From d8adaf8ea6a31a380f6bf1fe65e88b661d3bb51e Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Fri, 21 Oct 2016 20:16:43 +0000
Subject: [PATCH] tree stuff
---
src/classifier.c | 44 +++++++++++++++++++++++++++++++++-----------
1 files changed, 33 insertions(+), 11 deletions(-)
diff --git a/src/classifier.c b/src/classifier.c
index 208b7ed..e588af5 100644
--- a/src/classifier.c
+++ b/src/classifier.c
@@ -41,6 +41,20 @@
return options;
}
+void hierarchy_predictions(float *predictions, int n, tree *hier)
+{
+ int j;
+ for(j = 0; j < n; ++j){
+ int parent = hier->parent[j];
+ if(parent >= 0){
+ predictions[j] *= predictions[parent];
+ }
+ }
+ for(j = 0; j < n; ++j){
+ if(!hier->leaf[j]) predictions[j] = 0;
+ }
+}
+
float *get_regression_values(char **labels, int n)
{
float *v = calloc(n, sizeof(float));
@@ -99,7 +113,8 @@
load_args args = {0};
args.w = net.w;
args.h = net.h;
- args.threads = 16;
+ args.threads = 32;
+ args.hierarchy = net.hierarchy;
args.min = net.min_crop;
args.max = net.max_crop;
@@ -206,6 +221,7 @@
args.saturation = net.saturation;
args.hue = net.hue;
args.size = net.w;
+ args.hierarchy = net.hierarchy;
args.paths = paths;
args.classes = classes;
@@ -394,6 +410,7 @@
float *pred = calloc(classes, sizeof(float));
for(j = 0; j < 10; ++j){
float *p = network_predict(net, images[j].data);
+ if(net.hierarchy) hierarchy_predictions(p, net.outputs, net.hierarchy);
axpy_cpu(classes, 1, p, 1, pred, 1);
free_image(images[j]);
}
@@ -454,6 +471,7 @@
//show_image(crop, "cropped");
//cvWaitKey(0);
float *pred = network_predict(net, resized.data);
+ if(net.hierarchy) hierarchy_predictions(pred, net.outputs, net.hierarchy);
free_image(im);
free_image(resized);
@@ -513,6 +531,7 @@
//show_image(crop, "cropped");
//cvWaitKey(0);
float *pred = network_predict(net, crop.data);
+ if(net.hierarchy) hierarchy_predictions(pred, net.outputs, net.hierarchy);
if(resized.data != im.data) free_image(resized);
free_image(im);
@@ -573,6 +592,7 @@
image r = resize_min(im, scales[j]);
resize_network(&net, r.w, r.h);
float *p = network_predict(net, r.data);
+ if(net.hierarchy) hierarchy_predictions(p, net.outputs, net.hierarchy);
axpy_cpu(classes, 1, p, 1, pred, 1);
flip_image(r);
p = network_predict(net, r.data);
@@ -672,7 +692,6 @@
}
}
-
void predict_classifier(char *datacfg, char *cfgfile, char *weightfile, char *filename)
{
network net = parse_network_cfg(cfgfile);
@@ -713,11 +732,13 @@
float *X = r.data;
time=clock();
float *predictions = network_predict(net, X);
- top_predictions(net, top, indexes);
+ if(net.hierarchy) hierarchy_predictions(predictions, net.outputs, net.hierarchy);
+ top_k(predictions, net.outputs, top, indexes);
printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
for(i = 0; i < top; ++i){
int index = indexes[i];
- printf("%s: %f\n", names[index], predictions[index]);
+ if(net.hierarchy) printf("%d, %s: %f, parent: %s \n",index, names[index], predictions[index], (net.hierarchy->parent[index] >= 0) ? names[net.hierarchy->parent[index]] : "Root");
+ else printf("%s: %f\n",names[index], predictions[index]);
}
if(r.data != im.data) free_image(r);
free_image(im);
@@ -899,15 +920,15 @@
float curr_threat = 0;
if(1){
curr_threat = predictions[0] * 0 +
- predictions[1] * .6 +
- predictions[2];
+ predictions[1] * .6 +
+ predictions[2];
} else {
curr_threat = predictions[218] +
- predictions[539] +
- predictions[540] +
- predictions[368] +
- predictions[369] +
- predictions[370];
+ predictions[539] +
+ predictions[540] +
+ predictions[368] +
+ predictions[369] +
+ predictions[370];
}
threat = roll * curr_threat + (1-roll) * threat;
@@ -1092,6 +1113,7 @@
show_image(in, "Classifier");
float *predictions = network_predict(net, in_s.data);
+ if(net.hierarchy) hierarchy_predictions(predictions, net.outputs, net.hierarchy);
top_predictions(net, top, indexes);
printf("\033[2J");
--
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