Added MVN layer. Renamed layer test data.

modules/dnn/test/test_layers.cpp

@@ -54,42 +54,47 @@ static void testLayer(String basename, bool useCaffeModel = false)
 
 TEST(Layer_Test_Softmax, Accuracy)
 {
-     testLayer("softmax");
+     testLayer("layer_softmax");
 }
 
 TEST(Layer_Test_LRN_spatial, Accuracy)
 {
-     testLayer("lrn_spatial");
+     testLayer("layer_lrn_spatial");
 }
 
 TEST(Layer_Test_LRN_channels, Accuracy)
 {
-     testLayer("lrn_channels");
+     testLayer("layer_lrn_channels");
 }
 
 TEST(Layer_Test_Convolution, Accuracy)
 {
-     testLayer("convolution", true);
+     testLayer("layer_convolution", true);
 }
 
 TEST(Layer_Test_InnerProduct, Accuracy)
 {
-     testLayer("inner_product", true);
+     testLayer("layer_inner_product", true);
 }
 
 TEST(Layer_Test_Pooling_max, Accuracy)
 {
-     testLayer("pooling_max");
+     testLayer("layer_pooling_max");
 }
 
 TEST(Layer_Test_Pooling_ave, Accuracy)
 {
-     testLayer("pooling_ave");
+     testLayer("layer_pooling_ave");
 }
 
 TEST(Layer_Test_DeConvolution, Accuracy)
 {
-     testLayer("deconvolution", true);
+     testLayer("layer_deconvolution", true);
+}
+
+TEST(Layer_Test_MVN, Accuracy)
+{
+     testLayer("layer_mvn");
 }
 
 TEST(Layer_Test_Reshape, squeeze)

modules/dnn/testdata/dnn/layers/layer_mvn.prototxt

@@ -0,0 +1,21 @@
+name: "test_MVN_channels"
+input: "input"
+
+input_dim: 2
+input_dim: 6
+input_dim: 75
+input_dim: 113
+
+layer {
+  type: "MVN"
+
+  mvn_param {
+  	eps: 0.1
+    across_channels: false
+    normalize_variance: true
+  }
+
+  name: "output"
+  bottom: "input"
+  top: "output"
+}

modules/dnn/testdata/dnn/layers/run.py

@@ -30,7 +30,7 @@ def get_cafe_output(inp_blob, proto_name, caffemodel_name):
     return out_blob
 
 if __name__ == '__main__':
-    proto_filenames = glob.glob("*.prototxt")
+    proto_filenames = glob.glob("layer_*.prototxt")
 
     inp_blob = np.load('blob.npy')
     print inp_blob.shape