From a05c4bd2e99eead9e553241246b54409dac07c87 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Wed, 01 Apr 2015 17:25:50 +0000
Subject: [PATCH] sqrt

---
 src/detection.c |   62 +++++++++++++++++-------------
 1 files changed, 35 insertions(+), 27 deletions(-)

diff --git a/src/detection.c b/src/detection.c
index 69202aa..e927140 100644
--- a/src/detection.c
+++ b/src/detection.c
@@ -26,13 +26,22 @@
                 float green = get_color(1,class,classes);
                 float blue = get_color(2,class,classes);
 
+                //float maxheight = distance_from_edge(r, side);
+                //float maxwidth  = distance_from_edge(c, side);
                 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);
+                float y = box[j+0];
+                float x = box[j+1];
+                x = (x+c)/side;
+                y = (y+r)/side;
+                float h = box[j+2]; //*maxheight;
+                float w = box[j+3]; //*maxwidth;
+                //printf("coords %f %f %f %f\n", x, y, w, h);
+
+                int left  = (x-w/2)*im.w;
+                int right = (x+w/2)*im.w;
+                int top   = (y-h/2)*im.h;
+                int bot   = (y+h/2)*im.h;
+                draw_box(im, left, top, right, bot, red, green, blue);
             }
         }
     }
@@ -60,25 +69,20 @@
     char **paths = (char **)list_to_array(plist);
     printf("%d\n", plist->size);
     data train, buffer;
-    int im_dim = 512;
-    int jitter = 64;
+    int im_dim = 448;
     int classes = 20;
     int background = 1;
-    pthread_t load_thread = load_data_detection_thread(imgs, paths, plist->size, classes, im_dim, im_dim, 7, 7, jitter, background, &buffer);
+    pthread_t load_thread = load_data_detection_thread(imgs, paths, plist->size, classes, im_dim, im_dim, 7, 7, background, &buffer);
     clock_t time;
     while(1){
         i += 1;
         time=clock();
         pthread_join(load_thread, 0);
         train = buffer;
-        load_thread = load_data_detection_thread(imgs, paths, plist->size, classes, im_dim, im_dim, 7, 7, jitter, background, &buffer);
+        load_thread = load_data_detection_thread(imgs, paths, plist->size, classes, im_dim, im_dim, 7, 7, background, &buffer);
 
-/*
-           image im = float_to_image(im_dim - jitter, im_dim-jitter, 3, train.X.vals[114]);
-           draw_detection(im, train.y.vals[114], 7);
-           show_image(im, "truth");
-           cvWaitKey(0);
-*/
+           //image im = float_to_image(im_dim, im_dim, 3, train.X.vals[114]);
+           //draw_detection(im, train.y.vals[114], 7);
 
         printf("Loaded: %lf seconds\n", sec(clock()-time));
         time=clock();
@@ -112,7 +116,9 @@
     int classes = 20;
     int background = 0;
     int nuisance = 1;
-    int num_output = 7*7*(4+classes+background+nuisance);
+    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;
@@ -136,18 +142,20 @@
         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 = 1.-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 h = pred.vals[j][ci + 2];
-                    float w = pred.vals[j][ci + 3];
+                    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]; //* distance_from_edge(row, num_boxes);
+                    h = h*h;
+                    float w = pred.vals[j][ci + 3]; //* distance_from_edge(col, num_boxes);
+                    w = w*w;
                     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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