From eaf033c0570308dfcd381ed61d274c7f5add7cfc Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Mon, 09 Nov 2015 21:27:02 +0000
Subject: [PATCH] Added tiny yolo model

---
 src/network.c |   17 +++--------------
 1 files changed, 3 insertions(+), 14 deletions(-)

diff --git a/src/network.c b/src/network.c
index 7f19318..9bcb264 100644
--- a/src/network.c
+++ b/src/network.c
@@ -11,7 +11,6 @@
 #include "convolutional_layer.h"
 #include "deconvolutional_layer.h"
 #include "detection_layer.h"
-#include "region_layer.h"
 #include "normalization_layer.h"
 #include "maxpool_layer.h"
 #include "avgpool_layer.h"
@@ -72,8 +71,6 @@
             return "softmax";
         case DETECTION:
             return "detection";
-        case REGION:
-            return "region";
         case DROPOUT:
             return "dropout";
         case CROP:
@@ -119,8 +116,6 @@
             forward_normalization_layer(l, state);
         } else if(l.type == DETECTION){
             forward_detection_layer(l, state);
-        } else if(l.type == REGION){
-            forward_region_layer(l, state);
         } else if(l.type == CONNECTED){
             forward_connected_layer(l, state);
         } else if(l.type == CROP){
@@ -180,10 +175,6 @@
             sum += net.layers[i].cost[0];
             ++count;
         }
-        if(net.layers[i].type == REGION){
-            sum += net.layers[i].cost[0];
-            ++count;
-        }
     }
     return sum/count;
 }
@@ -224,8 +215,6 @@
             backward_dropout_layer(l, state);
         } else if(l.type == DETECTION){
             backward_detection_layer(l, state);
-        } else if(l.type == REGION){
-            backward_region_layer(l, state);
         } else if(l.type == SOFTMAX){
             if(i != 0) backward_softmax_layer(l, state);
         } else if(l.type == CONNECTED){
@@ -540,12 +529,12 @@
     return acc;
 }
 
-float *network_accuracies(network net, data d)
+float *network_accuracies(network net, data d, int n)
 {
     static float acc[2];
     matrix guess = network_predict_data(net, d);
-    acc[0] = matrix_topk_accuracy(d.y, guess,1);
-    acc[1] = matrix_topk_accuracy(d.y, guess,5);
+    acc[0] = matrix_topk_accuracy(d.y, guess, 1);
+    acc[1] = matrix_topk_accuracy(d.y, guess, n);
     free_matrix(guess);
     return acc;
 }

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