From e63b3a6f912cc2b1f6f00f2a9d342624a06dc3a4 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Tue, 09 Jun 2015 18:17:46 +0000
Subject: [PATCH] syncing messed something up
---
src/detection.c | 119 +++++++++++++++++++++++++++++++++++++++++++++++++++--------
1 files changed, 103 insertions(+), 16 deletions(-)
diff --git a/src/detection.c b/src/detection.c
index c012848..ccd5097 100644
--- a/src/detection.c
+++ b/src/detection.c
@@ -21,7 +21,7 @@
//printf("%d\n", j);
//printf("Prob: %f\n", box[j]);
int class = max_index(box+j, classes);
- if(box[j+class] > .4){
+ if(box[j+class] > .05){
//int z;
//for(z = 0; z < classes; ++z) printf("%f %s\n", box[j+z], class_names[z]);
printf("%f %s\n", box[j+class], class_names[class]);
@@ -32,8 +32,8 @@
//float maxheight = distance_from_edge(r, side);
//float maxwidth = distance_from_edge(c, side);
j += classes;
- float y = box[j+0];
- float x = box[j+1];
+ float x = box[j+0];
+ float y = box[j+1];
x = (x+c)/side;
y = (y+r)/side;
float w = box[j+2]; //*maxwidth;
@@ -257,10 +257,11 @@
if (imgnet){
plist = get_paths("/home/pjreddie/data/imagenet/det.train.list");
}else{
- plist = get_paths("/home/pjreddie/data/voc/no_2012_val.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/voc/val_2012.txt");
//plist = get_paths("/home/pjreddie/data/coco/trainval.txt");
- //plist = get_paths("/home/pjreddie/data/voc/all2007-2012.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);
@@ -272,12 +273,13 @@
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);
- draw_detection(copy, train.y.vals[114], 7);
+ draw_detection(copy, train.y.vals[114], 7, "truth");
+ cvWaitKey(0);
free_image(copy);
- */
+ */
printf("Loaded: %lf seconds\n", sec(clock()-time));
time=clock();
@@ -289,7 +291,7 @@
if(i == 100){
net.learning_rate *= 10;
}
- if(i%100==0){
+ if(i%1000==0){
char buff[256];
sprintf(buff, "/home/pjreddie/imagenet_backup/%s_%d.weights",base, i);
save_weights(net, buff);
@@ -313,8 +315,8 @@
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);
+ 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+nuisance];
@@ -337,7 +339,88 @@
srand(time(0));
//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/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);
+
+ int classes = layer.classes;
+ int nuisance = layer.nuisance;
+ int background = (layer.background && !nuisance);
+ int num_boxes = sqrt(get_detection_layer_locations(layer));
+
+ int per_box = 4+classes+background+nuisance;
+ 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]));
+ }
+
+ //clock_t time;
+ for(i = nthreads; i <= splits; i += nthreads){
+ //time=clock();
+ 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));
+ fprintf(stderr, "%d\n", i);
+ for(t = 0; t < nthreads; ++t){
+ predict_detections(net, val[t], .001, (i-nthreads+t)*m/splits, classes, nuisance, background, num_boxes, per_box);
+ free_data(val[t]);
+ }
+ }
+ fprintf(stderr, "Total Detection Time: %f Seconds\n", (double)(time(0) - start));
+}
+
+void do_mask(network net, data d, int offset, int classes, int nuisance, int background, int num_boxes, int per_box)
+{
+ matrix pred = network_predict_data(net, d);
+ int j, k;
+ for(j = 0; j < pred.rows; ++j){
+ printf("%d ", offset + j);
+ for(k = 0; k < pred.cols; k += per_box){
+ float scale = 1.-pred.vals[j][k];
+ printf("%f ", scale);
+ }
+ printf("\n");
+ }
+ free_matrix(pred);
+}
+
+void mask_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_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");
@@ -381,7 +464,7 @@
fprintf(stderr, "%d: Loaded: %lf seconds\n", i, sec(clock()-time));
for(t = 0; t < nthreads; ++t){
- predict_detections(net, val[t], .01, (i-nthreads+t)*m/splits, classes, nuisance, background, num_boxes, per_box);
+ do_mask(net, val[t], (i-nthreads+t)*m/splits, classes, nuisance, background, num_boxes, per_box);
free_data(val[t]);
}
time=clock();
@@ -526,14 +609,17 @@
while(1){
fgets(filename, 256, stdin);
strtok(filename, "\n");
- image im = load_image_color(filename, im_size, im_size);
+ image im = load_image_color(filename,0,0);
+ image sized = resize_image(im, im_size, im_size);
printf("%d %d %d\n", im.h, im.w, im.c);
- float *X = im.data;
+ float *X = sized.data;
time=clock();
float *predictions = network_predict(net, X);
printf("%s: Predicted in %f seconds.\n", filename, sec(clock()-time));
- draw_detection(im, predictions, 7, "detections");
+ draw_detection(im, predictions, 7, "YOLO#SWAG#BLAZEIT");
free_image(im);
+ free_image(sized);
+ cvWaitKey(0);
}
}
@@ -551,5 +637,6 @@
else if(0==strcmp(argv[2], "teststuff")) train_detection_teststuff(cfg, weights);
else if(0==strcmp(argv[2], "trainloc")) train_localization(cfg, weights);
else if(0==strcmp(argv[2], "valid")) validate_detection(cfg, weights);
+ else if(0==strcmp(argv[2], "mask")) mask_detection(cfg, weights);
else if(0==strcmp(argv[2], "validpost")) validate_detection_post(cfg, weights);
}
--
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