From 1b5afb45838e603fa6780762eb8cc59246dc2d81 Mon Sep 17 00:00:00 2001
From: IlyaOvodov <b@ovdv.ru>
Date: Tue, 08 May 2018 11:09:35 +0000
Subject: [PATCH] Output improvements for detector results: When printing detector results, output was done in random order, obfuscating results for interpreting. Now: 1. Text output includes coordinates of rects in (left,right,top,bottom in pixels) along with label and score 2. Text output is sorted by rect lefts to simplify finding appropriate rects on image 3. If several class probs are > thresh for some detection, the most probable is written first and coordinates for others are not repeated 4. Rects are imprinted in image in order by their best class prob, so most probable rects are always on top and not overlayed by less probable ones 5. Most probable label for rect is always written first Also: 6. Message about low GPU memory include required amount
---
src/writing.c | 111 +++++++++++++++++++++++++++++--------------------------
1 files changed, 59 insertions(+), 52 deletions(-)
diff --git a/src/writing.c b/src/writing.c
index 71dd53b..0a76d48 100644
--- a/src/writing.c
+++ b/src/writing.c
@@ -9,7 +9,6 @@
void train_writing(char *cfgfile, char *weightfile)
{
char *backup_directory = "/home/pjreddie/backup/";
- data_seed = time(0);
srand(time(0));
float avg_loss = -1;
char *base = basecfg(cfgfile);
@@ -25,16 +24,18 @@
clock_t time;
int N = plist->size;
printf("N: %d\n", N);
+ image out = get_network_image(net);
data train, buffer;
load_args args = {0};
args.w = net.w;
args.h = net.h;
+ args.out_w = out.w;
+ args.out_h = out.h;
args.paths = paths;
args.n = imgs;
args.m = N;
- args.downsample = 1;
args.d = &buffer;
args.type = WRITING_DATA;
@@ -51,9 +52,9 @@
float loss = train_network(net, train);
/*
- image pred = float_to_image(64, 64, 1, out);
- print_image(pred);
- */
+ image pred = float_to_image(64, 64, 1, out);
+ print_image(pred);
+ */
/*
image im = float_to_image(256, 256, 3, train.X.vals[0]);
@@ -69,22 +70,22 @@
if(avg_loss == -1) avg_loss = loss;
avg_loss = avg_loss*.9 + loss*.1;
printf("%d, %.3f: %f, %f avg, %f rate, %lf seconds, %d images\n", get_current_batch(net), (float)(*net.seen)/N, loss, avg_loss, get_current_rate(net), sec(clock()-time), *net.seen);
- free_data(train);
- if(get_current_batch(net)%100 == 0){
- char buff[256];
- sprintf(buff, "%s/%s_batch_%d.weights", backup_directory, base, get_current_batch(net));
- save_weights(net, buff);
- }
- if(*net.seen/N > epoch){
- epoch = *net.seen/N;
- char buff[256];
- sprintf(buff, "%s/%s_%d.weights",backup_directory,base, epoch);
- save_weights(net, buff);
- }
+ free_data(train);
+ if(get_current_batch(net)%100 == 0){
+ char buff[256];
+ sprintf(buff, "%s/%s_batch_%d.weights", backup_directory, base, get_current_batch(net));
+ save_weights(net, buff);
+ }
+ if(*net.seen/N > epoch){
+ epoch = *net.seen/N;
+ char buff[256];
+ sprintf(buff, "%s/%s_%d.weights",backup_directory,base, epoch);
+ save_weights(net, buff);
+ }
}
}
-void test_writing(char *cfgfile, char *weightfile, char *outfile)
+void test_writing(char *cfgfile, char *weightfile, char *filename)
{
network net = parse_network_cfg(cfgfile);
if(weightfile){
@@ -93,51 +94,57 @@
set_batch_network(&net, 1);
srand(2222222);
clock_t time;
- char filename[256];
+ char buff[256];
+ char *input = buff;
+ while(1){
+ if(filename){
+ strncpy(input, filename, 256);
+ }else{
+ printf("Enter Image Path: ");
+ fflush(stdout);
+ input = fgets(input, 256, stdin);
+ if(!input) return;
+ strtok(input, "\n");
+ }
- fgets(filename, 256, stdin);
- strtok(filename, "\n");
- image im = load_image_color(filename, 0, 0);
- //image im = load_image_color("/home/pjreddie/darknet/data/figs/C02-1001-Figure-1.png", 0, 0);
- image sized = resize_image(im, net.w, net.h);
- printf("%d %d %d\n", im.h, im.w, im.c);
- float *X = sized.data;
- time=clock();
- network_predict(net, X);
- printf("%s: Predicted in %f seconds.\n", filename, sec(clock()-time));
- image pred = get_network_image(net);
+ image im = load_image_color(input, 0, 0);
+ resize_network(&net, im.w, im.h);
+ printf("%d %d %d\n", im.h, im.w, im.c);
+ float *X = im.data;
+ time=clock();
+ network_predict(net, X);
+ printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
+ image pred = get_network_image(net);
- image t = threshold_image(pred, .5);
- free_image(pred);
- pred = t;
+ image upsampled = resize_image(pred, im.w, im.h);
+ image thresh = threshold_image(upsampled, .5);
+ pred = thresh;
- if (outfile) {
- printf("Save image as %s.png (shape: %d %d)\n", outfile, pred.w, pred.h);
- save_image(pred, outfile);
- } else {
- show_image(sized, "orig");
show_image(pred, "prediction");
+ show_image(im, "orig");
#ifdef OPENCV
- cvWaitKey(0);
- cvDestroyAllWindows();
+ cvWaitKey(0);
+ cvDestroyAllWindows();
#endif
- }
- free_image(im);
- free_image(sized);
+ free_image(upsampled);
+ free_image(thresh);
+ free_image(im);
+ if (filename) break;
+ }
}
void run_writing(int argc, char **argv)
{
- if(argc < 4){
- fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]);
- return;
- }
+ if(argc < 4){
+ fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]);
+ return;
+ }
- char *cfg = argv[3];
- char *weights = (argc > 4) ? argv[4] : 0;
- char *outfile = (argc > 5) ? argv[5] : 0;
- if(0==strcmp(argv[2], "train")) train_writing(cfg, weights);
- else if(0==strcmp(argv[2], "test")) test_writing(cfg, weights, outfile);
+ char *cfg = argv[3];
+ char *weights = (argc > 4) ? argv[4] : 0;
+ char *filename = (argc > 5) ? argv[5] : 0;
+ if(0==strcmp(argv[2], "train")) train_writing(cfg, weights);
+ else if(0==strcmp(argv[2], "test")) test_writing(cfg, weights, filename);
}
--
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