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accidentally broke multigpu a while ago :-/

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This commit is contained in:
Joseph Redmon
2017-06-26 14:00:18 -07:00
parent 63ebd694d7
commit 59ed1719d4
12 changed files with 119 additions and 46 deletions
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1
examples/classifier.c
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@ -33,6 +33,7 @@ void train_classifier(char *datacfg, char *cfgfile, char *weightfile, int *gpus,
cuda_set_device(gpus[i]);
#endif
nets[i] = load_network(cfgfile, weightfile, clear);
nets[i].learning_rate *= ngpus;
}
srand(time(0));
network net = nets[0];

2
examples/darknet.c
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@ -337,7 +337,7 @@ void denormalize_net(char *cfgfile, char *weightfile, char *outfile)
int i;
for (i = 0; i < net.n; ++i) {
layer l = net.layers[i];
if (l.type == CONVOLUTIONAL && l.batch_normalize) {
if ((l.type == DECONVOLUTIONAL || l.type == CONVOLUTIONAL) && l.batch_normalize) {
denormalize_convolutional_layer(l);
net.layers[i].batch_normalize=0;
}

1
examples/detector.c
View File

@ -23,6 +23,7 @@ void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, i
cuda_set_device(gpus[i]);
#endif
nets[i] = load_network(cfgfile, weightfile, clear);
nets[i].learning_rate *= ngpus;
}
srand(time(0));
network net = nets[0];

3
examples/rnn.c
View File

@ -43,6 +43,7 @@ char **read_tokens(char *filename, size_t *read)
size = size*2;
d = realloc(d, size*sizeof(char *));
}
if(0==strcmp(line, "<NEWLINE>")) line = "\n";
d[count-1] = line;
}
fclose(fp);
@ -190,7 +191,7 @@ void train_char_rnn(char *cfgfile, char *weightfile, char *filename, int clear,
for(j = 0; j < streams; ++j){
//printf("%d\n", j);
if(rand()%10 == 0){
if(rand()%64 == 0){
//fprintf(stderr, "Reset\n");
offsets[j] = rand_size_t()%size;
reset_rnn_state(net, j);

33
examples/segmenter.c
View File

@ -2,7 +2,7 @@
#include <sys/time.h>
#include <assert.h>
void train_segmenter(char *datacfg, char *cfgfile, char *weightfile, int *gpus, int ngpus, int clear)
void train_segmenter(char *datacfg, char *cfgfile, char *weightfile, int *gpus, int ngpus, int clear, int display)
{
int i;
@ -95,9 +95,9 @@ void train_segmenter(char *datacfg, char *cfgfile, char *weightfile, int *gpus,
#else
loss = train_network(net, train);
#endif
if(1){
image tr = float_to_image(net.w/div, net.h/div, 80, train.y.vals[net.batch]);
image im = float_to_image(net.w, net.h, net.c, train.X.vals[net.batch]);
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 mask = mask_to_rgb(tr);
image prmask = mask_to_rgb(pred);
show_image(im, "input");
@ -163,10 +163,10 @@ void predict_segmenter(char *datafile, char *cfgfile, char *weightfile, char *fi
float *X = sized.data;
time=clock();
float *predictions = network_predict(net, X);
image m = float_to_image(sized.w, sized.h, 81, predictions);
image rgb = mask_to_rgb(m);
image pred = get_network_image(net);
image prmask = mask_to_rgb(pred);
show_image(sized, "orig");
show_image(rgb, "pred");
show_image(prmask, "pred");
#ifdef OPENCV
cvWaitKey(0);
#endif
@ -174,7 +174,7 @@ void predict_segmenter(char *datafile, char *cfgfile, char *weightfile, char *fi
printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
free_image(im);
free_image(sized);
free_image(rgb);
free_image(prmask);
if (filename) break;
}
}
@ -183,7 +183,7 @@ 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)
{
#ifdef OPENCV
printf("Regressor Demo\n");
printf("Classifier Demo\n");
network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&net, weightfile);
@ -200,8 +200,8 @@ void demo_segmenter(char *datacfg, char *cfgfile, char *weightfile, int cam_inde
}
if(!cap) error("Couldn't connect to webcam.\n");
cvNamedWindow("Regressor", CV_WINDOW_NORMAL);
cvResizeWindow("Regressor", 512, 512);
cvNamedWindow("Segmenter", CV_WINDOW_NORMAL);
cvResizeWindow("Segmenter", 512, 512);
float fps = 0;
while(1){
@ -210,7 +210,6 @@ void demo_segmenter(char *datacfg, char *cfgfile, char *weightfile, int cam_inde
image in = get_image_from_stream(cap);
image in_s = letterbox_image(in, net.w, net.h);
show_image(in, "Regressor");
float *predictions = network_predict(net, in_s.data);
@ -218,10 +217,13 @@ void demo_segmenter(char *datacfg, char *cfgfile, char *weightfile, int cam_inde
printf("\033[1;1H");
printf("\nFPS:%.0f\n",fps);
printf("People: %f\n", predictions[0]);
image pred = get_network_image(net);
image prmask = mask_to_rgb(pred);
show_image(prmask, "Segmenter");
free_image(in_s);
free_image(in);
free_image(prmask);
cvWaitKey(10);
@ -266,12 +268,13 @@ void run_segmenter(int argc, char **argv)
int cam_index = find_int_arg(argc, argv, "-c", 0);
int clear = find_arg(argc, argv, "-clear");
int display = find_arg(argc, argv, "-display");
char *data = argv[3];
char *cfg = argv[4];
char *weights = (argc > 5) ? argv[5] : 0;
char *filename = (argc > 6) ? argv[6]: 0;
if(0==strcmp(argv[2], "test")) predict_segmenter(data, cfg, weights, filename);
else if(0==strcmp(argv[2], "train")) train_segmenter(data, cfg, weights, gpus, ngpus, clear);
else if(0==strcmp(argv[2], "train")) train_segmenter(data, cfg, weights, gpus, ngpus, clear, display);
else if(0==strcmp(argv[2], "demo")) demo_segmenter(data, cfg, weights, cam_index, filename);
}