Merge pull request #2599 from Saafke:dnn_superres_CUDA_support

* Create CUDA backend support for dnn_superres

Not sure if this is the best way. Perhaps better to to create getter for 'net' so user can set backend themselves.

* Create seperate functions

* Remove trailing whitespace

modules/dnn_superres/include/opencv2/dnn_superres.hpp

@@ -94,6 +94,14 @@ public:
      */
     CV_WRAP void setModel(const String& algo, int scale);
 
+    /** @brief Set computation backend
+    */
+    CV_WRAP void setPreferableBackend(int backendId);
+
+    /** @brief Set computation target
+    */
+    CV_WRAP void setPreferableTarget(int targetId);
+
     /** @brief Upsample via neural network
     @param img Image to upscale
     @param result Destination upscaled image

modules/dnn_superres/src/dnn_superres.cpp

@@ -91,6 +91,24 @@ void DnnSuperResImpl::setModel(const String& algo, int scale)
     this->alg = algo;
 }
 
+void DnnSuperResImpl::setPreferableBackend(int backendId)
+{
+    if (net.empty())
+        CV_Error(Error::StsError, "Model is emtpy. Please read a model before setting the backend.");
+
+    net.setPreferableBackend(backendId);
+    CV_LOG_INFO(NULL, "Successfully set computation backend.");
+}
+
+void DnnSuperResImpl::setPreferableTarget(int targetId)
+{
+    if (net.empty())
+        CV_Error(Error::StsError, "Model is empty. Please read a model before setting the target.");
+
+    net.setPreferableTarget(targetId);
+    CV_LOG_INFO(NULL, "Successfully set target device.");
+}
+
 void DnnSuperResImpl::upsample(InputArray img, OutputArray result)
 {
     if (net.empty())