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pathing changes and stuff

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This commit is contained in:
Joseph Redmon 2015-06-16 11:45:40 -07:00
parent f98efe6c32
commit 48401dcbf1
4 changed files with 9 additions and 98 deletions
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4
Makefile
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@ -1,5 +1,5 @@
GPU=1
OPENCV=1
GPU=0
OPENCV=0
DEBUG=0
ARCH= -arch=sm_52

4
cfg/yolo.cfg
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@ -1,6 +1,6 @@
[net]
batch=1
subdivisions=1
batch=64
subdivisions=64
height=448
width=448
channels=3

95
src/detection.c
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@ -120,94 +120,6 @@ void train_detection(char *cfgfile, char *weightfile)
}
}
void predict_detections(network net, data d, float threshold, int offset, int classes, int objectness, int background, int num_boxes, int per_box)
{
matrix pred = network_predict_data(net, d);
int j, k, class;
for(j = 0; j < pred.rows; ++j){
for(k = 0; k < pred.cols; k += per_box){
float scale = 1.;
int index = k/per_box;
int row = index / num_boxes;
int col = index % num_boxes;
if (objectness) scale = 1.-pred.vals[j][k];
for (class = 0; class < classes; ++class){
int ci = k+classes+(background || objectness);
float x = (pred.vals[j][ci + 0] + col)/num_boxes;
float y = (pred.vals[j][ci + 1] + row)/num_boxes;
float w = pred.vals[j][ci + 2]; // distance_from_edge(row, num_boxes);
float h = pred.vals[j][ci + 3]; // distance_from_edge(col, num_boxes);
w = pow(w, 2);
h = pow(h, 2);
float prob = scale*pred.vals[j][k+class+(background || objectness)];
if(prob < threshold) continue;
printf("%d %d %f %f %f %f %f\n", offset + j, class, prob, x, y, w, h);
}
}
}
free_matrix(pred);
}
void validate_detection(char *cfgfile, char *weightfile)
{
network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&net, weightfile);
}
detection_layer layer = get_network_detection_layer(net);
fprintf(stderr, "Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
srand(time(0));
list *plist = get_paths("/home/pjreddie/data/voc/test.txt");
char **paths = (char **)list_to_array(plist);
int classes = layer.classes;
int objectness = layer.objectness;
int background = layer.background;
int num_boxes = sqrt(get_detection_layer_locations(layer));
int per_box = 4+classes+(background || objectness);
int num_output = num_boxes*num_boxes*per_box;
int m = plist->size;
int i = 0;
int splits = 100;
int nthreads = 4;
int t;
data *val = calloc(nthreads, sizeof(data));
data *buf = calloc(nthreads, sizeof(data));
pthread_t *thr = calloc(nthreads, sizeof(data));
time_t start = time(0);
for(t = 0; t < nthreads; ++t){
int num = (i+1+t)*m/splits - (i+t)*m/splits;
char **part = paths+((i+t)*m/splits);
thr[t] = load_data_thread(part, num, 0, 0, num_output, net.w, net.h, &(buf[t]));
}
for(i = nthreads; i <= splits; i += nthreads){
for(t = 0; t < nthreads; ++t){
pthread_join(thr[t], 0);
val[t] = buf[t];
}
for(t = 0; t < nthreads && i < splits; ++t){
int num = (i+1+t)*m/splits - (i+t)*m/splits;
char **part = paths+((i+t)*m/splits);
thr[t] = load_data_thread(part, num, 0, 0, num_output, net.w, net.h, &(buf[t]));
}
fprintf(stderr, "%d\n", i);
for(t = 0; t < nthreads; ++t){
predict_detections(net, val[t], .001, (i-nthreads+t)*m/splits, classes, objectness, background, num_boxes, per_box);
free_data(val[t]);
}
}
fprintf(stderr, "Total Detection Time: %f Seconds\n", (double)(time(0) - start));
}
void convert_detections(float *predictions, int classes, int objectness, int background, int num_boxes, int w, int h, float thresh, float **probs, box *boxes)
{
int i,j;
@ -271,7 +183,7 @@ void print_detections(FILE **fps, char *id, box *boxes, float **probs, int num_b
}
}
void valid_detection(char *cfgfile, char *weightfile)
void validate_detection(char *cfgfile, char *weightfile)
{
network net = parse_network_cfg(cfgfile);
if(weightfile){
@ -282,8 +194,8 @@ void valid_detection(char *cfgfile, char *weightfile)
fprintf(stderr, "Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
srand(time(0));
char *base = "/home/pjreddie/data/voc/devkit/results/VOC2012/Main/comp4_det_test_";
list *plist = get_paths("/home/pjreddie/data/voc/test.txt");
char *base = "results/comp4_det_test_";
list *plist = get_paths("data/voc.2012test.list");
char **paths = (char **)list_to_array(plist);
int classes = layer.classes;
@ -401,5 +313,4 @@ void run_detection(int argc, char **argv)
if(0==strcmp(argv[2], "test")) test_detection(cfg, weights, filename);
else if(0==strcmp(argv[2], "train")) train_detection(cfg, weights);
else if(0==strcmp(argv[2], "valid")) validate_detection(cfg, weights);
else if(0==strcmp(argv[2], "run")) valid_detection(cfg, weights);
}

4
src/imagenet.c
View File

@ -66,8 +66,8 @@ void validate_imagenet(char *filename, char *weightfile)
}
srand(time(0));
char **labels = get_labels("/data/imagenet/inet.val.labels.list");
list *plist = get_paths("/data/imagenet/inet.val.list");
char **labels = get_labels("data/inet.labels.list");
list *plist = get_paths("data/inet.val.list");
char **paths = (char **)list_to_array(plist);
int m = plist->size;