From 9d42f49a240136a8cd643cdc1f98230d4f22b05e Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Tue, 25 Aug 2015 01:27:42 +0000
Subject: [PATCH] changing data loading
---
src/parser.c | 32 ++++++++++++++++++++++++++++----
1 files changed, 28 insertions(+), 4 deletions(-)
diff --git a/src/parser.c b/src/parser.c
index 9670715..242a83c 100644
--- a/src/parser.c
+++ b/src/parser.c
@@ -14,6 +14,7 @@
#include "softmax_layer.h"
#include "dropout_layer.h"
#include "detection_layer.h"
+#include "region_layer.h"
#include "avgpool_layer.h"
#include "route_layer.h"
#include "list.h"
@@ -37,6 +38,7 @@
int is_crop(section *s);
int is_cost(section *s);
int is_detection(section *s);
+int is_region(section *s);
int is_route(section *s);
list *read_cfg(char *filename);
@@ -167,11 +169,21 @@
int rescore = option_find_int(options, "rescore", 0);
int joint = option_find_int(options, "joint", 0);
int objectness = option_find_int(options, "objectness", 0);
- int background = option_find_int(options, "background", 0);
+ int background = 0;
detection_layer layer = make_detection_layer(params.batch, params.inputs, classes, coords, joint, rescore, background, objectness);
return layer;
}
+region_layer parse_region(list *options, size_params params)
+{
+ int coords = option_find_int(options, "coords", 1);
+ int classes = option_find_int(options, "classes", 1);
+ int rescore = option_find_int(options, "rescore", 0);
+ int num = option_find_int(options, "num", 1);
+ region_layer layer = make_region_layer(params.batch, params.inputs, num, classes, coords, rescore);
+ return layer;
+}
+
cost_layer parse_cost(list *options, size_params params)
{
char *type_s = option_find_str(options, "type", "sse");
@@ -236,6 +248,9 @@
{
float probability = option_find_float(options, "probability", .5);
dropout_layer layer = make_dropout_layer(params.batch, params.inputs, probability);
+ layer.out_w = params.w;
+ layer.out_h = params.h;
+ layer.out_c = params.c;
return layer;
}
@@ -295,7 +310,6 @@
net->learning_rate = option_find_float(options, "learning_rate", .001);
net->momentum = option_find_float(options, "momentum", .9);
net->decay = option_find_float(options, "decay", .0001);
- net->seen = option_find_int(options, "seen",0);
int subdivs = option_find_int(options, "subdivisions",1);
net->batch /= subdivs;
net->subdivisions = subdivs;
@@ -345,6 +359,8 @@
l = parse_cost(options, params);
}else if(is_detection(s)){
l = parse_detection(options, params);
+ }else if(is_region(s)){
+ l = parse_region(options, params);
}else if(is_softmax(s)){
l = parse_softmax(options, params);
}else if(is_normalization(s)){
@@ -397,6 +413,10 @@
{
return (strcmp(s->type, "[detection]")==0);
}
+int is_region(section *s)
+{
+ return (strcmp(s->type, "[region]")==0);
+}
int is_deconvolutional(section *s)
{
return (strcmp(s->type, "[deconv]")==0
@@ -501,7 +521,7 @@
return sections;
}
-void save_weights(network net, char *filename)
+void save_weights_upto(network net, char *filename, int cutoff)
{
fprintf(stderr, "Saving weights to %s\n", filename);
FILE *fp = fopen(filename, "w");
@@ -513,7 +533,7 @@
fwrite(&net.seen, sizeof(int), 1, fp);
int i;
- for(i = 0; i < net.n; ++i){
+ for(i = 0; i < net.n && i < cutoff; ++i){
layer l = net.layers[i];
if(l.type == CONVOLUTIONAL){
#ifdef GPU
@@ -547,6 +567,10 @@
}
fclose(fp);
}
+void save_weights(network net, char *filename)
+{
+ save_weights_upto(net, filename, net.n);
+}
void load_weights_upto(network *net, char *filename, int cutoff)
{
--
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