mirror/darknet
1
0
Fork 0
mirror of https://github.com/pjreddie/darknet.git synced 2023-08-10 21:13:14 +03:00
Code Issues Projects Releases Wiki Activity

MERRY CHRISTMAS I BROKE ALL YOUR DETECTION THINGS

Browse Source
This commit is contained in:
Joseph Redmon
2017-12-26 10:52:21 -08:00
parent 80d9bec20f
commit 6e79145309
36 changed files with 1166 additions and 689 deletions
Download Patch File Download Diff File Expand all files Collapse all files

159
examples/detector.c
View File

@ -2,6 +2,7 @@
static int coco_ids[] = {1,2,3,4,5,6,7,8,9,10,11,13,14,15,16,17,18,19,20,21,22,23,24,25,27,28,31,32,33,34,35,36,37,38,39,40,41,42,43,44,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,67,70,72,73,74,75,76,77,78,79,80,81,82,84,85,86,87,88,89,90};
void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, int ngpus, int clear)
{
list *options = read_data_cfg(datacfg);
@ -73,6 +74,7 @@ void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, i
free_data(train);
load_thread = load_data(args);
#pragma omp parallel for
for(i = 0; i < ngpus; ++i){
resize_network(nets[i], dim, dim);
}
@ -84,28 +86,28 @@ void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, i
load_thread = load_data(args);
/*
int k;
for(k = 0; k < l.max_boxes; ++k){
box b = float_to_box(train.y.vals[10] + 1 + k*5);
if(!b.x) break;
printf("loaded: %f %f %f %f\n", b.x, b.y, b.w, b.h);
}
*/
int k;
for(k = 0; k < l.max_boxes; ++k){
box b = float_to_box(train.y.vals[10] + 1 + k*5);
if(!b.x) break;
printf("loaded: %f %f %f %f\n", b.x, b.y, b.w, b.h);
}
*/
/*
int zz;
for(zz = 0; zz < train.X.cols; ++zz){
image im = float_to_image(net->w, net->h, 3, train.X.vals[zz]);
int k;
for(k = 0; k < l.max_boxes; ++k){
box b = float_to_box(train.y.vals[zz] + k*5, 1);
printf("%f %f %f %f\n", b.x, b.y, b.w, b.h);
draw_bbox(im, b, 1, 1,0,0);
}
show_image(im, "truth11");
cvWaitKey(0);
save_image(im, "truth11");
}
*/
int zz;
for(zz = 0; zz < train.X.cols; ++zz){
image im = float_to_image(net->w, net->h, 3, train.X.vals[zz]);
int k;
for(k = 0; k < l.max_boxes; ++k){
box b = float_to_box(train.y.vals[zz] + k*5, 1);
printf("%f %f %f %f\n", b.x, b.y, b.w, b.h);
draw_bbox(im, b, 1, 1,0,0);
}
show_image(im, "truth11");
cvWaitKey(0);
save_image(im, "truth11");
}
*/
printf("Loaded: %lf seconds\n", what_time_is_it_now()-time);
@ -158,15 +160,15 @@ static int get_coco_image_id(char *filename)
return atoi(p+1);
}
static void print_cocos(FILE *fp, char *image_path, box *boxes, float **probs, int num_boxes, int classes, int w, int h)
static void print_cocos(FILE *fp, char *image_path, detection *dets, int num_boxes, int classes, int w, int h)
{
int i, j;
int image_id = get_coco_image_id(image_path);
for(i = 0; i < num_boxes; ++i){
float xmin = boxes[i].x - boxes[i].w/2.;
float xmax = boxes[i].x + boxes[i].w/2.;
float ymin = boxes[i].y - boxes[i].h/2.;
float ymax = boxes[i].y + boxes[i].h/2.;
float xmin = dets[i].bbox.x - dets[i].bbox.w/2.;
float xmax = dets[i].bbox.x + dets[i].bbox.w/2.;
float ymin = dets[i].bbox.y - dets[i].bbox.h/2.;
float ymax = dets[i].bbox.y + dets[i].bbox.h/2.;
if (xmin < 0) xmin = 0;
if (ymin < 0) ymin = 0;
