Merge remote-tracking branch 'upstream/3.4' into merge-3.4

modules/dnn/include/opencv2/dnn/all_layers.hpp

@@ -366,6 +366,7 @@ CV__DNN_INLINE_NS_BEGIN
          */
         std::vector<std::vector<Range> > sliceRanges;
         int axis;
+        int num_split;
 
         static Ptr<SliceLayer> create(const LayerParams &params);
     };

modules/dnn/include/opencv2/dnn/dnn.hpp

@@ -383,7 +383,7 @@ CV__DNN_INLINE_NS_BEGIN
 
         /** @brief Dump net to String
          *  @returns String with structure, hyperparameters, backend, target and fusion
-         *  To see correct backend, target and fusion run after forward().
+         *  Call method after setInput(). To see correct backend, target and fusion run after forward().
          */
         CV_WRAP String dump();
         /** @brief Dump net structure, hyperparameters, backend, target and fusion to dot file

modules/dnn/src/dnn.cpp

@@ -2979,6 +2979,13 @@ String parseLayerParams(const String& name, const LayerParams& lp) {
 String Net::dump()
 {
     CV_Assert(!empty());
+
+    if (impl->netInputLayer->inputsData.empty())
+        CV_Error(Error::StsError, "Requested set input");
+
+    if (!impl->netWasAllocated)
+        impl->setUpNet();
+
     std::ostringstream out;
     std::map<int, LayerData>& map = impl->layers;
     int prefBackend = impl->preferableBackend;

modules/dnn/src/layers/slice_layer.cpp

@@ -61,6 +61,7 @@ public:
     {
         setParamsFrom(params);
         axis = params.get<int>("axis", 1);
+        num_split = params.get<int>("num_split", 0);
         if (params.has("slice_point"))
         {
             CV_Assert(!params.has("begin") && !params.has("size") && !params.has("end"));
@@ -141,9 +142,10 @@ public:
         else  // Divide input blob on equal parts by axis.
         {
             CV_Assert(0 <= axis && axis < inpShape.size());
-            CV_Assert(requiredOutputs > 0 && inpShape[axis] % requiredOutputs == 0);
-            inpShape[axis] /= requiredOutputs;
-            outputs.resize(requiredOutputs, inpShape);
+            int splits = num_split ? num_split : requiredOutputs;
+            CV_Assert(splits > 0 && inpShape[axis] % splits == 0);
+            inpShape[axis] /= splits;
+            outputs.resize(splits, inpShape);
         }
         return false;
     }

modules/dnn/src/tensorflow/tf_importer.cpp

@@ -1410,6 +1410,9 @@ void TFImporter::populateNet(Net dstNet)
                 axis = toNCHW(axis);
             layerParams.set("axis", axis);
 
+            if (hasLayerAttr(layer, "num_split"))
+                layerParams.set("num_split", getLayerAttr(layer, "num_split").i());
+
             int id = dstNet.addLayer(name, "Slice", layerParams);
             layer_id[name] = id;
 

modules/dnn/test/test_misc.cpp

@@ -78,6 +78,26 @@ TEST(readNet, Regression)
     EXPECT_FALSE(net.empty());
 }
 
+typedef testing::TestWithParam<tuple<Backend, Target> > dump;
+TEST_P(dump, Regression)
+{
+    const int backend  = get<0>(GetParam());
+    const int target   = get<1>(GetParam());
+    Net net = readNet(findDataFile("dnn/squeezenet_v1.1.prototxt"),
+                      findDataFile("dnn/squeezenet_v1.1.caffemodel", false));
+
+    int size[] = {1, 3, 227, 227};
+    Mat input = cv::Mat::ones(4, size, CV_32F);
+    net.setInput(input);
+    net.setPreferableBackend(backend);
+    net.setPreferableTarget(target);
+    EXPECT_FALSE(net.dump().empty());
+    net.forward();
+    EXPECT_FALSE(net.dump().empty());
+}
+
+INSTANTIATE_TEST_CASE_P(/**/, dump, dnnBackendsAndTargets());
+
 class FirstCustomLayer CV_FINAL : public Layer
 {
 public:

modules/dnn/test/test_onnx_importer.cpp

@@ -605,7 +605,7 @@ TEST_P(Test_ONNX_nets, Resnet34_kinetics)
     if (target != DNN_TARGET_CPU)
         throw SkipTestException("Only CPU is supported");
 
-    String onnxmodel = findDataFile("dnn/resnet-34_kinetics.onnx");
+    String onnxmodel = findDataFile("dnn/resnet-34_kinetics.onnx", false);
     Mat image0 = imread(findDataFile("dnn/dog416.png"));
     Mat image1 = imread(findDataFile("dnn/street.png"));
 

modules/dnn/test/test_tf_importer.cpp

@@ -350,6 +350,11 @@ TEST_P(Test_TensorFlow_layers, l2_normalize_3d)
     runTensorFlowNet("l2_normalize_3d");
 }
 
+TEST_P(Test_TensorFlow_layers, Split)
+{
+    runTensorFlowNet("split");
+}
+
 class Test_TensorFlow_nets : public DNNTestLayer {};
 
 TEST_P(Test_TensorFlow_nets, MobileNet_SSD)