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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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64
examples/regressor.c
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@ -10,7 +10,7 @@ void train_regressor(char *datacfg, char *cfgfile, char *weightfile, int *gpus,
char *base = basecfg(cfgfile);
printf("%s\n", base);
printf("%d\n", ngpus);
network *nets = calloc(ngpus, sizeof(network));
network **nets = calloc(ngpus, sizeof(network*));
srand(time(0));
int seed = rand();
@ -19,19 +19,15 @@ void train_regressor(char *datacfg, char *cfgfile, char *weightfile, int *gpus,
#ifdef GPU
cuda_set_device(gpus[i]);
#endif
nets[i] = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&nets[i], weightfile);
}
if(clear) *nets[i].seen = 0;
nets[i].learning_rate *= ngpus;
nets[i] = load_network(cfgfile, weightfile, clear);
nets[i]->learning_rate *= ngpus;
}
srand(time(0));
network net = nets[0];
network *net = nets[0];
int imgs = net.batch * net.subdivisions * ngpus;
int imgs = net->batch * net->subdivisions * ngpus;
printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net->learning_rate, net->momentum, net->decay);
list *options = read_data_cfg(datacfg);
char *backup_directory = option_find_str(options, "backup", "/backup/");
@ -44,18 +40,18 @@ void train_regressor(char *datacfg, char *cfgfile, char *weightfile, int *gpus,
clock_t time;
load_args args = {0};
args.w = net.w;
args.h = net.h;
args.w = net->w;
args.h = net->h;
args.threads = 32;
args.min = net.min_crop;
args.max = net.max_crop;
args.angle = net.angle;
args.aspect = net.aspect;
args.exposure = net.exposure;
args.saturation = net.saturation;
args.hue = net.hue;
args.size = net.w;
args.min = net->min_crop;
args.max = net->max_crop;
args.angle = net->angle;
args.aspect = net->aspect;
args.exposure = net->exposure;
args.saturation = net->saturation;
args.hue = net->hue;
args.size = net->w;
args.paths = paths;
args.n = imgs;
@ -68,8 +64,8 @@ void train_regressor(char *datacfg, char *cfgfile, char *weightfile, int *gpus,
args.d = &buffer;
load_thread = load_data(args);
int epoch = (*net.seen)/N;
while(get_current_batch(net) < net.max_batches || net.max_batches == 0){
int epoch = (*net->seen)/N;
while(get_current_batch(net) < net->max_batches || net->max_batches == 0){
time=clock();
pthread_join(load_thread, 0);
@ -91,10 +87,10 @@ void train_regressor(char *datacfg, char *cfgfile, char *weightfile, int *gpus,
#endif
if(avg_loss == -1) avg_loss = loss;
avg_loss = avg_loss*.9 + loss*.1;
printf("%ld, %.3f: %f, %f avg, %f rate, %lf seconds, %ld images\n", get_current_batch(net), (float)(*net.seen)/N, loss, avg_loss, get_current_rate(net), sec(clock()-time), *net.seen);
printf("%ld, %.3f: %f, %f avg, %f rate, %lf seconds, %ld 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;
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);
@ -117,11 +113,8 @@ void train_regressor(char *datacfg, char *cfgfile, char *weightfile, int *gpus,
void predict_regressor(char *cfgfile, char *weightfile, char *filename)
{
network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&net, weightfile);
}
set_batch_network(&net, 1);
network *net = load_network(cfgfile, weightfile, 0);
set_batch_network(net, 1);
srand(2222222);
clock_t time;
@ -138,7 +131,7 @@ void predict_regressor(char *cfgfile, char *weightfile, char *filename)
strtok(input, "\n");
}
image im = load_image_color(input, 0, 0);
image sized = letterbox_image(im, net.w, net.h);
image sized = letterbox_image(im, net->w, net->h);
float *X = sized.data;
time=clock();
@ -156,11 +149,8 @@ void demo_regressor(char *datacfg, char *cfgfile, char *weightfile, int cam_inde
{
#ifdef OPENCV
printf("Regressor Demo\n");
network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&net, weightfile);
}
set_batch_network(&net, 1);
network *net = load_network(cfgfile, weightfile, 0);
set_batch_network(net, 1);
srand(2222222);
CvCapture * cap;
@ -181,7 +171,7 @@ void demo_regressor(char *datacfg, char *cfgfile, char *weightfile, int cam_inde
gettimeofday(&tval_before, NULL);
image in = get_image_from_stream(cap);
image in_s = letterbox_image(in, net.w, net.h);
image in_s = letterbox_image(in, net->w, net->h);
show_image(in, "Regressor");
float *predictions = network_predict(net, in_s.data);