From 2c6d4ba1d5cffd26c5c9527175d565a81226e18d Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Wed, 19 Feb 2014 21:41:44 +0000
Subject: [PATCH] Single image feature extraction for VOC
---
src/tests.c | 180 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++--
1 files changed, 172 insertions(+), 8 deletions(-)
diff --git a/src/tests.c b/src/tests.c
index 09ec7b2..c72e900 100644
--- a/src/tests.c
+++ b/src/tests.c
@@ -366,20 +366,21 @@
void train_VOC()
{
- network net = parse_network_cfg("cfg/voc_backup_ramp_80.cfg");
+ network net = parse_network_cfg("cfg/voc_start.cfg");
srand(2222222);
- int i = 0;
+ int i = 20;
char *labels[] = {"aeroplane","bicycle","bird","boat","bottle","bus","car","cat","chair","cow","diningtable","dog","horse","motorbike","person","pottedplant","sheep","sofa","train","tvmonitor"};
float lr = .00001;
float momentum = .9;
float decay = 0.01;
while(i++ < 1000 || 1){
- visualize_network(net);
- cvWaitKey(100);
- data train = load_data_image_pathfile_random("images/VOC2012/train_paths.txt", 1000, labels, 20, 300, 400);
+ data train = load_data_image_pathfile_random("images/VOC2012/val_paths.txt", 1000, labels, 20, 300, 400);
+
image im = float_to_image(300, 400, 3,train.X.vals[0]);
show_image(im, "input");
+ visualize_network(net);
cvWaitKey(100);
+
normalize_data_rows(train);
clock_t start = clock(), end;
float loss = train_network_sgd(net, train, 1000, lr, momentum, decay);
@@ -388,14 +389,175 @@
free_data(train);
if(i%10==0){
char buff[256];
- sprintf(buff, "cfg/voc_backup_ramp_%d.cfg", i);
+ sprintf(buff, "cfg/voc_clean_ramp_%d.cfg", i);
save_network(net, buff);
}
//lr *= .99;
}
}
-int main()
+int voc_size(int x)
+{
+ x = x-1+3;
+ x = x-1+3;
+ x = (x-1)*2+1;
+ x = x-1+5;
+ x = (x-1)*2+1;
+ x = (x-1)*4+11;
+ return x;
+}
+
+image features_output_size(network net, IplImage *src, int outh, int outw)
+{
+ int h = voc_size(outh);
+ int w = voc_size(outw);
+
+ IplImage *sized = cvCreateImage(cvSize(w,h), src->depth, src->nChannels);
+ cvResize(src, sized, CV_INTER_LINEAR);
+ image im = ipl_to_image(sized);
+ reset_network_size(net, im.h, im.w, im.c);
+ forward_network(net, im.data);
+ image out = get_network_image_layer(net, 5);
+ //printf("%d %d\n%d %d\n", outh, out.h, outw, out.w);
+ free_image(im);
+ cvReleaseImage(&sized);
+ return copy_image(out);
+}
+
+void features_VOC(int part, int total)
+{
+ int i,j, count = 0;
+ network net = parse_network_cfg("cfg/voc_features.cfg");
+ char *path_file = "images/VOC2012/all_paths.txt";
+ char *out_dir = "voc_features/";
+ list *paths = get_paths(path_file);
+ node *n = paths->front;
+ int size = paths->size;
+ for(count = 0; count < part*size/total; ++count) n = n->next;
+ while(n && count++ < (part+1)*size/total){
+ char *path = (char *)n->val;
+ char buff[1024];
+ sprintf(buff, "%s%s.txt",out_dir, path);
+ printf("%s\n", path);
+ FILE *fp = fopen(buff, "w");
+ if(fp == 0) file_error(buff);
+
+ IplImage* src = 0;
+ if( (src = cvLoadImage(path,-1)) == 0 )
+ {
+ printf("Cannot load file image %s\n", path);
+ exit(0);
+ }
+ int w = src->width;
+ int h = src->height;
+ int sbin = 8;
+ int interval = 10;
+ double scale = pow(2., 1./interval);
+ int m = (w<h)?w:h;
+ int max_scale = 1+floor((double)log((double)m/(5.*sbin))/log(scale));
