shortcut_layer resize for random=1

src/data.c

@@ -269,7 +269,7 @@ void fill_truth_region(char *path, float *truth, int classes, int num_boxes, int
         h =  boxes[i].h;
         id = boxes[i].id;
 
-        if (w < .01 || h < .01) continue;
+        if (w < .001 || h < .001) continue;
 
         int col = (int)(x*num_boxes);
         int row = (int)(y*num_boxes);
@@ -326,7 +326,7 @@ void fill_truth_detection(char *path, int num_boxes, float *truth, int classes,
         id = boxes[i].id;
 
 		// not detect small objects
-		if ((w < 0.001 || h < 0.001)) { printf("small w = %f, h = %f \n", w, h); continue; }
+		if ((w < 0.001 || h < 0.001)) continue;
 
         truth[i*5+0] = x;
         truth[i*5+1] = y;

src/detector.c

@@ -43,6 +43,9 @@ void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, i
     float avg_loss = -1;
     network *nets = calloc(ngpus, sizeof(network));
 
+	int iter_save;
+	iter_save = 100;
+
     srand(time(0));
     int seed = rand();
     int i;
@@ -89,7 +92,7 @@ void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, i
 	args.small_object = l.small_object;
     args.d = &buffer;
     args.type = DETECTION_DATA;
-	args.threads = 4;// 8;
+	args.threads = 8;	// 64
 
     args.angle = net.angle;
     args.exposure = net.exposure;
@@ -113,7 +116,6 @@ void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, i
 		if(l.random && count++%10 == 0){
             printf("Resizing\n");
 			int dim = (rand() % 12 + (init_w/32 - 5)) * 32;	// +-160
-            //int dim = (rand() % 10 + 10) * 32;
             //if (get_current_batch(net)+100 > net.max_batches) dim = 544;
             //int dim = (rand() % 4 + 16) * 32;
             printf("%d\n", dim);
@@ -177,7 +179,9 @@ void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, i
 #endif	// OPENCV
 
 		//if (i % 1000 == 0 || (i < 1000 && i % 100 == 0)) {
-		if (i % 100 == 0) {
+		//if (i % 100 == 0) {
+		if(i >= iter_save) {
+			iter_save += 100;
 #ifdef GPU
 			if (ngpus != 1) sync_nets(nets, ngpus, 0);
 #endif

src/network.c

@@ -375,6 +375,8 @@ int resize_network(network *net, int w, int h)
             resize_region_layer(&l, w, h);
         }else if(l.type == ROUTE){
             resize_route_layer(&l, net);
+		}else if (l.type == SHORTCUT) {
+			resize_shortcut_layer(&l, w, h);
         }else if(l.type == REORG){
             resize_reorg_layer(&l, w, h);
         }else if(l.type == AVGPOOL){

src/shortcut_layer.c

@@ -36,6 +36,26 @@ layer make_shortcut_layer(int batch, int index, int w, int h, int c, int w2, int
     return l;
 }
 
+void resize_shortcut_layer(layer *l, int w, int h)
+{
+	assert(l->w == l->out_w);
+	assert(l->h == l->out_h);
+	l->w = l->out_w = w;
+	l->h = l->out_h = h;
+	l->outputs = w*h*l->out_c;
+	l->inputs = l->outputs;
+	l->delta = realloc(l->delta, l->outputs*l->batch * sizeof(float));
+	l->output = realloc(l->output, l->outputs*l->batch * sizeof(float));
+
+#ifdef GPU
+	cuda_free(l->output_gpu);
+	cuda_free(l->delta_gpu);
+	l->output_gpu = cuda_make_array(l->output, l->outputs*l->batch);
+	l->delta_gpu = cuda_make_array(l->delta, l->outputs*l->batch);
+#endif
+
+}
+
 void forward_shortcut_layer(const layer l, network_state state)
 {
     copy_cpu(l.outputs*l.batch, state.input, 1, l.output, 1);

src/shortcut_layer.h

@@ -7,6 +7,7 @@
 layer make_shortcut_layer(int batch, int index, int w, int h, int c, int w2, int h2, int c2);
 void forward_shortcut_layer(const layer l, network_state state);
 void backward_shortcut_layer(const layer l, network_state state);
+void resize_shortcut_layer(layer *l, int w, int h);
 
 #ifdef GPU
 void forward_shortcut_layer_gpu(const layer l, network_state state);