From b8e6e80c6d411d05a9e09f1e3676eb9a7f3ea0e8 Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Fri, 03 Aug 2018 11:35:03 +0000
Subject: [PATCH] Added spatial Yolo v3 yolov3-spp.cfg
---
src/coco.c | 48 ++++++++++++++++++++----------------------------
1 files changed, 20 insertions(+), 28 deletions(-)
diff --git a/src/coco.c b/src/coco.c
index 1371870..1913a47 100644
--- a/src/coco.c
+++ b/src/coco.c
@@ -12,14 +12,10 @@
#include "opencv2/highgui/highgui_c.h"
#endif
-void convert_detections(float *predictions, int classes, int num, int square, int side, int w, int h, float thresh, float **probs, box *boxes, int only_objectness);
-
char *coco_classes[] = {"person","bicycle","car","motorcycle","airplane","bus","train","truck","boat","traffic light","fire hydrant","stop sign","parking meter","bench","bird","cat","dog","horse","sheep","cow","elephant","bear","zebra","giraffe","backpack","umbrella","handbag","tie","suitcase","frisbee","skis","snowboard","sports ball","kite","baseball bat","baseball glove","skateboard","surfboard","tennis racket","bottle","wine glass","cup","fork","knife","spoon","bowl","banana","apple","sandwich","orange","broccoli","carrot","hot dog","pizza","donut","cake","chair","couch","potted plant","bed","dining table","toilet","tv","laptop","mouse","remote","keyboard","cell phone","microwave","oven","toaster","sink","refrigerator","book","clock","vase","scissors","teddy bear","hair drier","toothbrush"};
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};
-image coco_labels[80];
-
void train_coco(char *cfgfile, char *weightfile)
{
//char *train_images = "/home/pjreddie/data/voc/test/train.txt";
@@ -28,7 +24,6 @@
//char *train_images = "data/bags.train.list";
char *backup_directory = "/home/pjreddie/backup/";
srand(time(0));
- data_seed = time(0);
char *base = basecfg(cfgfile);
printf("%s\n", base);
float avg_loss = -1;
@@ -161,7 +156,6 @@
layer l = net.layers[net.n-1];
int classes = l.classes;
- int square = l.sqrt;
int side = l.side;
int j;
@@ -218,11 +212,11 @@
char *path = paths[i+t-nthreads];
int image_id = get_coco_image_id(path);
float *X = val_resized[t].data;
- float *predictions = network_predict(net, X);
+ network_predict(net, X);
int w = val[t].w;
int h = val[t].h;
- convert_detections(predictions, classes, l.n, square, side, w, h, thresh, probs, boxes, 0);
- if (nms) do_nms_sort(boxes, probs, side*side*l.n, classes, iou_thresh);
+ get_detection_boxes(l, w, h, thresh, probs, boxes, 0);
+ if (nms) do_nms_sort_v2(boxes, probs, side*side*l.n, classes, iou_thresh);
print_cocos(fp, image_id, boxes, probs, side*side*l.n, classes, w, h);
free_image(val[t]);
free_image(val_resized[t]);
@@ -251,7 +245,6 @@
layer l = net.layers[net.n-1];
int classes = l.classes;
- int square = l.sqrt;
int side = l.side;
int j, k;
@@ -283,14 +276,12 @@
image orig = load_image_color(path, 0, 0);
image sized = resize_image(orig, net.w, net.h);
char *id = basecfg(path);
- float *predictions = network_predict(net, sized.data);
- convert_detections(predictions, classes, l.n, square, side, 1, 1, thresh, probs, boxes, 1);
+ 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);
- char *labelpath = find_replace(path, "images", "labels");
- labelpath = find_replace(labelpath, "JPEGImages", "labels");
- labelpath = find_replace(labelpath, ".jpg", ".txt");
- labelpath = find_replace(labelpath, ".JPEG", ".txt");
+ char labelpath[4096];
+ replace_image_to_label(path, labelpath);
int num_labels = 0;
box_label *truth = read_boxes(labelpath, &num_labels);
@@ -324,7 +315,7 @@
void test_coco(char *cfgfile, char *weightfile, char *filename, float thresh)
{
-
+ image **alphabet = load_alphabet();
network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&net, weightfile);
@@ -354,11 +345,11 @@
image sized = resize_image(im, net.w, net.h);
float *X = sized.data;
time=clock();
- float *predictions = network_predict(net, X);
+ network_predict(net, X);
printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
- convert_detections(predictions, l.classes, l.n, l.sqrt, l.side, 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, coco_classes, coco_labels, 80);
+ get_detection_boxes(l, 1, 1, thresh, probs, boxes, 0);
+ if (nms) do_nms_sort_v2(boxes, probs, l.side*l.side*l.n, l.classes, nms);
+ draw_detections(im, l.side*l.side*l.n, thresh, boxes, probs, coco_classes, alphabet, 80);
save_image(im, "prediction");
show_image(im, "predictions");
free_image(im);
@@ -373,15 +364,15 @@
void run_coco(int argc, char **argv)
{
- int i;
- for(i = 0; i < 80; ++i){
- char buff[256];
- sprintf(buff, "data/labels/%s.png", coco_classes[i]);
- coco_labels[i] = load_image_color(buff, 0, 0);
- }
+ int dont_show = find_arg(argc, argv, "-dont_show");
+ 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", .2);
+ 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 ext_output = find_arg(argc, argv, "-ext_output");
if(argc < 4){
fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]);
@@ -395,5 +386,6 @@
else if(0==strcmp(argv[2], "train")) train_coco(cfg, weights);
else if(0==strcmp(argv[2], "valid")) validate_coco(cfg, weights);
else if(0==strcmp(argv[2], "recall")) validate_coco_recall(cfg, weights);
- else if(0==strcmp(argv[2], "demo")) demo(cfg, weights, thresh, cam_index, filename, coco_classes, coco_labels, 80, frame_skip);
+ else if(0==strcmp(argv[2], "demo")) demo(cfg, weights, thresh, hier_thresh, cam_index, filename, coco_classes, 80, frame_skip,
+ prefix, out_filename, http_stream_port, dont_show, ext_output);
}
--
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