From ec766fc3f114dd4faaa3add500776a7bae957ba5 Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Tue, 29 May 2018 11:35:32 +0000
Subject: [PATCH] Ignore empty extra lines in train.txt
---
src/classifier.c | 160 ++++++++++++++++++++++++++++++++++++----------------
1 files changed, 110 insertions(+), 50 deletions(-)
diff --git a/src/classifier.c b/src/classifier.c
index 5e718c5..b38f2fe 100644
--- a/src/classifier.c
+++ b/src/classifier.c
@@ -21,6 +21,12 @@
#include "opencv2/videoio/videoio_c.h"
#endif
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)
@@ -35,7 +41,7 @@
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;
@@ -87,6 +93,7 @@
args.min = net.min_crop;
args.max = net.max_crop;
+ args.flip = net.flip;
args.angle = net.angle;
args.aspect = net.aspect;
args.exposure = net.exposure;
@@ -101,13 +108,23 @@
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();
@@ -130,24 +147,38 @@
#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);
+#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_%d.weights",backup_directory,base, i);
+ save_weights(net, buff);
+ }
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){
- char buff[256];
- sprintf(buff, "%s/%s.backup",backup_directory,base);
- save_weights(net, buff);
- }
}
+#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);
@@ -193,6 +224,7 @@
args.min = net.min_crop;
args.max = net.max_crop;
+ args.flip = net.flip;
args.angle = net.angle;
args.aspect = net.aspect;
args.exposure = net.exposure;
@@ -281,6 +313,7 @@
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);
@@ -349,6 +382,7 @@
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);
@@ -362,11 +396,11 @@
int *indexes = calloc(topk, sizeof(int));
for(i = 0; i < m; ++i){
- int class = -1;
+ int class_id = -1;
char *path = paths[i];
for(j = 0; j < classes; ++j){
if(strstr(path, labels[j])){
- class = j;
+ class_id = j;
break;
}
}
@@ -396,9 +430,9 @@
free_image(im);
top_k(pred, classes, topk, indexes);
free(pred);
- if(indexes[0] == class) avg_acc += 1;
+ if(indexes[0] == class_id) avg_acc += 1;
for(j = 0; j < topk; ++j){
- if(indexes[j] == class) avg_topk += 1;
+ if(indexes[j] == class_id) avg_topk += 1;
}
printf("%d: top 1: %f, top %d: %f\n", i, avg_acc/(i+1), topk, avg_topk/(i+1));
@@ -421,6 +455,7 @@
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);
@@ -435,11 +470,11 @@
int size = net.w;
for(i = 0; i < m; ++i){
- int class = -1;
+ int class_id = -1;
char *path = paths[i];
for(j = 0; j < classes; ++j){
if(strstr(path, labels[j])){
- class = j;
+ class_id = j;
break;
}
}
@@ -456,9 +491,9 @@
free_image(resized);
top_k(pred, classes, topk, indexes);
- if(indexes[0] == class) avg_acc += 1;
+ if(indexes[0] == class_id) avg_acc += 1;
for(j = 0; j < topk; ++j){
- if(indexes[j] == class) avg_topk += 1;
+ if(indexes[j] == class_id) avg_topk += 1;
}
printf("%d: top 1: %f, top %d: %f\n", i, avg_acc/(i+1), topk, avg_topk/(i+1));
@@ -484,6 +519,7 @@
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);
@@ -497,11 +533,11 @@
int *indexes = calloc(topk, sizeof(int));
for(i = 0; i < m; ++i){
- int class = -1;
+ int class_id = -1;
char *path = paths[i];
for(j = 0; j < classes; ++j){
if(strstr(path, labels[j])){
- class = j;
+ class_id = j;
break;
}
}
@@ -519,9 +555,9 @@
free_image(crop);
top_k(pred, classes, topk, indexes);
- if(indexes[0] == class) avg_acc += 1;
+ if(indexes[0] == class_id) avg_acc += 1;
for(j = 0; j < topk; ++j){
- if(indexes[j] == class) avg_topk += 1;
+ if(indexes[j] == class_id) avg_topk += 1;
}
printf("%d: top 1: %f, top %d: %f\n", i, avg_acc/(i+1), topk, avg_topk/(i+1));
@@ -544,6 +580,7 @@
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);
@@ -559,11 +596,11 @@
int *indexes = calloc(topk, sizeof(int));
for(i = 0; i < m; ++i){
- int class = -1;
+ int class_id = -1;
char *path = paths[i];
for(j = 0; j < classes; ++j){
if(strstr(path, labels[j])){
- class = j;
+ class_id = j;
break;
}
}
@@ -583,9 +620,9 @@
free_image(im);
