Small version of YOLO, ~1GB RAM

Joseph Redmon

2015-07-12 0b2be9d76a369e28fd1fc384b3952621921c9ae5

 src/network.c

@@ -10,6 +10,7 @@
#include "convolutional_layer.h"
#include "deconvolutional_layer.h"
#include "detection_layer.h"
#include "normalization_layer.h"
#include "maxpool_layer.h"
#include "cost_layer.h"
#include "softmax_layer.h"
@@ -39,6 +40,8 @@
            return "cost";
        case ROUTE:
            return "route";
        case NORMALIZATION:
            return "normalization";
        default:
            break;
    }
@@ -66,6 +69,8 @@
            forward_convolutional_layer(l, state);
        } else if(l.type == DECONVOLUTIONAL){
            forward_deconvolutional_layer(l, state);
        } else if(l.type == NORMALIZATION){
            forward_normalization_layer(l, state);
        } else if(l.type == DETECTION){
            forward_detection_layer(l, state);
        } else if(l.type == CONNECTED){
@@ -147,6 +152,8 @@
            backward_convolutional_layer(l, state);
        } else if(l.type == DECONVOLUTIONAL){
            backward_deconvolutional_layer(l, state);
        } else if(l.type == NORMALIZATION){
            backward_normalization_layer(l, state);
        } else if(l.type == MAXPOOL){
            if(i != 0) backward_maxpool_layer(l, state);
        } else if(l.type == DROPOUT){
@@ -266,6 +273,8 @@
            resize_convolutional_layer(&l, w, h);
        }else if(l.type == MAXPOOL){
            resize_maxpool_layer(&l, w, h);
        }else if(l.type == NORMALIZATION){
            resize_normalization_layer(&l, w, h);
        }else{
            error("Cannot resize this type of layer");
        }