From d50ebc7fdf6543faab8c8b02d30730a9991f02b6 Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Tue, 06 Dec 2016 11:41:18 +0000
Subject: [PATCH] Fixed command line examples
---
src/detector.c | 137 ++++++++++++++++++++++++++++++++++-----------
1 files changed, 102 insertions(+), 35 deletions(-)
diff --git a/src/detector.c b/src/detector.c
index f18ae51..a389407 100644
--- a/src/detector.c
+++ b/src/detector.c
@@ -66,7 +66,7 @@
args.num_boxes = l.max_boxes;
args.d = &buffer;
args.type = DETECTION_DATA;
- args.threads = 4;
+ args.threads = 8;
args.angle = net.angle;
args.exposure = net.exposure;
@@ -75,8 +75,28 @@
pthread_t load_thread = load_data(args);
clock_t time;
+ int count = 0;
//while(i*imgs < N*120){
while(get_current_batch(net) < net.max_batches){
+ if(l.random && count++%10 == 0){
+ printf("Resizing\n");
+ int dim = (rand() % 10 + 10) * 32;
+ if (get_current_batch(net)+100 > net.max_batches) dim = 544;
+ //int dim = (rand() % 4 + 16) * 32;
+ printf("%d\n", dim);
+ args.w = dim;
+ args.h = dim;
+
+ pthread_join(load_thread, 0);
+ train = buffer;
+ free_data(train);
+ load_thread = load_data(args);
+
+ for(i = 0; i < ngpus; ++i){
+ resize_network(nets + i, dim, dim);
+ }
+ net = nets[0];
+ }
time=clock();
pthread_join(load_thread, 0);
train = buffer;
@@ -118,12 +138,18 @@
i = get_current_batch(net);
printf("%d: %f, %f avg, %f rate, %lf seconds, %d images\n", get_current_batch(net), loss, avg_loss, get_current_rate(net), sec(clock()-time), i*imgs);
if(i%1000==0 || (i < 1000 && i%100 == 0)){
+#ifdef GPU
+ if(ngpus != 1) sync_nets(nets, ngpus, 0);
+#endif
char buff[256];
sprintf(buff, "%s/%s_%d.weights", backup_directory, base, i);
save_weights(net, buff);
}
free_data(train);
}
+#ifdef GPU
+ if(ngpus != 1) sync_nets(nets, ngpus, 0);
+#endif
char buff[256];
sprintf(buff, "%s/%s_final.weights", backup_directory, base);
save_weights(net, buff);
@@ -183,23 +209,39 @@
}
}
+void print_imagenet_detections(FILE *fp, int id, box *boxes, float **probs, 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.;
+
+ if (xmin < 0) xmin = 0;
+ if (ymin < 0) ymin = 0;
+ if (xmax > w) xmax = w;
+ if (ymax > h) ymax = h;
+
+ 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],
+ xmin, ymin, xmax, ymax);
+ }
+ }
+}
+
void validate_detector(char *datacfg, char *cfgfile, char *weightfile)
{
+ int j;
list *options = read_data_cfg(datacfg);
char *valid_images = option_find_str(options, "valid", "data/train.list");
char *name_list = option_find_str(options, "names", "data/names.list");
char *prefix = option_find_str(options, "results", "results");
char **names = get_labels(name_list);
-
-
- char buff[1024];
- int coco = option_find_int_quiet(options, "coco", 0);
- FILE *coco_fp = 0;
- if(coco){
- snprintf(buff, 1024, "%s/coco_results.json", prefix);
- coco_fp = fopen(buff, "w");
- fprintf(coco_fp, "[\n");
- }
+ char *mapf = option_find_str(options, "map", 0);
+ int *map = 0;
+ if (mapf) map = read_map(mapf);
network net = parse_network_cfg(cfgfile);
if(weightfile){
@@ -216,12 +258,31 @@
layer l = net.layers[net.n-1];
int classes = l.classes;
- int j;
- FILE **fps = calloc(classes, sizeof(FILE *));
- for(j = 0; j < classes; ++j){
- snprintf(buff, 1024, "%s/%s%s.txt", prefix, base, names[j]);
- fps[j] = fopen(buff, "w");
+ char buff[1024];
+ char *type = option_find_str(options, "eval", "voc");
+ FILE *fp = 0;
+ FILE **fps = 0;
+ int coco = 0;
+ int imagenet = 0;
+ if(0==strcmp(type, "coco")){
+ snprintf(buff, 1024, "%s/coco_results.json", prefix);
