Fixed timer

Makefile

@@ -136,7 +136,7 @@ $(OBJDIR)%.o: %.c $(DEPS)
 	$(CC) $(COMMON) $(CFLAGS) -c $< -o $@
 
 $(OBJDIR)%.o: %.cpp $(DEPS)
-	$(CPP) $(COMMON) $(CFLAGS) -c $< -o $@
+	$(CPP) -std=c++11 $(COMMON) $(CFLAGS) -c $< -o $@
 
 $(OBJDIR)%.o: %.cu $(DEPS)
 	$(NVCC) $(ARCH) $(COMMON) --compiler-options "$(CFLAGS)" -c $< -o $@

include/darknet.h

@@ -795,6 +795,15 @@ LIB_API tree *read_tree(char *filename);
 LIB_API metadata get_metadata(char *file);
 
 
+// http_stream.h
+LIB_API double get_time_point();
+void start_timer();
+void stop_timer();
+double get_time();
+void stop_timer_and_show();
+void stop_timer_and_show_name(char *name);
+void show_total_time();
+
 #ifdef __cplusplus
 }
 #endif  // __cplusplus

src/convolutional_kernels.cu

@@ -17,16 +17,6 @@ extern "C" {
 #include "cuda.h"
 }
 
-extern "C" {
-    double get_time_point();
-    void start_timer();
-    void stop_timer();
-    double get_time();
-    void stop_timer_and_show();
-    void stop_timer_and_show_name(char *name);
-    void show_total_time();
-}
-
 __global__ void binarize_kernel(float *x, int n, float *binary)
 {
     int i = (blockIdx.x + blockIdx.y*gridDim.x) * blockDim.x + threadIdx.x;

src/http_stream.h

@@ -27,14 +27,6 @@ image image_data_augmentation(IplImage* ipl, int w, int h,
     float jitter, float dhue, float dsat, float dexp);
 #endif  // OPENCV
 
-double get_time_point();
-void start_timer();
-void stop_timer();
-double get_time();
-void stop_timer_and_show();
-void stop_timer_and_show_name(char *name);
-void show_total_time();
-
 #ifdef __cplusplus
 }
 #endif

src/network.c

@@ -192,8 +192,6 @@ network make_network(int n)
     return net;
 }
 
-double get_time_point();
-
 void forward_network(network net, network_state state)
 {
     state.workspace = net.workspace;

src/parser.c

@@ -786,10 +786,14 @@ network parse_network_cfg_custom(char *filename, int batch)
             l = parse_avgpool(options, params);
         }else if(lt == ROUTE){
             l = parse_route(options, params, net);
+            int k;
+            for (k = 0; k < l.n; ++k) net.layers[l.input_layers[k]].use_bin_output = 0;
         }else if (lt == UPSAMPLE) {
             l = parse_upsample(options, params, net);
         }else if(lt == SHORTCUT){
             l = parse_shortcut(options, params, net);
+            net.layers[count - 1].use_bin_output = 0;
+            net.layers[l.index].use_bin_output = 0;
         }else if(lt == DROPOUT){
             l = parse_dropout(options, params);
             l.output = net.layers[count-1].output;