Import ClipByValue from Keras

modules/dnn/src/tensorflow/tf_importer.cpp

@@ -1641,6 +1641,27 @@ void TFImporter::populateNet(Net dstNet)
                 connect(layer_id, dstNet, Pin(name), flattenId, 0);
             }
         }
+        else if (type == "ClipByValue")
+        {
+            // op: "ClipByValue"
+            // input: "input"
+            // input: "mix"
+            // input: "max"
+            CV_Assert(layer.input_size() == 3);
+
+            Mat minValue = getTensorContent(getConstBlob(layer, value_id, 1));
+            Mat maxValue = getTensorContent(getConstBlob(layer, value_id, 2));
+            CV_Assert(minValue.total() == 1, minValue.type() == CV_32F,
+                      maxValue.total() == 1, maxValue.type() == CV_32F);
+
+            layerParams.set("min_value", minValue.at<float>(0));
+            layerParams.set("max_value", maxValue.at<float>(0));
+
+            int id = dstNet.addLayer(name, "ReLU6", layerParams);
+            layer_id[name] = id;
+
+            connect(layer_id, dstNet, parsePin(layer.input(0)), id, 0);
+        }
         else if (type == "Abs" || type == "Tanh" || type == "Sigmoid" ||
                  type == "Relu" || type == "Elu" ||
                  type == "Identity" || type == "Relu6")

modules/dnn/test/test_tf_importer.cpp

@@ -415,6 +415,7 @@ TEST(Test_TensorFlow, softmax)
 TEST(Test_TensorFlow, relu6)
 {
     runTensorFlowNet("keras_relu6");
+    runTensorFlowNet("keras_relu6", DNN_TARGET_CPU, /*hasText*/ true);
 }
 
 TEST(Test_TensorFlow, keras_mobilenet_head)