From db0397cfaaf488364e3d2e1669dfefae2ee6ea73 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Mon, 14 Dec 2015 19:57:10 +0000
Subject: [PATCH] shortcut layers, msr networks
---
src/imagenet.c | 111 ++++++++++++++++++++++++++++++++++++++-----------------
1 files changed, 77 insertions(+), 34 deletions(-)
diff --git a/src/imagenet.c b/src/imagenet.c
index 906dbd4..dece952 100644
--- a/src/imagenet.c
+++ b/src/imagenet.c
@@ -2,12 +2,17 @@
#include "utils.h"
#include "parser.h"
+#ifdef OPENCV
+#include "opencv2/highgui/highgui_c.h"
+#endif
+
void train_imagenet(char *cfgfile, char *weightfile)
{
data_seed = time(0);
srand(time(0));
float avg_loss = -1;
char *base = basecfg(cfgfile);
+ char *backup_directory = "/home/pjreddie/backup/";
printf("%s\n", base);
network net = parse_network_cfg(cfgfile);
if(weightfile){
@@ -15,44 +20,60 @@
}
printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
int imgs = 1024;
- int i = net.seen/imgs;
- char **labels = get_labels("/home/pjreddie/data/imagenet/cls.labels.list");
+ char **labels = get_labels("data/inet.labels.list");
list *plist = get_paths("/data/imagenet/cls.train.list");
char **paths = (char **)list_to_array(plist);
printf("%d\n", plist->size);
+ int N = plist->size;
clock_t time;
pthread_t load_thread;
data train;
data buffer;
- load_thread = load_data_thread(paths, imgs, plist->size, labels, 1000, 256, 256, &buffer);
- while(1){
- ++i;
+
+ load_args args = {0};
+ args.w = net.w;
+ args.h = net.h;
+ args.paths = paths;
+ args.classes = 1000;
+ args.n = imgs;
+ args.m = N;
+ args.labels = labels;
+ args.d = &buffer;
+ args.type = CLASSIFICATION_DATA;
+
+ load_thread = load_data_in_thread(args);
+ int epoch = (*net.seen)/N;
+ while(get_current_batch(net) < net.max_batches || net.max_batches == 0){
time=clock();
pthread_join(load_thread, 0);
train = buffer;
-/*
- image im = float_to_image(256, 256, 3, train.X.vals[114]);
- show_image(im, "training");
- cvWaitKey(0);
- */
-
- load_thread = load_data_thread(paths, imgs, plist->size, labels, 1000, 256, 256, &buffer);
+ load_thread = load_data_in_thread(args);
printf("Loaded: %lf seconds\n", sec(clock()-time));
time=clock();
float loss = train_network(net, train);
- net.seen += imgs;
if(avg_loss == -1) 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), net.seen);
+ printf("%d, %.3f: %f, %f avg, %f rate, %lf seconds, %d images\n", get_current_batch(net), (float)(*net.seen)/N, loss, avg_loss, get_current_rate(net), sec(clock()-time), *net.seen);
free_data(train);
- //if(i%100 == 0 && net.learning_rate > .00001) net.learning_rate *= .97;
- if(i%100==0){
+ if(*net.seen/N > epoch){
+ epoch = *net.seen/N;
char buff[256];
- sprintf(buff, "/home/pjreddie/imagenet_backup/%s_%d.weights",base, i);
+ sprintf(buff, "%s/%s_%d.weights",backup_directory,base, epoch);
save_weights(net, buff);
}
}
+ char buff[256];
+ sprintf(buff, "%s/%s.weights", backup_directory, base);
+ save_weights(net, buff);
+
+ pthread_join(load_thread, 0);
+ free_data(buffer);
+ free_network(net);
+ free_ptrs((void**)labels, 1000);
+ free_ptrs((void**)paths, plist->size);
+ free_list(plist);
+ free(base);
}
void validate_imagenet(char *filename, char *weightfile)
@@ -64,9 +85,10 @@
}
srand(time(0));
