Added dnn readNetFromDarknet function binding and modified ReadNetFromTensorflow for config parameter

Author: Johnson Su

cc/modules/dnn/dnn.cc

@@ -11,6 +11,8 @@
 NAN_MODULE_INIT(Dnn::Init) {
   Net::Init(target);
 
+  Nan::SetMethod(target, "readNetFromDarknet", readNetFromDarknet);
+  Nan::SetMethod(target, "readNetFromDarknetAsync", readNetFromDarknetAsync);
   Nan::SetMethod(target, "readNetFromTensorflow", ReadNetFromTensorflow);
   Nan::SetMethod(target, "readNetFromTensorflowAsync", ReadNetFromTensorflowAsync);
   Nan::SetMethod(target, "readNetFromCaffe", ReadNetFromCaffe);
@@ -24,6 +26,22 @@ NAN_MODULE_INIT(Dnn::Init) {
 #endif
 };
 
+NAN_METHOD(Dnn::readNetFromDarknet)
+{
+  FF::SyncBinding(
+      std::make_shared<DnnBindings::readNetFromDarknetWorker>(),
+      "readNetFromDarknet",
+      info);
+}
+
+NAN_METHOD(Dnn::readNetFromDarknetAsync)
+{
+  FF::AsyncBinding(
+      std::make_shared<DnnBindings::readNetFromDarknetWorker>(),
+      "readNetFromDarknetAsync",
+      info);
+}
+
 NAN_METHOD(Dnn::ReadNetFromTensorflow) {
   FF::SyncBinding(
     std::make_shared<DnnBindings::ReadNetFromTensorflowWorker>(),

cc/modules/dnn/dnn.h

@@ -11,6 +11,8 @@ class Dnn {
 public:
   static NAN_MODULE_INIT(Init);
 
+  static NAN_METHOD(readNetFromDarknet);
+  static NAN_METHOD(readNetFromDarknetAsync);
   static NAN_METHOD(ReadNetFromTensorflow);
   static NAN_METHOD(ReadNetFromTensorflowAsync);
   static NAN_METHOD(ReadNetFromCaffe);

cc/modules/dnn/dnnBindings.h

@@ -5,16 +5,47 @@
 
 namespace DnnBindings {
 
+  struct readNetFromDarknetWorker : public CatchCvExceptionWorker{
+  public:
+    std::string cfgFile;
+    std::string darknetModelFile = "";
+
+    cv::dnn::Net net;
+
+    std::string executeCatchCvExceptionWorker() {
+      net = cv::dnn::readNetFromDarknet(cfgFile, darknetModelFile);
+      if (net.empty()) {
+        return std::string("failed to cfgFile: " + cfgFile + ", darknetModelFile: " + darknetModelFile).data();
+      }
+      return "";
+    }
+
+    v8::Local<v8::Value> getReturnValue() {
+      return Net::Converter::wrap(net);
+    }
+
+    bool unwrapRequiredArgs(Nan::NAN_METHOD_ARGS_TYPE info) {
+      return (
+          StringConverter::arg(0, &cfgFile, info));
+    }
+
+    bool unwrapOptionalArgs(Nan::NAN_METHOD_ARGS_TYPE info) {
+      return (
+          StringConverter::optArg(1, &darknetModelFile, info));
+    }
+  };
+
   struct ReadNetFromTensorflowWorker : public CatchCvExceptionWorker {
   public:
     std::string modelFile;
+    std::string configFile = "";
 
     cv::dnn::Net net;
 
     std::string executeCatchCvExceptionWorker() {
-      net = cv::dnn::readNetFromTensorflow(modelFile);
+      net = cv::dnn::readNetFromTensorflow(modelFile, configFile);
       if (net.empty()) {
-        return std::string("failed to load net: " + modelFile).data();
+        return std::string("failed to load net: " + modelFile + "failed to load config: " + configFile).data();
       }
       return "";
     }
@@ -25,7 +56,13 @@ namespace DnnBindings {
 
     bool unwrapRequiredArgs(Nan::NAN_METHOD_ARGS_TYPE info) {
       return (
-        StringConverter::arg(0, &modelFile, info)
+          StringConverter::arg(0, &modelFile, info)
+      );
+    }
+
+    bool unwrapOptionalArgs(Nan::NAN_METHOD_ARGS_TYPE info) {
+      return (
+          StringConverter::optArg(1, &configFile, info)
       );
     }
   };