@ -179,19 +181,19 @@ static void print_cocos(FILE *fp, char *image_path, box *boxes, float **probs, i
float bh = ymax - ymin;
for(j = 0; j < classes; ++j){
if (probs[i][j]) fprintf(fp, "{\"image_id\":%d, \"category_id\":%d, \"bbox\":[%f, %f, %f, %f], \"score\":%f},\n", image_id, coco_ids[j], bx, by, bw, bh, probs[i][j]);
if (dets[i].prob[j]) fprintf(fp, "{\"image_id\":%d, \"category_id\":%d, \"bbox\":[%f, %f, %f, %f], \"score\":%f},\n", image_id, coco_ids[j], bx, by, bw, bh, dets[i].prob[j]);
}
}
}
void print_detector_detections(FILE **fps, char *id, box *boxes, float **probs, int total, int classes, int w, int h)
void print_detector_detections(FILE **fps, char *id, detection *dets, int total, int classes, int w, int h)
{
int i, j;
for(i = 0; i < total; ++i){
float xmin = boxes[i].x - boxes[i].w/2. + 1;
float xmax = boxes[i].x + boxes[i].w/2. + 1;
float ymin = boxes[i].y - boxes[i].h/2. + 1;
float ymax = boxes[i].y + boxes[i].h/2. + 1;
float xmin = dets[i].bbox.x - dets[i].bbox.w/2. + 1;
float xmax = dets[i].bbox.x + dets[i].bbox.w/2. + 1;
float ymin = dets[i].bbox.y - dets[i].bbox.h/2. + 1;
float ymax = dets[i].bbox.y + dets[i].bbox.h/2. + 1;
if (xmin < 1) xmin = 1;
if (ymin < 1) ymin = 1;
@ -199,20 +201,20 @@ void print_detector_detections(FILE **fps, char *id, box *boxes, float **probs,
if (ymax > h) ymax = h;
for(j = 0; j < classes; ++j){
if (probs[i][j]) fprintf(fps[j], "%s %f %f %f %f %f\n", id, probs[i][j],
if (dets[i].prob[j]) fprintf(fps[j], "%s %f %f %f %f %f\n", id, dets[i].prob[j],
xmin, ymin, xmax, ymax);
}
}
}
void print_imagenet_detections(FILE *fp, int id, box *boxes, float **probs, int total, int classes, int w, int h)
void print_imagenet_detections(FILE *fp, int id, detection *dets, int total, int classes, int w, int h)
{
int i, j;
for(i = 0; i < total; ++i){
float xmin = boxes[i].x - boxes[i].w/2.;
float xmax = boxes[i].x + boxes[i].w/2.;
float ymin = boxes[i].y - boxes[i].h/2.;
float ymax = boxes[i].y + boxes[i].h/2.;
float xmin = dets[i].bbox.x - dets[i].bbox.w/2.;
float xmax = dets[i].bbox.x + dets[i].bbox.w/2.;
float ymin = dets[i].bbox.y - dets[i].bbox.h/2.;
float ymax = dets[i].bbox.y + dets[i].bbox.h/2.;
if (xmin < 0) xmin = 0;
if (ymin < 0) ymin = 0;
@ -221,7 +223,7 @@ void print_imagenet_detections(FILE *fp, int id, box *boxes, float **probs, int
for(j = 0; j < classes; ++j){
int class = j;
if (probs[i][class]) fprintf(fp, "%d %d %f %f %f %f %f\n", id, j+1, probs[i][class],
if (dets[i].prob[class]) fprintf(fp, "%d %d %f %f %f %f %f\n", id, j+1, dets[i].prob[class],
xmin, ymin, xmax, ymax);
}
}
@ -277,10 +279,7 @@ void validate_detector_flip(char *datacfg, char *cfgfile, char *weightfile, char
}
}
box *boxes = calloc(l.w*l.h*l.n, sizeof(box));
float **probs = calloc(l.w*l.h*l.n, sizeof(float *));
for(j = 0; j < l.w*l.h*l.n; ++j) probs[j] = calloc(classes+1, sizeof(float *));
detection *dets = make_network_boxes(net);
int m = plist->size;
int i=0;
@ -334,14 +333,14 @@ void validate_detector_flip(char *datacfg, char *cfgfile, char *weightfile, char
network_predict(net, input.data);
int w = val[t].w;
int h = val[t].h;
get_region_boxes(l, w, h, net->w, net->h, thresh, probs, boxes, 0, 0, map, .5, 0);
