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it's raining really hard outside :-( :rain: :storm: ☁️

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This commit is contained in:
Joseph Redmon
2017-10-17 11:41:34 -07:00
parent 532c6e1481
commit cd5d393b46
27 changed files with 1340 additions and 1669 deletions
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70
examples/yolo.c
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@ -10,17 +10,14 @@ void train_yolo(char *cfgfile, char *weightfile)
char *base = basecfg(cfgfile);
printf("%s\n", base);
float avg_loss = -1;
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 = net.batch*net.subdivisions;
int i = *net.seen/imgs;
network *net = load_network(cfgfile, weightfile, 0);
printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net->learning_rate, net->momentum, net->decay);
int imgs = net->batch*net->subdivisions;
int i = *net->seen/imgs;
data train, buffer;
layer l = net.layers[net.n - 1];
layer l = net->layers[net->n - 1];
int side = l.side;
int classes = l.classes;
@ -31,8 +28,8 @@ void train_yolo(char *cfgfile, char *weightfile)
char **paths = (char **)list_to_array(plist);
load_args args = {0};
args.w = net.w;
args.h = net.h;
args.w = net->w;
args.h = net->h;
args.paths = paths;
args.n = imgs;
args.m = plist->size;
@ -42,15 +39,15 @@ void train_yolo(char *cfgfile, char *weightfile)
args.d = &buffer;
args.type = REGION_DATA;
args.angle = net.angle;
args.exposure = net.exposure;
args.saturation = net.saturation;
args.hue = net.hue;
args.angle = net->angle;
args.exposure = net->exposure;
args.saturation = net->saturation;
args.hue = net->hue;
pthread_t load_thread = load_data_in_thread(args);
clock_t time;
//while(i*imgs < N*120){
while(get_current_batch(net) < net.max_batches){
while(get_current_batch(net) < net->max_batches){
i += 1;
time=clock();
pthread_join(load_thread, 0);
@ -98,14 +95,11 @@ void print_yolo_detections(FILE **fps, char *id, box *boxes, float **probs, int
}
}
void validate_yolo(char *cfgfile, char *weightfile)
void validate_yolo(char *cfg, char *weights)
{
network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&net, weightfile);
}
set_batch_network(&net, 1);
fprintf(stderr, "Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
network *net = load_network(cfg, weights, 0);
set_batch_network(net, 1);
fprintf(stderr, "Learning Rate: %g, Momentum: %g, Decay: %g\n", net->learning_rate, net->momentum, net->decay);
srand(time(0));
char *base = "results/comp4_det_test_";
@ -114,7 +108,7 @@ void validate_yolo(char *cfgfile, char *weightfile)
//list *plist = get_paths("data/voc.2012.test");
char **paths = (char **)list_to_array(plist);
layer l = net.layers[net.n-1];
layer l = net->layers[net->n-1];
int classes = l.classes;
int j;
@ -144,8 +138,8 @@ void validate_yolo(char *cfgfile, char *weightfile)
pthread_t *thr = calloc(nthreads, sizeof(pthread_t));
load_args args = {0};
args.w = net.w;
args.h = net.h;
args.w = net->w;
args.h = net->h;
args.type = IMAGE_DATA;
for(t = 0; t < nthreads; ++t){
@ -186,21 +180,18 @@ void validate_yolo(char *cfgfile, char *weightfile)
fprintf(stderr, "Total Detection Time: %f Seconds\n", (double)(time(0) - start));
}
void validate_yolo_recall(char *cfgfile, char *weightfile)
void validate_yolo_recall(char *cfg, char *weights)
{
network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&net, weightfile);
}
set_batch_network(&net, 1);
fprintf(stderr, "Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
network *net = load_network(cfg, weights, 0);
set_batch_network(net, 1);
fprintf(stderr, "Learning Rate: %g, Momentum: %g, Decay: %g\n", net->learning_rate, net->momentum, net->decay);
srand(time(0));
char *base = "results/comp4_det_test_";
list *plist = get_paths("data/voc.2007.test");
char **paths = (char **)list_to_array(plist);
layer l = net.layers[net.n-1];
layer l = net->layers[net->n-1];
int classes = l.classes;
int side = l.side;
@ -230,7 +221,7 @@ void validate_yolo_recall(char *cfgfile, char *weightfile)
for(i = 0; i < m; ++i){
char *path = paths[i];
image orig = load_image_color(path, 0, 0);
image sized = resize_image(orig, net.w, net.h);
image sized = resize_image(orig, net->w, net->h);
char *id = basecfg(path);
network_predict(net, sized.data);
get_detection_boxes(l, orig.w, orig.h, thresh, probs, boxes, 1);
@ -275,12 +266,9 @@ void validate_yolo_recall(char *cfgfile, char *weightfile)
void test_yolo(char *cfgfile, char *weightfile, char *filename, float thresh)
{
image **alphabet = load_alphabet();
network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&net, weightfile);
}
layer l = net.layers[net.n-1];
set_batch_network(&net, 1);
network *net = load_network(cfgfile, weightfile, 0);
layer l = net->layers[net->n-1];
set_batch_network(net, 1);
srand(2222222);
clock_t time;
char buff[256];
@ -301,7 +289,7 @@ void test_yolo(char *cfgfile, char *weightfile, char *filename, float thresh)
strtok(input, "\n");
}
image im = load_image_color(input,0,0);
image sized = resize_image(im, net.w, net.h);
image sized = resize_image(im, net->w, net->h);
float *X = sized.data;
time=clock();
network_predict(net, X);