Merge pull request #15753 from dmatveev:dm/ng-5000-security_barrier-interactive_face

G-API: Introduced Security Barrier & Interactive Face Detection samples

* G-API-NG/Samples: Added samples & relevant changes

- Security barrier camera sample
- Age/Gender/Emotions recognition sample
- GIEBackend now loads CPU extension libraries
- A couple of API-level workarounds added to deal with cv::Mat/Blob conversions

* G-API-NG/Samples: removed HAVE_INF_ENGINE remnants

modules/gapi/include/opencv2/gapi/infer/ie.hpp

@@ -25,6 +25,22 @@ namespace ie {
 
 GAPI_EXPORTS cv::gapi::GBackend backend();
 
+/**
+ * Specify how G-API and IE should trait input data
+ *
+ * In OpenCV, the same cv::Mat is used to represent both
+ * image and tensor data. Sometimes those are hardly distinguishable,
+ * so this extra parameter is used to give G-API a hint.
+ *
+ * This hint controls how G-API reinterprets the data when converting
+ * it to IE Blob format (and which layout/etc is assigned to this data).
+ */
+enum class TraitAs: int
+{
+    TENSOR, //!< G-API traits an associated cv::Mat as a raw tensor and passes dimensions as-is
+    IMAGE   //!< G-API traits an associated cv::Mat as an image so creates an "image" blob (NCHW/NHWC, etc)
+};
+
 namespace detail {
     struct ParamDesc {
         std::string model_path;
@@ -35,7 +51,8 @@ namespace detail {
         std::vector<std::string> input_names;
         std::vector<std::string> output_names;
 
-        std::unordered_map<std::string, cv::Mat> const_inputs;
+        using ConstInput = std::pair<cv::Mat, TraitAs>;
+        std::unordered_map<std::string, ConstInput> const_inputs;
 
         // NB: nun_* may differ from topology's real input/output port numbers
         // (e.g. topology's partial execution)
@@ -83,8 +100,9 @@ public:
     }
 
     Params<Net>& constInput(const std::string &layer_name,
-                            const cv::Mat &data) {
-        desc.const_inputs[layer_name] = data;
+                            const cv::Mat &data,
+                            TraitAs hint = TraitAs::TENSOR) {
+        desc.const_inputs[layer_name] = {data, hint};
         return *this;
     }