if (nms) do_nms_sort(boxes, probs, l.w*l.h*l.n, classes, nms);
fill_network_boxes(net, w, h, thresh, .5, map, 0, dets);
if (nms) do_nms_sort(dets, l.w*l.h*l.n, classes, nms);
if (coco){
print_cocos(fp, path, boxes, probs, l.w*l.h*l.n, classes, w, h);
print_cocos(fp, path, dets, l.w*l.h*l.n, classes, w, h);
} else if (imagenet){
print_imagenet_detections(fp, i+t-nthreads+1, boxes, probs, l.w*l.h*l.n, classes, w, h);
print_imagenet_detections(fp, i+t-nthreads+1, dets, l.w*l.h*l.n, classes, w, h);
} else {
print_detector_detections(fps, id, boxes, probs, l.w*l.h*l.n, classes, w, h);
print_detector_detections(fps, id, dets, l.w*l.h*l.n, classes, w, h);
}
free(id);
free_image(val[t]);
@ -410,10 +409,8 @@ void validate_detector(char *datacfg, char *cfgfile, char *weightfile, char *out
}
}
box *boxes = calloc(l.w*l.h*l.n, sizeof(box));
float **probs = calloc(l.w*l.h*l.n, sizeof(float *));
for(j = 0; j < l.w*l.h*l.n; ++j) probs[j] = calloc(classes+1, sizeof(float *));
detection *dets = make_network_boxes(net);
int nboxes = num_boxes(net);
int m = plist->size;
int i=0;
@ -462,14 +459,14 @@ void validate_detector(char *datacfg, char *cfgfile, char *weightfile, char *out
network_predict(net, X);
int w = val[t].w;
int h = val[t].h;
get_region_boxes(l, w, h, net->w, net->h, thresh, probs, boxes, 0, 0, map, .5, 0);
if (nms) do_nms_sort(boxes, probs, l.w*l.h*l.n, classes, nms);
fill_network_boxes(net, w, h, thresh, .5, map, 0, dets);
if (nms) do_nms_sort(dets, nboxes, classes, nms);
if (coco){
print_cocos(fp, path, boxes, probs, l.w*l.h*l.n, classes, w, h);
print_cocos(fp, path, dets, nboxes, classes, w, h);
} else if (imagenet){
print_imagenet_detections(fp, i+t-nthreads+1, boxes, probs, l.w*l.h*l.n, classes, w, h);
print_imagenet_detections(fp, i+t-nthreads+1, dets, nboxes, classes, w, h);
} else {
print_detector_detections(fps, id, boxes, probs, l.w*l.h*l.n, classes, w, h);
print_detector_detections(fps, id, dets, nboxes, classes, w, h);
}
free(id);
free_image(val[t]);
@ -498,12 +495,9 @@ void validate_detector_recall(char *cfgfile, char *weightfile)
char **paths = (char **)list_to_array(plist);
layer l = net->layers[net->n-1];
int classes = l.classes;
int j, k;
box *boxes = calloc(l.w*l.h*l.n, sizeof(box));
float **probs = calloc(l.w*l.h*l.n, sizeof(float *));
for(j = 0; j < l.w*l.h*l.n; ++j) probs[j] = calloc(classes+1, sizeof(float *));
detection *dets = make_network_boxes(net);
int m = plist->size;
int i=0;
@ -516,6 +510,7 @@ void validate_detector_recall(char *cfgfile, char *weightfile)
int correct = 0;
int proposals = 0;
float avg_iou = 0;
int nboxes = num_boxes(net);
for(i = 0; i < m; ++i){
char *path = paths[i];
@ -523,8 +518,8 @@ void validate_detector_recall(char *cfgfile, char *weightfile)
image sized = resize_image(orig, net->w, net->h);
char *id = basecfg(path);
network_predict(net, sized.data);
get_region_boxes(l, sized.w, sized.h, net->w, net->h, thresh, probs, boxes, 0, 1, 0, .5, 1);
if (nms) do_nms(boxes, probs, l.w*l.h*l.n, 1, nms);
fill_network_boxes(net, sized.w, sized.h, thresh, .5, 0, 1, dets);
if (nms) do_nms_obj(dets, nboxes, 1, nms);
