yolo3 ok

demo/demo/demo.cpp

@@ -23,7 +23,7 @@ int main(int argc, char *argv[]) {
     std::cout<<"detection\n";
     signal(SIGINT, sig_handler);
 
-    Yolo3Detection yolo;
+    tk::dnn::Yolo3Detection yolo;
     yolo.init("./");
 
     gRun = true;
@@ -39,6 +39,7 @@ int main(int argc, char *argv[]) {
         std::cout<<"camera started\n";
 
     cv::Mat frame;
+    cv::Mat dnn_input;
     cv::namedWindow("detection", cv::WINDOW_NORMAL);
     cv::resizeWindow("detection", 544*1.2, 320*1.2);
     
@@ -48,7 +49,8 @@ int main(int argc, char *argv[]) {
             continue;
         }  
  
-        yolo.update(frame);
+        dnn_input = frame.clone();
+        yolo.update(dnn_input);
 
         // draw dets
         for(int i=0; i<yolo.detected.size(); i++) {
@@ -64,7 +66,6 @@ int main(int argc, char *argv[]) {
             cv::rectangle(frame, cv::Point(x0, y0), cv::Point(x1, y1), yolo.colors[obj_class], 2);                
         }
     
-        
         cv::imshow("detection", frame);
         cv::waitKey(1);
     }

include/Yolo3Detection.h

@@ -11,6 +11,8 @@
 
 #include <tkDNN/tkdnn.h>
 
+namespace tk { namespace dnn {
+
 /**
  * 
  * @author Francesco Gatti
@@ -51,3 +53,5 @@ class Yolo3Detection {
         void update(cv::Mat &frame);
 
 };
+
+}}

src/Yolo3Detection.cpp

@@ -1,5 +1,7 @@
 #include "Yolo3Detection.h"
 
+namespace tk { namespace dnn {
+
 bool Yolo3Detection::init(std::string tensor_folder) {
 
     //const char *tensor_path = "../data/yolo3/yolo3_berkeley.rt";
@@ -43,7 +45,9 @@ void Yolo3Detection::update(cv::Mat &imageORIG) {
     if(!imageORIG.data) {
         std::cout<<"YOLO: NO IMAGE DATA\n";
         return;
-    }      
+    }     
+    float xRatio =  float(imageORIG.cols) / float(netRT->input_dim.w);
+    float yRatio =  float(imageORIG.rows) / float(netRT->input_dim.h);
 
     resize(imageORIG, imageORIG, cv::Size(netRT->input_dim.w, netRT->input_dim.h));
     imageORIG.convertTo(imageF, CV_32FC3, 1/255.0); 
@@ -83,10 +87,6 @@ void Yolo3Detection::update(cv::Mat &imageORIG) {
     tk::dnn::Yolo::mergeDetections(dets, ndets, classes);
     TIMER_STOP
 
-
-    float xRatio =  float(imageORIG.cols) / float(netRT->input_dim.w);
-    float yRatio =  float(imageORIG.rows) / float(netRT->input_dim.h);
-
     // fill detected
     detected.clear();
     for(int j=0; j<ndets; j++) {
@@ -126,3 +126,5 @@ void Yolo3Detection::update(cv::Mat &imageORIG) {
     }
 
 }
+
+}}