Load networks from intermediate representation of Intel's Deep learning deployment toolkit.

modules/dnn/test/test_layers.cpp

@@ -865,4 +865,25 @@ TEST(Layer_PriorBox, squares)
     normAssert(out.reshape(1, 4), target);
 }
 
+#ifdef HAVE_INF_ENGINE
+// Using Intel's Model Optimizer generate .xml and .bin files:
+// ./ModelOptimizer -w /path/to/caffemodel -d /path/to/prototxt \
+//                  -p FP32 -i -b ${batch_size} -o /path/to/output/folder
+TEST(Layer_Test_Convolution_DLDT, Accuracy)
+{
+    Net netDefault = readNet(_tf("layer_convolution.caffemodel"), _tf("layer_convolution.prototxt"));
+    Net net = readNet(_tf("layer_convolution.xml"), _tf("layer_convolution.bin"));
+
+    Mat inp = blobFromNPY(_tf("blob.npy"));
+
+    netDefault.setInput(inp);
+    Mat outDefault = netDefault.forward();
+
+    net.setInput(inp);
+    Mat out = net.forward();
+
+    normAssert(outDefault, out);
+}
+#endif  // HAVE_INF_ENGINE
+
 }} // namespace