+ fp = fopen(buff, "w");
+ fprintf(fp, "[\n");
+ coco = 1;
+ } else if(0==strcmp(type, "imagenet")){
+ snprintf(buff, 1024, "%s/imagenet-detection.txt", prefix);
+ fp = fopen(buff, "w");
+ imagenet = 1;
+ classes = 200;
+ } else {
+ fps = calloc(classes, sizeof(FILE *));
+ for(j = 0; j < classes; ++j){
+ snprintf(buff, 1024, "%s/%s%s.txt", prefix, base, names[j]);
+ fps[j] = fopen(buff, "w");
+ }
}
+
+
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, sizeof(float *));
@@ -230,10 +291,10 @@
int i=0;
int t;
- float thresh = .001;
- float nms = .5;
+ float thresh = .005;
+ float nms = .45;
- int nthreads = 2;
+ int nthreads = 4;
image *val = calloc(nthreads, sizeof(image));
image *val_resized = calloc(nthreads, sizeof(image));
image *buf = calloc(nthreads, sizeof(image));
@@ -272,11 +333,13 @@
network_predict(net, X);
int w = val[t].w;
int h = val[t].h;
- get_region_boxes(l, w, h, thresh, probs, boxes, 0);
+ get_region_boxes(l, w, h, thresh, probs, boxes, 0, map);
if (nms) do_nms_sort(boxes, probs, l.w*l.h*l.n, classes, nms);
- if(coco_fp){
- print_cocos(coco_fp, path, boxes, probs, l.w*l.h*l.n, classes, w, h);
- }else{
+ if (coco){
+ print_cocos(fp, path, boxes, probs, 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);
+ } else {
print_detector_detections(fps, id, boxes, probs, l.w*l.h*l.n, classes, w, h);
}
free(id);
@@ -285,12 +348,12 @@
}
}
for(j = 0; j < classes; ++j){
- fclose(fps[j]);
+ if(fps) fclose(fps[j]);
}
- if(coco_fp){
- fseek(coco_fp, -2, SEEK_CUR);
- fprintf(coco_fp, "\n]\n");
- fclose(coco_fp);
+ if(coco){
+ fseek(fp, -2, SEEK_CUR);
+ fprintf(fp, "\n]\n");
+ fclose(fp);
}
fprintf(stderr, "Total Detection Time: %f Seconds\n", (double)(time(0) - start));
}
@@ -334,7 +397,7 @@
image sized = resize_image(orig, net.w, net.h);
char *id = basecfg(path);
network_predict(net, sized.data);
- get_region_boxes(l, 1, 1, thresh, probs, boxes, 1);
+ get_region_boxes(l, 1, 1, thresh, probs, boxes, 1, 0);
if (nms) do_nms(boxes, probs, l.w*l.h*l.n, 1, nms);
char labelpath[4096];
@@ -384,7 +447,6 @@
if(weightfile){
load_weights(&net, weightfile);
}
- layer l = net.layers[net.n-1];
set_batch_network(&net, 1);
srand(2222222);
clock_t time;
@@ -392,9 +454,6 @@
char *input = buff;
int j;
float nms=.4;
- 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, sizeof(float *));
while(1){
if(filename){
strncpy(input, filename, 256);
@@ -407,11 +466,17 @@
}
image im = load_image_color(input,0,0);
image sized = resize_image(im, net.w, net.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, sizeof(float *));
+
float *X = sized.data;
time=clock();
network_predict(net, X);
printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
- get_region_boxes(l, 1, 1, thresh, probs, boxes, 0);
+ get_region_boxes(l, 1, 1, thresh, probs, boxes, 0, 0);
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, names, alphabet, l.classes);
save_image(im, "predictions");
@@ -419,6 +484,8 @@
free_image(im);
free_image(sized);
+ free(boxes);
+ free_ptrs((void **)probs, l.w*l.h*l.n);
#ifdef OPENCV
cvWaitKey(0);
cvDestroyAllWindows();
@@ -430,7 +497,7 @@
void run_detector(int argc, char **argv)
{
char *prefix = find_char_arg(argc, argv, "-prefix", 0);
- float thresh = find_float_arg(argc, argv, "-thresh", .2);
+ float thresh = find_float_arg(argc, argv, "-thresh", .24);
int cam_index = find_int_arg(argc, argv, "-c", 0);
int frame_skip = find_int_arg(argc, argv, "-s", 0);
if(argc < 4){
--
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