top_k(pred, classes, topk, indexes);
free(pred);
- if(indexes[0] == class) avg_acc += 1;
+ if(indexes[0] == class_id) avg_acc += 1;
for(j = 0; j < topk; ++j){
- if(indexes[j] == class) avg_topk += 1;
+ if(indexes[j] == class_id) avg_topk += 1;
}
printf("%d: top 1: %f, top %d: %f\n", i, avg_acc/(i+1), topk, avg_topk/(i+1));
@@ -594,7 +631,7 @@
void try_classifier(char *datacfg, char *cfgfile, char *weightfile, char *filename, int layer_num)
{
- network net = parse_network_cfg(cfgfile);
+ network net = parse_network_cfg_custom(cfgfile, 1);
if(weightfile){
load_weights(&net, weightfile);
}
@@ -605,7 +642,9 @@
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);
@@ -675,7 +714,7 @@
void predict_classifier(char *datacfg, char *cfgfile, char *weightfile, char *filename, int top)
{
- network net = parse_network_cfg(cfgfile);
+ network net = parse_network_cfg_custom(cfgfile, 1);
if(weightfile){
load_weights(&net, weightfile);
}
@@ -686,7 +725,9 @@
char *name_list = option_find_str(options, "names", 0);
if(!name_list) name_list = option_find_str(options, "labels", "data/labels.list");
- if(top == 0) top = option_find_int(options, "top", 1);
+ 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);
@@ -706,8 +747,9 @@
strtok(input, "\n");
}
image im = load_image_color(input, 0, 0);
- image r = resize_min(im, size);
- resize_network(&net, r.w, r.h);
+ image r = letterbox_image(im, net.w, net.h);
+ //image r = resize_min(im, size);
+ //resize_network(&net, r.w, r.h);
printf("%d %d\n", r.w, r.h);
float *X = r.data;
@@ -857,13 +899,18 @@
srand(2222222);
CvCapture * cap;
- if(filename){
- cap = cvCaptureFromFile(filename);
- }else{
- cap = cvCaptureFromCAM(cam_index);
+ if (filename) {
+ //cap = cvCaptureFromFile(filename);
+ cap = get_capture_video_stream(filename);
+ }
+ else {
+ //cap = cvCaptureFromCAM(cam_index);
+ 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);
@@ -883,7 +930,8 @@
struct timeval tval_before, tval_after, tval_result;
gettimeofday(&tval_before, NULL);
- image in = get_image_from_stream(cap);
+ //image in = get_image_from_stream(cap);
+ image in = get_image_from_stream_cpp(cap);
if(!in.data) break;
image in_s = resize_image(in, net.w, net.h);
@@ -989,13 +1037,18 @@
srand(2222222);
CvCapture * cap;
- if(filename){
- cap = cvCaptureFromFile(filename);
- }else{
- cap = cvCaptureFromCAM(cam_index);
+ if (filename) {
+ //cap = cvCaptureFromFile(filename);
+ cap = get_capture_video_stream(filename);
+ }
+ else {
+ //cap = cvCaptureFromCAM(cam_index);
+ 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);
@@ -1012,7 +1065,8 @@
struct timeval tval_before, tval_after, tval_result;
gettimeofday(&tval_before, NULL);
- image in = get_image_from_stream(cap);
+ //image in = get_image_from_stream(cap);
+ image in = get_image_from_stream_cpp(cap);
image in_s = resize_image(in, net.w, net.h);
show_image(in, "Threat Detection");
@@ -1056,7 +1110,7 @@
{
#ifdef OPENCV
printf("Classifier Demo\n");
- network net = parse_network_cfg(cfgfile);
+ network net = parse_network_cfg_custom(cfgfile, 1);
if(weightfile){
load_weights(&net, weightfile);
}
@@ -1067,12 +1121,16 @@
CvCapture * cap;
if(filename){
- cap = cvCaptureFromFile(filename);
+ //cap = cvCaptureFromFile(filename);
+ cap = get_capture_video_stream(filename);
}else{
- cap = cvCaptureFromCAM(cam_index);
+ //cap = cvCaptureFromCAM(cam_index);
+ 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);
@@ -1089,7 +1147,8 @@
struct timeval tval_before, tval_after, tval_result;
gettimeofday(&tval_before, NULL);
- image in = get_image_from_stream(cap);
+ //image in = get_image_from_stream(cap);
+ image in = get_image_from_stream_cpp(cap);
image in_s = resize_image(in, net.w, net.h);
show_image(in, "Classifier");
@@ -1150,6 +1209,7 @@
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");
@@ -1161,7 +1221,7 @@
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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