Specify layer types for Caffe FP32->FP16 weights converter

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

@@ -726,13 +726,17 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN
      * @param src Path to origin model from Caffe framework contains single
      *            precision floating point weights (usually has `.caffemodel` extension).
      * @param dst Path to destination model with updated weights.
+     * @param layersTypes Set of layers types which parameters will be converted.
+     *                    By default, converts only Convolutional and Fully-Connected layers'
+     *                    weights.
      *
      * @note Shrinked model has no origin float32 weights so it can't be used
      *       in origin Caffe framework anymore. However the structure of data
      *       is taken from NVidia's Caffe fork: https://github.com/NVIDIA/caffe.
      *       So the resulting model may be used there.
      */
-    CV_EXPORTS_W void shrinkCaffeModel(const String& src, const String& dst);
+    CV_EXPORTS_W void shrinkCaffeModel(const String& src, const String& dst,
+                                       const std::vector<String>& layersTypes = std::vector<String>());
 
     /** @brief Performs non maximum suppression given boxes and corresponding scores.