From 81751b47dd5d2e63f571f048bdd0a6a2a45617b0 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Mon, 30 Mar 2015 19:04:03 +0000
Subject: [PATCH] ..... and back to coords

---
 src/detection.c |   38 ++++++++++++++++++++------------------
 1 files changed, 20 insertions(+), 18 deletions(-)

diff --git a/src/detection.c b/src/detection.c
index 1800ca6..bdced37 100644
--- a/src/detection.c
+++ b/src/detection.c
@@ -27,12 +27,11 @@
                 float blue = get_color(2,class,classes);
 
                 j += classes;
-                int d = im.w/side;
-                int y = r*d+box[j]*d;
-                int x = c*d+box[j+1]*d;
-                int h = box[j+2]*im.h;
-                int w = box[j+3]*im.w;
-                draw_box(im, x-w/2, y-h/2, x+w/2, y+h/2,red,green,blue);
+                int left = box[j]  *im.w;
+                int right = box[j+1]*im.w;
+                int top = box[j+2]*im.h;
+                int bot = box[j+3]*im.h;
+                draw_box(im, left, top, right, bot, red, green, blue);
             }
         }
     }
@@ -45,7 +44,7 @@
 {
     char *base = basecfg(cfgfile);
     printf("%s\n", base);
-    float avg_loss = 1;
+    float avg_loss = -1;
     network net = parse_network_cfg(cfgfile);
     if(weightfile){
         load_weights(&net, weightfile);
@@ -84,6 +83,7 @@
         time=clock();
         float loss = train_network(net, train);
         net.seen += imgs;
+        if (avg_loss < 0) avg_loss = loss;
         avg_loss = avg_loss*.9 + loss*.1;
         printf("%d: %f, %f avg, %lf seconds, %d images\n", i, loss, avg_loss, sec(clock()-time), i*imgs);
         if(i%100==0){
@@ -109,9 +109,11 @@
     char **paths = (char **)list_to_array(plist);
     int im_size = 448;
     int classes = 20;
-    int background = 1;
-    int nuisance = 0;
-    int num_output = 7*7*(4+classes+background+nuisance);
+    int background = 0;
+    int nuisance = 1;
+    int num_boxes = 7;
+    int per_box = 4+classes+background+nuisance;
+    int num_output = num_boxes*num_boxes*per_box;
 
     int m = plist->size;
     int i = 0;
@@ -135,16 +137,16 @@
         matrix pred = network_predict_data(net, val);
         int j, k, class;
         for(j = 0; j < pred.rows; ++j){
-            for(k = 0; k < pred.cols; k += classes+4+background+nuisance){
+            for(k = 0; k < pred.cols; k += per_box){
                 float scale = 1.;
-                if(nuisance) scale = pred.vals[j][k];
-                for(class = 0; class < classes; ++class){
-                    int index = (k)/(classes+4+background+nuisance); 
-                    int r = index/7;
-                    int c = index%7;
+                int index = k/per_box;
+                int row = index / num_boxes;
+                int col = index % num_boxes;
+                if (nuisance) scale = 1.-pred.vals[j][k];
+                for (class = 0; class < classes; ++class){
                     int ci = k+classes+background+nuisance;
-                    float y = (r + pred.vals[j][ci + 0])/7.;
-                    float x = (c + pred.vals[j][ci + 1])/7.;
+                    float y = (pred.vals[j][ci + 0] + row)/num_boxes;
+                    float x = (pred.vals[j][ci + 1] + col)/num_boxes;
                     float h = pred.vals[j][ci + 2];
                     float w = pred.vals[j][ci + 3];
                     printf("%d %d %f %f %f %f %f\n", (i-1)*m/splits + j, class, scale*pred.vals[j][k+class+background+nuisance], y, x, h, w);

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