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classifier.c - add the awesome training chart and make sure "top" is not bigger than "classes" in datacfg file.

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pull/913/head
vinjn 7 years ago
parent 6b6f0f0ca3
commit b36512ea2e
1 changed files with 80 additions and 36 deletions
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  1. 70
      src/classifier.c

70
src/classifier.c
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@ -23,6 +23,10 @@
image get_image_from_stream(CvCapture *cap);
image get_image_from_stream_cpp(CvCapture *cap);
#include "http_stream.h"
IplImage* draw_train_chart(float max_img_loss, int max_batches, int number_of_lines, int img_size);
void draw_train_loss(IplImage* img, int img_size, float avg_loss, float max_img_loss, int current_batch, int max_batches);
#endif
float *get_regression_values(char **labels, int n)
@ -37,7 +41,7 @@ float *get_regression_values(char **labels, int n)
return v;
}
void train_classifier(char *datacfg, char *cfgfile, char *weightfile, int *gpus, int ngpus, int clear)
void train_classifier(char *datacfg, char *cfgfile, char *weightfile, int *gpus, int ngpus, int clear, int dont_show)
{
int i;
@ -104,13 +108,23 @@ void train_classifier(char *datacfg, char *cfgfile, char *weightfile, int *gpus,
args.labels = labels;
args.type = CLASSIFICATION_DATA;
#ifdef OPENCV
args.threads = 3;
IplImage* img = NULL;
float max_img_loss = 5;
int number_of_lines = 100;
int img_size = 1000;
if (!dont_show)
img = draw_train_chart(max_img_loss, net.max_batches, number_of_lines, img_size);
#endif //OPENCV
data train;
data buffer;
pthread_t load_thread;
args.d = &buffer;
load_thread = load_data(args);
int epoch = (*net.seen)/N;
int iter_save = get_current_batch(net);
while(get_current_batch(net) < net.max_batches || net.max_batches == 0){
time=clock();
@ -133,24 +147,38 @@ void train_classifier(char *datacfg, char *cfgfile, char *weightfile, int *gpus,
#endif
if(avg_loss == -1) avg_loss = loss;
avg_loss = avg_loss*.9 + loss*.1;
i = get_current_batch(net);
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(*net.seen/N > epoch){
epoch = *net.seen/N;
char buff[256];
sprintf(buff, "%s/%s_%d.weights",backup_directory,base, epoch);
save_weights(net, buff);
}
if(get_current_batch(net)%100 == 0){
#ifdef OPENCV
if(!dont_show)
draw_train_loss(img, img_size, avg_loss, max_img_loss, i, net.max_batches);
#endif // OPENCV
if (i >= (iter_save + 100)) {
iter_save = i;
#ifdef GPU
if (ngpus != 1) sync_nets(nets, ngpus, 0);
#endif
char buff[256];
sprintf(buff, "%s/%s.backup",backup_directory,base);
sprintf(buff, "%s/%s_%d.weights",backup_directory,base, i);
save_weights(net, buff);
}
free_data(train);
}
#ifdef GPU
if (ngpus != 1) sync_nets(nets, ngpus, 0);
#endif
char buff[256];
sprintf(buff, "%s/%s.weights", backup_directory, base);
sprintf(buff, "%s/%s_final.weights", backup_directory, base);
save_weights(net, buff);
#ifdef OPENCV
cvReleaseImage(&img);
cvDestroyAllWindows();
#endif
free_network(net);
free_ptrs((void**)labels, classes);
free_ptrs((void**)paths, plist->size);
@ -285,6 +313,7 @@ void validate_classifier_crop(char *datacfg, char *filename, char *weightfile)
char *valid_list = option_find_str(options, "valid", "data/train.list");
int classes = option_find_int(options, "classes", 2);
int topk = option_find_int(options, "top", 1);
if (topk > classes) topk = classes;
char **labels = get_labels(label_list);
list *plist = get_paths(valid_list);
@ -353,6 +382,7 @@ void validate_classifier_10(char *datacfg, char *filename, char *weightfile)
char *valid_list = option_find_str(options, "valid", "data/train.list");
int classes = option_find_int(options, "classes", 2);
int topk = option_find_int(options, "top", 1);
if (topk > classes) topk = classes;
char **labels = get_labels(label_list);
list *plist = get_paths(valid_list);
@ -425,6 +455,7 @@ void validate_classifier_full(char *datacfg, char *filename, char *weightfile)
char *valid_list = option_find_str(options, "valid", "data/train.list");
