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MERRY CHRISTMAS I BROKE ALL YOUR DETECTION THINGS

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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
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53
examples/coco.c
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@@ -94,14 +94,14 @@ void train_coco(char *cfgfile, char *weightfile)
save_weights(net, buff);
}
void print_cocos(FILE *fp, int image_id, box *boxes, float **probs, int num_boxes, int classes, int w, int h)
static void print_cocos(FILE *fp, int image_id, detection *dets, int num_boxes, int classes, int w, int h)
{
int i, j;
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;
@@ -114,7 +114,7 @@ void print_cocos(FILE *fp, int image_id, box *boxes, float **probs, int num_boxe
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]);
}
}
}
@@ -140,17 +140,13 @@ void validate_coco(char *cfg, char *weights)
layer l = net->layers[net->n-1];
int classes = l.classes;
int side = l.side;
int j;
char buff[1024];
snprintf(buff, 1024, "%s/coco_results.json", base);
FILE *fp = fopen(buff, "w");
fprintf(fp, "[\n");
box *boxes = calloc(side*side*l.n, sizeof(box));
float **probs = calloc(side*side*l.n, sizeof(float *));
for(j = 0; j < side*side*l.n; ++j) probs[j] = calloc(classes, sizeof(float *));
detection *dets = make_network_boxes(net);
int m = plist->size;
int i=0;
@@ -199,9 +195,9 @@ void validate_coco(char *cfg, char *weights)
network_predict(net, X);
int w = val[t].w;
int h = val[t].h;
get_detection_boxes(l, w, h, thresh, probs, boxes, 0);
if (nms) do_nms_sort(boxes, probs, side*side*l.n, classes, iou_thresh);
print_cocos(fp, image_id, boxes, probs, side*side*l.n, classes, w, h);
fill_network_boxes(net, w, h, thresh, 0, 0, 0, dets);
if (nms) do_nms_sort(dets, l.side*l.side*l.n, classes, iou_thresh);
print_cocos(fp, image_id, dets, l.side*l.side*l.n, classes, w, h);
free_image(val[t]);
free_image(val_resized[t]);
}
@@ -235,9 +231,7 @@ void validate_coco_recall(char *cfgfile, char *weightfile)
snprintf(buff, 1024, "%s%s.txt", base, coco_classes[j]);
fps[j] = fopen(buff, "w");
}
box *boxes = calloc(side*side*l.n, sizeof(box));
float **probs = calloc(side*side*l.n, sizeof(float *));
for(j = 0; j < side*side*l.n; ++j) probs[j] = calloc(classes, sizeof(float *));
detection *dets = make_network_boxes(net);
int m = plist->size;
int i=0;
@@ -245,7 +239,6 @@ void validate_coco_recall(char *cfgfile, char *weightfile)
float thresh = .001;
int nms = 0;
float iou_thresh = .5;
float nms_thresh = .5;
int total = 0;
int correct = 0;
@@ -258,8 +251,9 @@ void validate_coco_recall(char *cfgfile, char *weightfile)
image sized = resize_image(orig, net->w, net->h);
char *id = basecfg(path);
network_predict(net, sized.data);
get_detection_boxes(l, 1, 1, thresh, probs, boxes, 1);
if (nms) do_nms(boxes, probs, side*side*l.n, 1, nms_thresh);
fill_network_boxes(net, orig.w, orig.h, thresh, 0, 0, 1, dets);
if (nms) do_nms_obj(dets, side*side*l.n, 1, nms);
char labelpath[4096];
find_replace(path, "images", "labels", labelpath);
@@ -270,7 +264,7 @@ void validate_coco_recall(char *cfgfile, char *weightfile)
int num_labels = 0;
box_label *truth = read_boxes(labelpath, &num_labels);
for(k = 0; k < side*side*l.n; ++k){
if(probs[k][0] > thresh){
if(dets[k].objectness > thresh){
++proposals;
}
}
@@ -279,8 +273,8 @@ void validate_coco_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 < side*side*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;
}
}
@@ -308,10 +302,7 @@ void test_coco(char *cfgfile, char *weightfile, char *filename, float thresh)
clock_t time;
char buff[256];
char *input = buff;
int j;
box *boxes = calloc(l.side*l.side*l.n, sizeof(box));
float **probs = calloc(l.side*l.side*l.n, sizeof(float *));
for(j = 0; j < l.side*l.side*l.n; ++j) probs[j] = calloc(l.classes, sizeof(float *));
detection *dets = make_network_boxes(net);
while(1){
if(filename){
strncpy(input, filename, 256);
@@ -328,9 +319,11 @@ void test_coco(char *cfgfile, char *weightfile, char *filename, float thresh)
time=clock();
network_predict(net, X);
printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
get_detection_boxes(l, 1, 1, thresh, probs, boxes, 0);
if (nms) do_nms_sort(boxes, probs, l.side*l.side*l.n, l.classes, nms);
draw_detections(im, l.side*l.side*l.n, thresh, boxes, probs, 0, coco_classes, alphabet, 80);
fill_network_boxes(net, 1, 1, thresh, 0, 0, 0, dets);
if (nms) do_nms_sort(dets, l.side*l.side*l.n, l.classes, nms);
draw_detections(im, dets, l.side*l.side*l.n, thresh, coco_classes, alphabet, 80);
save_image(im, "prediction");
show_image(im, "predictions");
free_image(im);