Case sensitive dnn layers types

modules/dnn/src/dnn.cpp

@@ -4626,16 +4626,15 @@ void LayerFactory::registerLayer(const String &type, Constructor constructor)
     CV_TRACE_ARG_VALUE(type, "type", type.c_str());
 
     cv::AutoLock lock(getLayerFactoryMutex());
-    String type_ = type.toLowerCase();
-    LayerFactory_Impl::iterator it = getLayerFactoryImpl().find(type_);
+    LayerFactory_Impl::iterator it = getLayerFactoryImpl().find(type);
 
     if (it != getLayerFactoryImpl().end())
     {
         if (it->second.back() == constructor)
-            CV_Error(cv::Error::StsBadArg, "Layer \"" + type_ + "\" already was registered");
+            CV_Error(cv::Error::StsBadArg, "Layer \"" + type + "\" already was registered");
         it->second.push_back(constructor);
     }
-    getLayerFactoryImpl().insert(std::make_pair(type_, std::vector<Constructor>(1, constructor)));
+    getLayerFactoryImpl().insert(std::make_pair(type, std::vector<Constructor>(1, constructor)));
 }
 
 void LayerFactory::unregisterLayer(const String &type)
@@ -4644,9 +4643,8 @@ void LayerFactory::unregisterLayer(const String &type)
     CV_TRACE_ARG_VALUE(type, "type", type.c_str());
 
     cv::AutoLock lock(getLayerFactoryMutex());
-    String type_ = type.toLowerCase();
 
-    LayerFactory_Impl::iterator it = getLayerFactoryImpl().find(type_);
+    LayerFactory_Impl::iterator it = getLayerFactoryImpl().find(type);
     if (it != getLayerFactoryImpl().end())
     {
         if (it->second.size() > 1)
@@ -4662,8 +4660,7 @@ Ptr<Layer> LayerFactory::createLayerInstance(const String &type, LayerParams& pa
     CV_TRACE_ARG_VALUE(type, "type", type.c_str());
 
     cv::AutoLock lock(getLayerFactoryMutex());
-    String type_ = type.toLowerCase();
-    LayerFactory_Impl::const_iterator it = getLayerFactoryImpl().find(type_);
+    LayerFactory_Impl::const_iterator it = getLayerFactoryImpl().find(type);
 
     if (it != getLayerFactoryImpl().end())
     {

modules/dnn/src/init.cpp

@@ -95,6 +95,7 @@ void initializeLayerFactory()
     CV_DNN_REGISTER_LAYER_CLASS(LRN,            LRNLayer);
     CV_DNN_REGISTER_LAYER_CLASS(InnerProduct,   InnerProductLayer);
     CV_DNN_REGISTER_LAYER_CLASS(Softmax,        SoftmaxLayer);
+    CV_DNN_REGISTER_LAYER_CLASS(SoftMax,        SoftmaxLayer);  // For compatibility. See https://github.com/opencv/opencv/issues/16877
     CV_DNN_REGISTER_LAYER_CLASS(MVN,            MVNLayer);
 
     CV_DNN_REGISTER_LAYER_CLASS(ReLU,           ReLULayer);

modules/dnn/src/onnx/onnx_importer.cpp

@@ -615,6 +615,15 @@ void ONNXImporter::populateNet(Net dstNet)
             layerParams.type = "ReLU";
             replaceLayerParam(layerParams, "alpha", "negative_slope");
         }
+        else if (layer_type == "Relu")
+        {
+            layerParams.type = "ReLU";
+        }
+        else if (layer_type == "PRelu")
+        {
+            layerParams.type = "PReLU";
+            layerParams.blobs.push_back(getBlob(node_proto, constBlobs, 1));
+        }
         else if (layer_type == "LRN")
         {
             replaceLayerParam(layerParams, "size", "local_size");
@@ -1133,10 +1142,10 @@ void ONNXImporter::populateNet(Net dstNet)
                 layerParams.set("zoom_factor_x", scales.at<float>(3));
             }
         }
-        else if (layer_type == "LogSoftmax")
+        else if (layer_type == "SoftMax" || layer_type == "LogSoftmax")
         {
             layerParams.type = "Softmax";
-            layerParams.set("log_softmax", true);
+            layerParams.set("log_softmax", layer_type == "LogSoftmax");
         }
         else
         {

modules/dnn/src/torch/torch_importer.cpp

@@ -865,15 +865,10 @@ struct TorchImporter
                 layerParams.set("indices_blob_id", tensorParams["indices"].first);
                 curModule->modules.push_back(newModule);
             }
-            else if (nnName == "SoftMax")
+            else if (nnName == "LogSoftMax" || nnName == "SoftMax")
             {
-                newModule->apiType = "SoftMax";
-                curModule->modules.push_back(newModule);
-            }
-            else if (nnName == "LogSoftMax")
-            {
-                newModule->apiType = "SoftMax";
-                layerParams.set("log_softmax", true);
+                newModule->apiType = "Softmax";
+                layerParams.set("log_softmax", nnName == "LogSoftMax");
                 curModule->modules.push_back(newModule);
             }
             else if (nnName == "SpatialCrossMapLRN")

modules/dnn/test/test_halide_layers.cpp

@@ -431,7 +431,7 @@ TEST_P(SoftMax, Accuracy)
     Backend backendId = get<0>(get<1>(GetParam()));
     Target targetId = get<1>(get<1>(GetParam()));
     LayerParams lp;
-    lp.type = "SoftMax";
+    lp.type = "Softmax";
     lp.name = "testLayer";
 
     int sz[] = {1, inChannels, 1, 1};

modules/dnn/test/test_onnx_importer.cpp

@@ -70,7 +70,7 @@ public:
         {
             LayerParams lp;
             Net netSoftmax;
-            netSoftmax.addLayerToPrev("softmaxLayer", "SoftMax", lp);
+            netSoftmax.addLayerToPrev("softmaxLayer", "Softmax", lp);
             netSoftmax.setPreferableBackend(DNN_BACKEND_OPENCV);
 
             netSoftmax.setInput(out);