data is 'NHWC'
         // - set static spatial dimensions to input tensor to resize from
-                tensor(InputTensorInfo().
+        preproc.input()
-                    set_element_type(ov::element::u8).
+            .tensor()
-                    set_spatial_static_shape(
+            .set_element_type(ov::element::u8)
-                        tensor_shape[ov::layout::height_idx(tensor_layout)],
+            .set_layout(tensor_layout)
-                        tensor_shape[ov::layout::width_idx(tensor_layout)]).
+            .set_spatial_static_shape(tensor_shape[ov::layout::height_idx(tensor_layout)],
-                    set_layout(tensor_layout)).
+                                      tensor_shape[ov::layout::width_idx(tensor_layout)]);
-                // 3) Adding explicit preprocessing steps:
+        // 2) Adding explicit preprocessing steps:
         // - convert layout to 'NCHW' (from 'NHWC' specified above at tensor layout)
         // - apply linear resize from tensor spatial dims to model spatial dims
-                preprocess(PreProcessSteps().
+        preproc.input().preprocess().resize(ov::preprocess::ResizeAlgorithm::RESIZE_LINEAR);
-                    convert_element_type(ov::element::f32). // WA for CPU plugin
-                    convert_layout("NCHW"). // WA for CPU plugin
-                    resize(ResizeAlgorithm::RESIZE_LINEAR)).
         // 4) Here we suppose model has 'NCHW' layout for input
-                network(InputNetworkInfo().
+        preproc.input().network().set_layout("NCHW");
-                    set_layout("NCHW"))).
-            output(OutputInfo().
         // 5) Set output tensor information:
         // - precision of tensor is supposed to be 'f32'
-                tensor(OutputTensorInfo().
+        preproc.output().tensor().set_element_type(ov::element::f32);
-                    set_element_type(ov::element::f32))).
         // 6) Apply preprocessing modifing the original 'model'
-            build();
+        model = preproc.build();
-        // clang-format on
 
         // -------- Step 5. Loading a model to the device --------
         ov::runtime::ExecutableNetwork executable_network = core.compile_model(model, device_name);

samples/cpp/ngraph_function_creation_sample/main.cpp

@@ -277,18 +277,17 @@ int main(int argc, char* argv[]) {
 
         // apply preprocessing
         // clang-format off
-        using namespace ov::preprocess;
+        model = ov::preprocess::PrePostProcessor(model)
-        model = PrePostProcessor(model)
             // 1) InputInfo() with no args assumes a model has a single input
-            .input(InputInfo()
+            .input(ov::preprocess::InputInfo()
                 // 2) Set input tensor information:
                 // - precision of tensor is supposed to be 'u8'
                 // - layout of data is 'NHWC'
-                .tensor(InputTensorInfo()
+                .tensor(ov::preprocess::InputTensorInfo()
                     .set_layout(tensor_layout)
                     .set_element_type(element::u8))
                 // 3) Here we suppose model has 'NCHW' layout for input
-                .network(InputNetworkInfo()
+                .network(ov::preprocess::InputNetworkInfo()
                     .set_layout("NCHW")))
         // 4) Once the build() method is called, the preprocessing steps
         // for layout and precision conversions are inserted automatically