From d28f7e6681ffe02a151b9dc89098d7fcef50b214 Mon Sep 17 00:00:00 2001
From: Alexey <AlexeyAB@users.noreply.github.com>
Date: Wed, 28 Mar 2018 20:51:14 +0000
Subject: [PATCH] Update Readme.md
---
src/detector.c | 73 ++++++++++++++++++++++++++----------
1 files changed, 52 insertions(+), 21 deletions(-)
diff --git a/src/detector.c b/src/detector.c
index 42ffbf7..77175b4 100644
--- a/src/detector.c
+++ b/src/detector.c
@@ -25,11 +25,13 @@
#pragma comment(lib, "opencv_highgui" OPENCV_VERSION ".lib")
#endif
-#endif
+IplImage* draw_train_chart(float max_img_loss, int max_batches, int number_of_lines, int img_size);
+void draw_train_loss(IplImage* img, int img_size, float avg_loss, float max_img_loss, int current_batch, int max_batches);
+#endif // OPENCV
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)
+void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, int ngpus, int clear, int dont_show)
{
list *options = read_data_cfg(datacfg);
char *train_images = option_find_str(options, "train", "data/train.list");
@@ -74,6 +76,8 @@
int init_w = net.w;
int init_h = net.h;
+ int iter_save;
+ iter_save = get_current_batch(net);
load_args args = {0};
args.w = net.w;
@@ -87,13 +91,22 @@
args.small_object = l.small_object;
args.d = &buffer;
args.type = DETECTION_DATA;
- args.threads = 4;// 8;
+ args.threads = 64; // 8
args.angle = net.angle;
args.exposure = net.exposure;
args.saturation = net.saturation;
args.hue = net.hue;
+#ifdef OPENCV
+ IplImage* img = NULL;
+ float max_img_loss = 5;
+ int number_of_lines = 100;
+ int img_size = 1000;
+ if (!dont_show)
+ img = draw_train_chart(max_img_loss, net.max_batches, number_of_lines, img_size);
+#endif //OPENCV
+
pthread_t load_thread = load_data(args);
clock_t time;
int count = 0;
@@ -102,7 +115,6 @@
if(l.random && count++%10 == 0){
printf("Resizing\n");
int dim = (rand() % 12 + (init_w/32 - 5)) * 32; // +-160
- //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);
@@ -159,8 +171,16 @@
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);
+
+#ifdef OPENCV
+ if(!dont_show)
+ draw_train_loss(img, img_size, avg_loss, max_img_loss, i, net.max_batches);
+#endif // OPENCV
+
//if (i % 1000 == 0 || (i < 1000 && i % 100 == 0)) {
- if (i % 100 == 0) {
+ //if (i % 100 == 0) {
+ if(i >= (iter_save + 100)) {
+ iter_save = i;
#ifdef GPU
if (ngpus != 1) sync_nets(nets, ngpus, 0);
#endif
@@ -176,6 +196,9 @@
char buff[256];
sprintf(buff, "%s/%s_final.weights", backup_directory, base);
save_weights(net, buff);
+
+ //cvReleaseImage(&img);
+ //cvDestroyAllWindows();
}
@@ -898,7 +921,7 @@
float box_h = points->data.fl[i * 2 + 1];
//int cluster_idx = labels->data.i[i];
int cluster_idx = 0;
- float min_dist = 1000000;
+ float min_dist = FLT_MAX;
for (j = 0; j < num_of_clusters; ++j) {
float anchor_w = centers->data.fl[j * 2];
float anchor_h = centers->data.fl[j * 2 + 1];
@@ -977,7 +1000,7 @@
}
#endif // OPENCV
-void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filename, float thresh, int dont_show)
+void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filename, float thresh, float hier_thresh, int dont_show)
{
list *options = read_data_cfg(datacfg);
char *name_list = option_find_str(options, "names", "data/names.list");
@@ -994,7 +1017,7 @@
char buff[256];
char *input = buff;
int j;
- float nms=.4;
+ float nms=.45; // 0.4F