int classes = option_find_int(options, "classes", 2);
int topk = option_find_int(options, "top", 1);
if (topk > classes) topk = classes;
char **labels = get_labels(label_list);
list *plist = get_paths(valid_list);
@ -488,6 +519,7 @@ void validate_classifier_single(char *datacfg, char *filename, char *weightfile)
char *valid_list = option_find_str(options, "valid", "data/train.list");
int classes = option_find_int(options, "classes", 2);
int topk = option_find_int(options, "top", 1);
if (topk > classes) topk = classes;
char **labels = get_labels(label_list);
list *plist = get_paths(valid_list);
@ -548,6 +580,7 @@ void validate_classifier_multi(char *datacfg, char *filename, char *weightfile)
char *valid_list = option_find_str(options, "valid", "data/train.list");
int classes = option_find_int(options, "classes", 2);
int topk = option_find_int(options, "top", 1);
if (topk > classes) topk = classes;
char **labels = get_labels(label_list);
list *plist = get_paths(valid_list);
@ -609,7 +642,9 @@ void try_classifier(char *datacfg, char *cfgfile, char *weightfile, char *filena
char *name_list = option_find_str(options, "names", 0);
if(!name_list) name_list = option_find_str(options, "labels", "data/labels.list");
int classes = option_find_int(options, "classes", 2);
int top = option_find_int(options, "top", 1);
if (top > classes) top = classes;
int i = 0;
char **names = get_labels(name_list);
@ -690,7 +725,9 @@ void predict_classifier(char *datacfg, char *cfgfile, char *weightfile, char *fi
char *name_list = option_find_str(options, "names", 0);
if(!name_list) name_list = option_find_str(options, "labels", "data/labels.list");
int classes = option_find_int(options, "classes", 2);
if (top == 0) top = option_find_int(options, "top", 1);
if (top > classes) top = classes;
int i = 0;
char **names = get_labels(name_list);
@ -871,7 +908,9 @@ void threat_classifier(char *datacfg, char *cfgfile, char *weightfile, int cam_i
cap = get_capture_webcam(cam_index);
}
int classes = option_find_int(options, "classes", 2);
int top = option_find_int(options, "top", 1);
if (top > classes) top = classes;
char *name_list = option_find_str(options, "names", 0);
char **names = get_labels(name_list);
@ -1007,7 +1046,9 @@ void gun_classifier(char *datacfg, char *cfgfile, char *weightfile, int cam_inde
cap = get_capture_webcam(cam_index);
}
int classes = option_find_int(options, "classes", 2);
int top = option_find_int(options, "top", 1);
if (top > classes) top = classes;
char *name_list = option_find_str(options, "names", 0);
char **names = get_labels(name_list);
@ -1087,7 +1128,9 @@ void demo_classifier(char *datacfg, char *cfgfile, char *weightfile, int cam_ind
cap = get_capture_webcam(cam_index);
}
int classes = option_find_int(options, "classes", 2);
int top = option_find_int(options, "top", 1);
if (top > classes) top = classes;
char *name_list = option_find_str(options, "names", 0);
char **names = get_labels(name_list);
@ -1166,6 +1209,7 @@ void run_classifier(int argc, char **argv)
ngpus = 1;
}
int dont_show = find_arg(argc, argv, "-dont_show");
int cam_index = find_int_arg(argc, argv, "-c", 0);
int top = find_int_arg(argc, argv, "-t", 0);
int clear = find_arg(argc, argv, "-clear");
@ -1177,7 +1221,7 @@ void run_classifier(int argc, char **argv)
int layer = layer_s ? atoi(layer_s) : -1;
if(0==strcmp(argv[2], "predict")) predict_classifier(data, cfg, weights, filename, top);
else if(0==strcmp(argv[2], "try")) try_classifier(data, cfg, weights, filename, atoi(layer_s));
else if(0==strcmp(argv[2], "train")) train_classifier(data, cfg, weights, gpus, ngpus, clear);
else if(0==strcmp(argv[2], "train")) train_classifier(data, cfg, weights, gpus, ngpus, clear, dont_show);
else if(0==strcmp(argv[2], "demo")) demo_classifier(data, cfg, weights, cam_index, filename);
else if(0==strcmp(argv[2], "gun")) gun_classifier(data, cfg, weights, cam_index, filename);
else if(0==strcmp(argv[2], "threat")) threat_classifier(data, cfg, weights, cam_index, filename);

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