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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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77
examples/segmenter.c
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@ -10,7 +10,7 @@ void train_segmenter(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();
@ -19,23 +19,20 @@ void train_segmenter(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] = load_network(cfgfile, weightfile, clear);
nets[i]->learning_rate *= ngpus;
}
srand(time(0));
network net = nets[0];
network *net = nets[0];
image pred = get_network_image(net);
int div = net.w/pred.w;
assert(pred.w * div == net.w);
assert(pred.h * div == net.h);
int div = net->w/pred.w;
assert(pred.w * div == net->w);
assert(pred.h * div == net->h);
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/");
@ -48,19 +45,19 @@ void train_segmenter(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.scale = div;
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.classes = 80;
args.paths = paths;
@ -74,8 +71,8 @@ void train_segmenter(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);
@ -96,8 +93,8 @@ void train_segmenter(char *datacfg, char *cfgfile, char *weightfile, int *gpus,
loss = train_network(net, train);
#endif
if(display){
image tr = float_to_image(net.w/div, net.h/div, 80, train.y.vals[net.batch*(net.subdivisions-1)]);
image im = float_to_image(net.w, net.h, net.c, train.X.vals[net.batch*(net.subdivisions-1)]);
image tr = float_to_image(net->w/div, net->h/div, 80, train.y.vals[net->batch*(net->subdivisions-1)]);
image im = float_to_image(net->w, net->h, net->c, train.X.vals[net->batch*(net->subdivisions-1)]);
image mask = mask_to_rgb(tr);
image prmask = mask_to_rgb(pred);
show_image(im, "input");
@ -111,10 +108,10 @@ void train_segmenter(char *datacfg, char *cfgfile, char *weightfile, int *gpus,
}
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);
@ -135,13 +132,10 @@ void train_segmenter(char *datacfg, char *cfgfile, char *weightfile, int *gpus,
free(base);
}
void predict_segmenter(char *datafile, char *cfgfile, char *weightfile, char *filename)
void predict_segmenter(char *datafile, char *cfg, char *weights, char *filename)
{
network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&net, weightfile);
}
set_batch_network(&net, 1);
network *net = load_network(cfg, weights, 0);
set_batch_network(net, 1);
srand(2222222);
clock_t time;
@ -158,7 +152,7 @@ void predict_segmenter(char *datafile, char *cfgfile, char *weightfile, char *fi
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();
@ -180,15 +174,12 @@ void predict_segmenter(char *datafile, char *cfgfile, char *weightfile, char *fi
}
void demo_segmenter(char *datacfg, char *cfgfile, char *weightfile, int cam_index, const char *filename)
void demo_segmenter(char *datacfg, char *cfg, char *weights, int cam_index, const char *filename)
{
#ifdef OPENCV
printf("Classifier Demo\n");
network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&net, weightfile);
}
set_batch_network(&net, 1);
network *net = load_network(cfg, weights, 0);
set_batch_network(net, 1);
srand(2222222);
CvCapture * cap;
@ -209,7 +200,7 @@ void demo_segmenter(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);
network_predict(net, in_s.data);