while(1){
if(filename){
strncpy(input, filename, 256);
@@ -1007,20 +1030,27 @@
strtok(input, "\n");
}
image im = load_image_color(input,0,0);
+ int letter = 0;
image sized = resize_image(im, net.w, net.h);
+ //image sized = letterbox_image(im, net.w, net.h); letter = 1;
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 *));
+ //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, 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);
+ //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);
+ int nboxes = 0;
+ detection *dets = get_network_boxes(&net, im.w, im.h, thresh, hier_thresh, 0, 1, &nboxes, letter);
+ if (nms) do_nms_sort_v3(dets, nboxes, l.classes, nms);
+ draw_detections_v3(im, dets, nboxes, thresh, names, alphabet, l.classes);
+ free_detections(dets, nboxes);
save_image(im, "predictions");
if (!dont_show) {
show_image(im, "predictions");
@@ -1028,8 +1058,8 @@
free_image(im);
free_image(sized);
- free(boxes);
- free_ptrs((void **)probs, l.w*l.h*l.n);
+ //free(boxes);
+ //free_ptrs((void **)probs, l.w*l.h*l.n);
#ifdef OPENCV
if (!dont_show) {
cvWaitKey(0);
@@ -1047,7 +1077,8 @@
int http_stream_port = find_int_arg(argc, argv, "-http_port", -1);
char *out_filename = find_char_arg(argc, argv, "-out_filename", 0);
char *prefix = find_char_arg(argc, argv, "-prefix", 0);
- float thresh = find_float_arg(argc, argv, "-thresh", .24);
+ float thresh = find_float_arg(argc, argv, "-thresh", .25); // 0.24
+ float hier_thresh = find_float_arg(argc, argv, "-hier", .5);
int cam_index = find_int_arg(argc, argv, "-c", 0);
int frame_skip = find_int_arg(argc, argv, "-s", 0);
int num_of_clusters = find_int_arg(argc, argv, "-num_of_clusters", 5);
@@ -1088,12 +1119,12 @@
if(weights)
if (weights[strlen(weights) - 1] == 0x0d) weights[strlen(weights) - 1] = 0;
char *filename = (argc > 6) ? argv[6]: 0;
- if(0==strcmp(argv[2], "test")) test_detector(datacfg, cfg, weights, filename, thresh, dont_show);
- else if(0==strcmp(argv[2], "train")) train_detector(datacfg, cfg, weights, gpus, ngpus, clear);
+ if(0==strcmp(argv[2], "test")) test_detector(datacfg, cfg, weights, filename, thresh, hier_thresh, dont_show);
+ else if(0==strcmp(argv[2], "train")) train_detector(datacfg, cfg, weights, gpus, ngpus, clear, dont_show);
else if(0==strcmp(argv[2], "valid")) validate_detector(datacfg, cfg, weights);
else if(0==strcmp(argv[2], "recall")) validate_detector_recall(datacfg, cfg, weights);
else if(0==strcmp(argv[2], "map")) validate_detector_map(datacfg, cfg, weights, thresh);
- else if(0==strcmp(argv[2], "calc_anchors")) calc_anchors(datacfg, num_of_clusters, final_width, final_heigh, show);
+ else if(0==strcmp(argv[2], "calc_anchors")) calc_anchors(datacfg, num_of_clusters, final_width, final_heigh, show);
else if(0==strcmp(argv[2], "demo")) {
list *options = read_data_cfg(datacfg);
int classes = option_find_int(options, "classes", 20);
@@ -1101,7 +1132,7 @@
char **names = get_labels(name_list);
if(filename)
if (filename[strlen(filename) - 1] == 0x0d) filename[strlen(filename) - 1] = 0;
- demo(cfg, weights, thresh, cam_index, filename, names, classes, frame_skip, prefix, out_filename,
+ demo(cfg, weights, thresh, hier_thresh, cam_index, filename, names, classes, frame_skip, prefix, out_filename,
http_stream_port, dont_show);
}
}
--
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