char labelpath[4096];
find_replace(path, "images", "labels", labelpath);
@ -534,8 +529,8 @@ void validate_detector_recall(char *cfgfile, char *weightfile)
int num_labels = 0;
box_label *truth = read_boxes(labelpath, &num_labels);
for(k = 0; k < l.w*l.h*l.n; ++k){
if(probs[k][0] > thresh){
for(k = 0; k < nboxes; ++k){
if(dets[k].objectness > thresh){
++proposals;
}
}
@ -544,8 +539,8 @@ void validate_detector_recall(char *cfgfile, char *weightfile)
box t = {truth[j].x, truth[j].y, truth[j].w, truth[j].h};
float best_iou = 0;
for(k = 0; k < l.w*l.h*l.n; ++k){
float iou = box_iou(boxes[k], t);
if(probs[k][0] > thresh && iou > best_iou){
float iou = box_iou(dets[k].bbox, t);
if(dets[k].objectness > thresh && iou > best_iou){
best_iou = iou;
}
}
@ -562,6 +557,7 @@ void validate_detector_recall(char *cfgfile, char *weightfile)
}
}
void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filename, float thresh, float hier_thresh, char *outfile, int fullscreen)
{
list *options = read_data_cfg(datacfg);
@ -575,7 +571,6 @@ void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filenam
double time;
char buff[256];
char *input = buff;
int j;
float nms=.3;
while(1){
if(filename){
@ -595,23 +590,18 @@ void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filenam
//resize_network(net, sized.w, sized.h);
layer l = net->layers[net->n-1];
box *boxes = calloc(l.w*l.h*l.n, sizeof(box));
float **probs = calloc(l.w*l.h*l.n, sizeof(float *));
for(j = 0; j < l.w*l.h*l.n; ++j) probs[j] = calloc(l.classes + 1, sizeof(float *));
float **masks = 0;
if (l.coords > 4){
masks = calloc(l.w*l.h*l.n, sizeof(float*));
for(j = 0; j < l.w*l.h*l.n; ++j) masks[j] = calloc(l.coords-4, sizeof(float *));
}
int nboxes = num_boxes(net);
printf("%d\n", nboxes);
float *X = sized.data;
time=what_time_is_it_now();
network_predict(net, X);
printf("%s: Predicted in %f seconds.\n", input, what_time_is_it_now()-time);
get_region_boxes(l, im.w, im.h, net->w, net->h, thresh, probs, boxes, masks, 0, 0, hier_thresh, 1);
detection *dets = get_network_boxes(net, im.w, im.h, thresh, hier_thresh, 0, 1);
//if (nms) do_nms_obj(boxes, probs, l.w*l.h*l.n, l.classes, nms);
if (nms) do_nms_sort(boxes, probs, l.w*l.h*l.n, l.classes, nms);
draw_detections(im, l.w*l.h*l.n, thresh, boxes, probs, masks, names, alphabet, l.classes);
if (nms) do_nms_sort(dets, nboxes, l.classes, nms);
draw_detections(im, dets, nboxes, thresh, names, alphabet, l.classes);
free_detections(dets, num_boxes(net));
if(outfile){
save_image(im, outfile);
}
@ -630,12 +620,19 @@ void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filenam
free_image(im);
free_image(sized);
free(boxes);
free_ptrs((void **)probs, l.w*l.h*l.n);
if (filename) break;
}
}
void network_detect(network *net, image im, float thresh, float hier_thresh, float nms, detection *dets)
{
network_predict_image(net, im);
layer l = net->layers[net->n-1];
int nboxes = num_boxes(net);
fill_network_boxes(net, im.w, im.h, thresh, hier_thresh, 0, 0, dets);
if (nms) do_nms_sort(dets, nboxes, l.classes, nms);
}
void run_detector(int argc, char **argv)
{
char *prefix = find_char_arg(argc, argv, "-prefix", 0);