- char **labels = get_labels("/home/pjreddie/data/imagenet/cls.val.labels.list");
+ char **labels = get_labels("data/inet.labels.list");
+ //list *plist = get_paths("data/inet.suppress.list");
+ list *plist = get_paths("data/inet.val.list");
- list *plist = get_paths("/data/imagenet/cls.val.list");
char **paths = (char **)list_to_array(plist);
int m = plist->size;
free_list(plist);
@@ -78,7 +100,19 @@
int num = (i+1)*m/splits - i*m/splits;
data val, buffer;
- pthread_t load_thread = load_data_thread(paths, num, 0, labels, 1000, 256, 256, &buffer);
+
+ load_args args = {0};
+ args.w = net.w;
+ args.h = net.h;
+ args.paths = paths;
+ args.classes = 1000;
+ args.n = num;
+ args.m = 0;
+ args.labels = labels;
+ args.d = &buffer;
+ args.type = CLASSIFICATION_DATA;
+
+ pthread_t load_thread = load_data_in_thread(args);
for(i = 1; i <= splits; ++i){
time=clock();
@@ -87,11 +121,14 @@
num = (i+1)*m/splits - i*m/splits;
char **part = paths+(i*m/splits);
- if(i != splits) load_thread = load_data_thread(part, num, 0, labels, 1000, 256, 256, &buffer);
+ if(i != splits){
+ args.paths = part;
+ load_thread = load_data_in_thread(args);
+ }
printf("Loaded: %d images in %lf seconds\n", val.X.rows, sec(clock()-time));
time=clock();
- float *acc = network_accuracies(net, val);
+ float *acc = network_accuracies(net, val, 5);
avg_acc += acc[0];
avg_top5 += acc[1];
printf("%d: top1: %f, top5: %f, %lf seconds, %d images\n", i, avg_acc/i, avg_top5/i, sec(clock()-time), val.X.rows);
@@ -99,37 +136,42 @@
}
}
-void test_imagenet(char *cfgfile, char *weightfile)
+void test_imagenet(char *cfgfile, char *weightfile, char *filename)
{
network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&net, weightfile);
}
set_batch_network(&net, 1);
- //imgs=1;
srand(2222222);
int i = 0;
- char **names = get_labels("cfg/shortnames.txt");
+ char **names = get_labels("data/shortnames.txt");
clock_t time;
- char filename[256];
int indexes[10];
+ char buff[256];
+ char *input = buff;
while(1){
- fgets(filename, 256, stdin);
- strtok(filename, "\n");
- image im = load_image_color(filename, 256, 256);
- scale_image(im, 2.);
- translate_image(im, -1.);
- printf("%d %d %d\n", im.h, im.w, im.c);
+ if(filename){
+ strncpy(input, filename, 256);
+ }else{
+ printf("Enter Image Path: ");
+ fflush(stdout);
+ input = fgets(input, 256, stdin);
+ if(!input) return;
+ strtok(input, "\n");
+ }
+ image im = load_image_color(input, 256, 256);
float *X = im.data;
time=clock();
float *predictions = network_predict(net, X);
top_predictions(net, 10, indexes);
- printf("%s: Predicted in %f seconds.\n", filename, sec(clock()-time));
+ printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
for(i = 0; i < 10; ++i){
int index = indexes[i];
printf("%s: %f\n", names[index], predictions[index]);
}
free_image(im);
+ if (filename) break;
}
}
@@ -142,7 +184,8 @@
char *cfg = argv[3];
char *weights = (argc > 4) ? argv[4] : 0;
- if(0==strcmp(argv[2], "test")) test_imagenet(cfg, weights);
+ char *filename = (argc > 5) ? argv[5]: 0;
+ if(0==strcmp(argv[2], "test")) test_imagenet(cfg, weights, filename);
else if(0==strcmp(argv[2], "train")) train_imagenet(cfg, weights);
else if(0==strcmp(argv[2], "valid")) validate_imagenet(cfg, weights);
}
--
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