+ image *ims = calloc(max_scale+interval, sizeof(image));
+
+ for(i = 0; i < interval; ++i){
+ double factor = 1./pow(scale, i);
+ double ih = round(h*factor);
+ double iw = round(w*factor);
+ int ex_h = round(ih/4.) - 2;
+ int ex_w = round(iw/4.) - 2;
+ ims[i] = features_output_size(net, src, ex_h, ex_w);
+
+ ih = round(h*factor);
+ iw = round(w*factor);
+ ex_h = round(ih/8.) - 2;
+ ex_w = round(iw/8.) - 2;
+ ims[i+interval] = features_output_size(net, src, ex_h, ex_w);
+ for(j = i+interval; j < max_scale; j += interval){
+ factor /= 2.;
+ ih = round(h*factor);
+ iw = round(w*factor);
+ ex_h = round(ih/8.) - 2;
+ ex_w = round(iw/8.) - 2;
+ ims[j+interval] = features_output_size(net, src, ex_h, ex_w);
+ }
+ }
+ for(i = 0; i < max_scale+interval; ++i){
+ image out = ims[i];
+ //printf("%d, %d\n", out.h, out.w);
+ fprintf(fp, "%d, %d, %d\n",out.c, out.h, out.w);
+ for(j = 0; j < out.c*out.h*out.w; ++j){
+ if(j != 0)fprintf(fp, ",");
+ fprintf(fp, "%g", out.data[j]);
+ }
+ fprintf(fp, "\n");
+ free_image(out);
+ }
+ free(ims);
+ fclose(fp);
+ cvReleaseImage(&src);
+ n = n->next;
+ }
+}
+
+void features_VOC_image(char *image_file, char *image_dir, char *out_dir)
+{
+ int i,j;
+ network net = parse_network_cfg("cfg/voc_features.cfg");
+ char image_path[1024];
+ sprintf(image_path, "%s%s",image_dir, image_file);
+ char out_path[1024];
+ sprintf(out_path, "%s%s.txt",out_dir, image_file);
+ printf("%s\n", image_file);
+ FILE *fp = fopen(out_path, "w");
+ if(fp == 0) file_error(out_path);
+
+ IplImage* src = 0;
+ if( (src = cvLoadImage(image_path,-1)) == 0 ) file_error(image_path);
+ int w = src->width;
+ int h = src->height;
+ int sbin = 8;
+ int interval = 10;
+ double scale = pow(2., 1./interval);
+ int m = (w<h)?w:h;
+ int max_scale = 1+floor((double)log((double)m/(5.*sbin))/log(scale));
+ image *ims = calloc(max_scale+interval, sizeof(image));
+
+ for(i = 0; i < interval; ++i){
+ double factor = 1./pow(scale, i);
+ double ih = round(h*factor);
+ double iw = round(w*factor);
+ int ex_h = round(ih/4.) - 2;
+ int ex_w = round(iw/4.) - 2;
+ ims[i] = features_output_size(net, src, ex_h, ex_w);
+
+ ih = round(h*factor);
+ iw = round(w*factor);
+ ex_h = round(ih/8.) - 2;
+ ex_w = round(iw/8.) - 2;
+ ims[i+interval] = features_output_size(net, src, ex_h, ex_w);
+ for(j = i+interval; j < max_scale; j += interval){
+ factor /= 2.;
+ ih = round(h*factor);
+ iw = round(w*factor);
+ ex_h = round(ih/8.) - 2;
+ ex_w = round(iw/8.) - 2;
+ ims[j+interval] = features_output_size(net, src, ex_h, ex_w);
+ }
+ }
+ for(i = 0; i < max_scale+interval; ++i){
+ image out = ims[i];
+ fprintf(fp, "%d, %d, %d\n",out.c, out.h, out.w);
+ for(j = 0; j < out.c*out.h*out.w; ++j){
+ if(j != 0)fprintf(fp, ",");
+ fprintf(fp, "%g", out.data[j]);
+ }
+ fprintf(fp, "\n");
+ free_image(out);
+ }
+ free(ims);
+ fclose(fp);
+ cvReleaseImage(&src);
+}
+
+int main(int argc, char *argv[])
{
//feenableexcept(FE_DIVBYZERO | FE_INVALID | FE_OVERFLOW);
@@ -406,7 +568,9 @@
//test_ensemble();
//test_nist();
//test_full();
- train_VOC();
+ //train_VOC();
+ features_VOC_image(argv[1], argv[2], argv[3]);
+ printf("Success!\n");
//test_random_preprocess();
//test_random_classify();
//test_parser();
--
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