#include "network.h"
|
#include "utils.h"
|
#include "parser.h"
|
|
#ifdef OPENCV
|
#include "opencv2/highgui/highgui_c.h"
|
#endif
|
|
void train_writing(char *cfgfile, char *weightfile)
|
{
|
char *backup_directory = "/home/pjreddie/backup/";
|
data_seed = time(0);
|
srand(time(0));
|
float avg_loss = -1;
|
char *base = basecfg(cfgfile);
|
printf("%s\n", base);
|
network net = parse_network_cfg(cfgfile);
|
if(weightfile){
|
load_weights(&net, weightfile);
|
}
|
printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
|
int imgs = 1024;
|
int i = *net.seen/imgs;
|
list *plist = get_paths("figures.list");
|
char **paths = (char **)list_to_array(plist);
|
printf("%d\n", plist->size);
|
clock_t time;
|
while(1){
|
++i;
|
time=clock();
|
data train = load_data_writing(paths, imgs, plist->size, 256, 256, 1);
|
printf("Loaded %lf seconds\n",sec(clock()-time));
|
time=clock();
|
float loss = train_network(net, train);
|
|
/*
|
image pred = float_to_image(64, 64, 1, out);
|
print_image(pred);
|
*/
|
|
/*
|
image im = float_to_image(256, 256, 3, train.X.vals[0]);
|
image lab = float_to_image(64, 64, 1, train.y.vals[0]);
|
image pred = float_to_image(64, 64, 1, out);
|
show_image(im, "image");
|
show_image(lab, "label");
|
print_image(lab);
|
show_image(pred, "pred");
|
cvWaitKey(0);
|
*/
|
|
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);
|
free_data(train);
|
//if(i%100 == 0 && net.learning_rate > .00001) net.learning_rate *= .97;
|
if(i%1000==0){
|
char buff[256];
|
sprintf(buff, "%s/%s_%d.weights", backup_directory, base, i);
|
save_weights(net, buff);
|
}
|
}
|
}
|
|
void test_writing(char *cfgfile, char *weightfile, char *outfile)
|
{
|
network net = parse_network_cfg(cfgfile);
|
if(weightfile){
|
load_weights(&net, weightfile);
|
}
|
set_batch_network(&net, 1);
|
srand(2222222);
|
clock_t time;
|
char filename[256];
|
|
fgets(filename, 256, stdin);
|
strtok(filename, "\n");
|
image im = load_image_color(filename, 0, 0);
|
//image im = load_image_color("/home/pjreddie/darknet/data/figs/C02-1001-Figure-1.png", 0, 0);
|
image sized = resize_image(im, net.w, net.h);
|
printf("%d %d %d\n", im.h, im.w, im.c);
|
float *X = sized.data;
|
time=clock();
|
network_predict(net, X);
|
printf("%s: Predicted in %f seconds.\n", filename, sec(clock()-time));
|
image pred = get_network_image(net);
|
|
if (outfile) {
|
printf("Save image as %s.png (shape: %d %d)\n", outfile, pred.w, pred.h);
|
save_image(pred, outfile);
|
} else {
|
show_image(pred, "prediction");
|
#ifdef OPENCV
|
cvWaitKey(0);
|
cvDestroyAllWindows();
|
#endif
|
}
|
|
free_image(im);
|
free_image(sized);
|
}
|
|
void run_writing(int argc, char **argv)
|
{
|
if(argc < 4){
|
fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]);
|
return;
|
}
|
|
char *cfg = argv[3];
|
char *weights = (argc > 4) ? argv[4] : 0;
|
char *outfile = (argc > 5) ? argv[5] : 0;
|
if(0==strcmp(argv[2], "train")) train_writing(cfg, weights);
|
else if(0==strcmp(argv[2], "test")) test_writing(cfg, weights, outfile);
|
}
|
