From ccde487525fc89a1d4bc3e1cf11a18971e8451c9 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@users.noreply.github.com>
Date: Sat, 11 Jul 2015 00:33:24 +0000
Subject: [PATCH] Create README.md
---
src/detection.c | 100 ++-----------------------------------------------
1 files changed, 5 insertions(+), 95 deletions(-)
diff --git a/src/detection.c b/src/detection.c
index 2553115..94d3700 100644
--- a/src/detection.c
+++ b/src/detection.c
@@ -20,6 +20,7 @@
j = (r*side + c) * elems;
int class = max_index(box+j, classes);
if(box[j+class] > 0.2){
+ int width = box[j+class]*5 + 1;
printf("%f %s\n", box[j+class], class_names[class]);
float red = get_color(0,class,classes);
float green = get_color(1,class,classes);
@@ -39,9 +40,7 @@
int right = (x+w/2)*im.w;
int top = (y-h/2)*im.h;
int bot = (y+h/2)*im.h;
- draw_box(im, left, top, right, bot, red, green, blue);
- draw_box(im, left+1, top+1, right+1, bot+1, red, green, blue);
- draw_box(im, left-1, top-1, right-1, bot-1, red, green, blue);
+ draw_box_width(im, left, top, right, bot, width, red, green, blue);
}
}
}
@@ -120,94 +119,6 @@
}
}
-void predict_detections(network net, data d, float threshold, int offset, int classes, int objectness, int background, int num_boxes, int per_box)
-{
- matrix pred = network_predict_data(net, d);
- int j, k, class;
- for(j = 0; j < pred.rows; ++j){
- for(k = 0; k < pred.cols; k += per_box){
- float scale = 1.;
- int index = k/per_box;
- int row = index / num_boxes;
- int col = index % num_boxes;
- if (objectness) scale = 1.-pred.vals[j][k];
- for (class = 0; class < classes; ++class){
- int ci = k+classes+(background || objectness);
- float x = (pred.vals[j][ci + 0] + col)/num_boxes;
- float y = (pred.vals[j][ci + 1] + row)/num_boxes;
- float w = pred.vals[j][ci + 2]; // distance_from_edge(row, num_boxes);
- float h = pred.vals[j][ci + 3]; // distance_from_edge(col, num_boxes);
- w = pow(w, 2);
- h = pow(h, 2);
- float prob = scale*pred.vals[j][k+class+(background || objectness)];
- if(prob < threshold) continue;
- printf("%d %d %f %f %f %f %f\n", offset + j, class, prob, x, y, w, h);
- }
- }
- }
- free_matrix(pred);
-}
-
-void validate_detection(char *cfgfile, char *weightfile)
-{
- network net = parse_network_cfg(cfgfile);
- if(weightfile){
- load_weights(&net, weightfile);
- }
- detection_layer layer = get_network_detection_layer(net);
- fprintf(stderr, "Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
- srand(time(0));
-
- list *plist = get_paths("/home/pjreddie/data/voc/test.txt");
- char **paths = (char **)list_to_array(plist);
-
- int classes = layer.classes;
- int objectness = layer.objectness;
- int background = layer.background;
- int num_boxes = sqrt(get_detection_layer_locations(layer));
-
- int per_box = 4+classes+(background || objectness);
- int num_output = num_boxes*num_boxes*per_box;
-
- int m = plist->size;
- int i = 0;
- int splits = 100;
-
- int nthreads = 4;
- int t;
- data *val = calloc(nthreads, sizeof(data));
- data *buf = calloc(nthreads, sizeof(data));
- pthread_t *thr = calloc(nthreads, sizeof(data));
-
- time_t start = time(0);
-
- for(t = 0; t < nthreads; ++t){
- int num = (i+1+t)*m/splits - (i+t)*m/splits;
- char **part = paths+((i+t)*m/splits);
- thr[t] = load_data_thread(part, num, 0, 0, num_output, net.w, net.h, &(buf[t]));
- }
-
- for(i = nthreads; i <= splits; i += nthreads){
- for(t = 0; t < nthreads; ++t){
- pthread_join(thr[t], 0);
- val[t] = buf[t];
- }
- for(t = 0; t < nthreads && i < splits; ++t){
- int num = (i+1+t)*m/splits - (i+t)*m/splits;
- char **part = paths+((i+t)*m/splits);
- thr[t] = load_data_thread(part, num, 0, 0, num_output, net.w, net.h, &(buf[t]));
- }
-
- fprintf(stderr, "%d\n", i);
- for(t = 0; t < nthreads; ++t){
- predict_detections(net, val[t], .001, (i-nthreads+t)*m/splits, classes, objectness, background, num_boxes, per_box);
- free_data(val[t]);
- }
- }
- fprintf(stderr, "Total Detection Time: %f Seconds\n", (double)(time(0) - start));
-}
-
-
void convert_detections(float *predictions, int classes, int objectness, int background, int num_boxes, int w, int h, float thresh, float **probs, box *boxes)
{
int i,j;
@@ -271,7 +182,7 @@
}
}
-void valid_detection(char *cfgfile, char *weightfile)
+void validate_detection(char *cfgfile, char *weightfile)
{
network net = parse_network_cfg(cfgfile);
if(weightfile){
@@ -282,8 +193,8 @@
fprintf(stderr, "Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
srand(time(0));
- char *base = "/home/pjreddie/data/voc/devkit/results/VOC2012/Main/comp4_det_test_";
- list *plist = get_paths("/home/pjreddie/data/voc/test.txt");
+ char *base = "results/comp4_det_test_";
+ list *plist = get_paths("data/voc.2012test.list");
char **paths = (char **)list_to_array(plist);
int classes = layer.classes;
@@ -401,5 +312,4 @@
if(0==strcmp(argv[2], "test")) test_detection(cfg, weights, filename);
else if(0==strcmp(argv[2], "train")) train_detection(cfg, weights);
else if(0==strcmp(argv[2], "valid")) validate_detection(cfg, weights);
- else if(0==strcmp(argv[2], "run")) valid_detection(cfg, weights);
}
--
Gitblit v1.10.0