From 9802287b5890d9b2cc250adba1b9810657a95c9c Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Fri, 18 Dec 2015 23:55:58 +0000
Subject: [PATCH] some fixes
---
src/classifier.c | 26 ++++++++++++++------------
1 files changed, 14 insertions(+), 12 deletions(-)
diff --git a/src/classifier.c b/src/classifier.c
index 8a3ae5a..ddd88b1 100644
--- a/src/classifier.c
+++ b/src/classifier.c
@@ -143,7 +143,7 @@
clock_t time;
float avg_acc = 0;
float avg_topk = 0;
- int splits = 50;
+ int splits = m/1000;
int num = (i+1)*m/splits - i*m/splits;
data val, buffer;
@@ -201,7 +201,7 @@
int i = 0;
char **names = get_labels(name_list);
clock_t time;
- int indexes[10];
+ int *indexes = calloc(top, sizeof(int));
char buff[256];
char *input = buff;
while(1){
@@ -214,7 +214,7 @@
if(!input) return;
strtok(input, "\n");
}
- image im = load_image_color(input, 256, 256);
+ image im = load_image_color(input, net.w, net.h);
float *X = im.data;
time=clock();
float *predictions = network_predict(net, X);
@@ -229,10 +229,10 @@
}
}
-void test_classifier(char *datacfg, char *cfgfile, char *weightfile, char *filename, int target_layer)
+void test_classifier(char *datacfg, char *cfgfile, char *weightfile, int target_layer)
{
int curr = 0;
- network net = parse_network_cfg(filename);
+ network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&net, weightfile);
}
@@ -241,10 +241,8 @@
list *options = read_data_cfg(datacfg);
char *test_list = option_find_str(options, "test", "data/test.list");
- char *label_list = option_find_str(options, "labels", "data/labels.list");
int classes = option_find_int(options, "classes", 2);
- char **labels = get_labels(label_list);
list *plist = get_paths(test_list);
char **paths = (char **)list_to_array(plist);
@@ -262,7 +260,7 @@
args.classes = classes;
args.n = net.batch;
args.m = 0;
- args.labels = labels;
+ args.labels = 0;
args.d = &buffer;
args.type = CLASSIFICATION_DATA;
@@ -283,13 +281,17 @@
time=clock();
matrix pred = network_predict_data(net, val);
- int i;
+ int i, j;
if (target_layer >= 0){
//layer l = net.layers[target_layer];
}
- for(i = 0; i < val.X.rows; ++i){
-
+ for(i = 0; i < pred.rows; ++i){
+ printf("%s", paths[curr-net.batch+i]);
+ for(j = 0; j < pred.cols; ++j){
+ printf("\t%g", pred.vals[i][j]);
+ }
+ printf("\n");
}
free_matrix(pred);
@@ -315,7 +317,7 @@
int layer = layer_s ? atoi(layer_s) : -1;
if(0==strcmp(argv[2], "predict")) predict_classifier(data, cfg, weights, filename);
else if(0==strcmp(argv[2], "train")) train_classifier(data, cfg, weights);
- else if(0==strcmp(argv[2], "test")) test_classifier(data, cfg, weights,filename, layer);
+ else if(0==strcmp(argv[2], "test")) test_classifier(data, cfg, weights, layer);
else if(0==strcmp(argv[2], "valid")) validate_classifier(data, cfg, weights);
}
--
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