Adapt detection classes to use batches, adapt demos, update README

Signed-off-by: Micaela Verucchi <micaelaverucchi@gmail.com>

demo/demo/demo.cpp

@@ -34,9 +34,15 @@ int main(int argc, char *argv[]) {
     int n_classes = 80;
     if(argc > 4)
         n_classes = atoi(argv[4]); 
-    bool show = true;
+    int n_batch = 1;
     if(argc > 5)
-        show = atoi(argv[5]); 
+        n_batch = atoi(argv[5]); 
+    bool show = true;
+    if(argc > 6)
+        show = atoi(argv[6]); 
+
+    if(n_batch < 1 || n_batch > 64)
+        FatalError("Batch dim not supported");
 
     if(!show)
         SAVE_RESULT = true;
@@ -63,7 +69,7 @@ int main(int argc, char *argv[]) {
         FatalError("Network type not allowed (3rd parameter)\n");
     }
 
-    detNN->init(net, n_classes);
+    detNN->init(net, n_classes, n_batch);
 
     gRun = true;
 
@@ -81,30 +87,40 @@ int main(int argc, char *argv[]) {
     }
 
     cv::Mat frame;
-    cv::Mat dnn_input;
     if(show)
         cv::namedWindow("detection", cv::WINDOW_NORMAL);
-    
-    std::vector<tk::dnn::box> detected_bbox;
+
+    std::vector<cv::Mat> batch_frame;
+    std::vector<cv::Mat> batch_dnn_input;
 
     while(gRun) {
-        cap >> frame; 
-        if(!frame.data) {
-            break;
-        }  
- 
-        // this will be resized to the net format
-        dnn_input = frame.clone();
+        batch_dnn_input.clear();
+        batch_frame.clear();
         
+        for(int bi=0; bi< n_batch; ++bi){
+            cap >> frame; 
+            if(!frame.data) 
+                break;
+            
+            batch_frame.push_back(frame);
+
+            // this will be resized to the net format
+            batch_dnn_input.push_back(frame.clone());
+        } 
+        if(!frame.data) 
+            break;
+    
         //inference
-        detNN->update(dnn_input);
-        frame = detNN->draw(frame);
+        detNN->update(batch_dnn_input);
+        detNN->draw(batch_frame);
 
         if(show){
-            cv::imshow("detection", frame);
-            cv::waitKey(1);
+            for(int bi=0; bi< n_batch; ++bi){
+                cv::imshow("detection", batch_frame[bi]);
+                cv::waitKey(1);
+            }
         }
-        if(SAVE_RESULT)
+        if(n_batch == 1 && SAVE_RESULT)
             resultVideo << frame;
     }
 
@@ -112,10 +128,10 @@ int main(int argc, char *argv[]) {
     double mean = 0; 
     
     std::cout<<COL_GREENB<<"\n\nTime stats:\n";
-    std::cout<<"Min: "<<*std::min_element(detNN->stats.begin(), detNN->stats.end())<<" ms\n";    
-    std::cout<<"Max: "<<*std::max_element(detNN->stats.begin(), detNN->stats.end())<<" ms\n";    
+    std::cout<<"Min: "<<*std::min_element(detNN->stats.begin(), detNN->stats.end())/n_batch<<" ms\n";    
+    std::cout<<"Max: "<<*std::max_element(detNN->stats.begin(), detNN->stats.end())/n_batch<<" ms\n";    
     for(int i=0; i<detNN->stats.size(); i++) mean += detNN->stats[i]; mean /= detNN->stats.size();
-    std::cout<<"Avg: "<<mean<<" ms\n"<<COL_END;   
+    std::cout<<"Avg: "<<mean/n_batch<<" ms\n"<<COL_END;   
     
 
     return 0;

demo/demo/map.cpp

@@ -132,19 +132,20 @@ int main(int argc, char *argv[])
             FatalError("Wrong image file path.");
 
         cv::Mat frame = cv::imread(f.iFilename.c_str(), cv::IMREAD_COLOR);
+        std::vector<cv::Mat> batch_frames;
+        batch_frames.push_back(frame);
         int height = frame.rows;
         int width = frame.cols;
 
-        cv::Mat dnn_input;
         if(!frame.data) 
             break;
-        dnn_input = frame.clone();
+        std::vector<cv::Mat> batch_dnn_input;
+        batch_dnn_input.push_back(frame.clone());
 
         //inference 
-        
         detected_bbox.clear();
-        detNN->update(dnn_input, write_res_on_file, &times, write_coco_json);
-        frame = detNN->draw(frame);
+        detNN->update(batch_dnn_input, write_res_on_file, &times, write_coco_json);
+        detNN->draw(batch_frames);
         detected_bbox = detNN->detected;
 
         if(write_coco_json)
@@ -171,7 +172,7 @@ int main(int argc, char *argv[])
                 myfile << d.cl << " "<< d.prob << " "<< d.x << " "<< d.y << " "<< d.w << " "<< d.h <<"\n";
 
 			if(show)// draw rectangle for detection
-                cv::rectangle(frame, cv::Point(d.x, d.y), cv::Point(d.x + d.w, d.y + d.h), cv::Scalar(0, 0, 255), 2);             
+                cv::rectangle(batch_frames[0], cv::Point(d.x, d.y), cv::Point(d.x + d.w, d.y + d.h), cv::Scalar(0, 0, 255), 2);             
         }
 
         if(write_dets)
@@ -190,14 +191,14 @@ int main(int argc, char *argv[])
                 f.gt.push_back(b);
 
                 if(show)// draw rectangle for groundtruth
-                    cv::rectangle(frame, cv::Point((b.x-b.w/2)*width, (b.y-b.h/2)*height), cv::Point((b.x+b.w/2)*width,(b.y+b.h/2)*height), cv::Scalar(0, 255, 0), 2);             
+                    cv::rectangle(batch_frames[0], cv::Point((b.x-b.w/2)*width, (b.y-b.h/2)*height), cv::Point((b.x+b.w/2)*width,(b.y+b.h/2)*height), cv::Scalar(0, 255, 0), 2);             
             }
         }    
       
         images.push_back(f);
         
         if(show){
-            cv::imshow("detection", frame);
+            cv::imshow("detection", batch_frames[0]);
             cv::waitKey(0);
         }