From 372980d690f84aade1ebfd1a92750ed327ab1c8d Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Mon, 04 May 2015 18:29:21 +0000
Subject: [PATCH] i don't know what's going on anymore
---
src/detection.c | 103 ++++++++++++++++++++++++++++++---------------------
1 files changed, 61 insertions(+), 42 deletions(-)
diff --git a/src/detection.c b/src/detection.c
index eea6136..93e9fe1 100644
--- a/src/detection.c
+++ b/src/detection.c
@@ -81,7 +81,10 @@
if (imgnet){
plist = get_paths("/home/pjreddie/data/imagenet/det.train.list");
}else{
- plist = get_paths("/home/pjreddie/data/voc/trainall.txt");
+ plist = get_paths("/home/pjreddie/data/voc/no_2012_val.txt");
+ //plist = get_paths("/home/pjreddie/data/voc/no_2007_test.txt");
+ //plist = get_paths("/home/pjreddie/data/coco/trainval.txt");
+ //plist = get_paths("/home/pjreddie/data/voc/all2007-2012.txt");
}
paths = (char **)list_to_array(plist);
pthread_t load_thread = load_data_detection_thread(imgs, paths, plist->size, classes, net.w, net.h, side, side, background, &buffer);
@@ -93,14 +96,12 @@
train = buffer;
load_thread = load_data_detection_thread(imgs, paths, plist->size, classes, net.w, net.h, side, side, background, &buffer);
-/*
+ /*
image im = float_to_image(net.w, net.h, 3, train.X.vals[114]);
image copy = copy_image(im);
- translate_image(copy, 1);
- scale_image(copy, .5);
draw_detection(copy, train.y.vals[114], 7);
free_image(copy);
- */
+ */
printf("Loaded: %lf seconds\n", sec(clock()-time));
time=clock();
@@ -118,6 +119,34 @@
}
}
+void predict_detections(network net, data d, float threshold, int offset, int classes, int nuisance, 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 (nuisance) scale = 1.-pred.vals[j][k];
+ for (class = 0; class < classes; ++class){
+ int ci = k+classes+background+nuisance;
+ 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 = w*w;
+ h = h*h;
+ float prob = scale*pred.vals[j][k+class+background+nuisance];
+ if(prob < threshold) continue;
+ printf("%d %d %f %f %f %f %f\n", offset + j, class, prob, y, x, h, w);
+ }
+ }
+ }
+ free_matrix(pred);
+}
+
void validate_detection(char *cfgfile, char *weightfile)
{
network net = parse_network_cfg(cfgfile);
@@ -128,7 +157,9 @@
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/val.txt");
+ //list *plist = get_paths("/home/pjreddie/data/voc/test_2007.txt");
+ list *plist = get_paths("/home/pjreddie/data/voc/val_2012.txt");
+ //list *plist = get_paths("/home/pjreddie/data/voc/test.txt");
//list *plist = get_paths("/home/pjreddie/data/voc/val.expanded.txt");
//list *plist = get_paths("/home/pjreddie/data/voc/train.txt");
char **paths = (char **)list_to_array(plist);
@@ -144,47 +175,37 @@
int m = plist->size;
int i = 0;
int splits = 100;
- int num = (i+1)*m/splits - i*m/splits;
- fprintf(stderr, "%d\n", m);
- data val, buffer;
- pthread_t load_thread = load_data_thread(paths, num, 0, 0, num_output, net.w, net.h, &buffer);
+ int nthreads = 4;
+ int t;
+ data *val = calloc(nthreads, sizeof(data));
+ data *buf = calloc(nthreads, sizeof(data));
+ pthread_t *thr = calloc(nthreads, sizeof(data));
+ 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]));
+ }
+
clock_t time;
- for(i = 1; i <= splits; ++i){
+ for(i = nthreads; i <= splits; i += nthreads){
time=clock();
- pthread_join(load_thread, 0);
- val = buffer;
-
- num = (i+1)*m/splits - i*m/splits;
- char **part = paths+(i*m/splits);
- if(i != splits) load_thread = load_data_thread(part, num, 0, 0, num_output, net.w, net.h, &buffer);
+ 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: Loaded: %lf seconds\n", i, sec(clock()-time));
- matrix pred = network_predict_data(net, val);
- 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 (nuisance) scale = 1.-pred.vals[j][k];
- for (class = 0; class < classes; ++class){
- int ci = k+classes+background+nuisance;
- float y = (pred.vals[j][ci + 0] + row)/num_boxes;
- float x = (pred.vals[j][ci + 1] + col)/num_boxes;
- float h = pred.vals[j][ci + 2]; //* distance_from_edge(row, num_boxes);
- h = h*h;
- float w = pred.vals[j][ci + 3]; //* distance_from_edge(col, num_boxes);
- w = w*w;
- float prob = scale*pred.vals[j][k+class+background+nuisance];
- if(prob < .001) continue;
- printf("%d %d %f %f %f %f %f\n", (i-1)*m/splits + j, class, prob, y, x, h, w);
- }
- }
+ for(t = 0; t < nthreads; ++t){
+ predict_detections(net, val[t], .01, (i-nthreads+t)*m/splits, classes, nuisance, background, num_boxes, per_box);
+ free_data(val[t]);
}
time=clock();
- free_data(val);
}
}
@@ -203,8 +224,6 @@
fgets(filename, 256, stdin);
strtok(filename, "\n");
image im = load_image_color(filename, im_size, im_size);
- translate_image(im, -128);
- scale_image(im, 1/128.);
printf("%d %d %d\n", im.h, im.w, im.c);
float *X = im.data;
time=clock();
--
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