From c1bb8c129d7d4d8fc85348d5e7ac5441fa36ead5 Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Sat, 19 May 2018 13:52:05 +0000
Subject: [PATCH] Fixed xnor for random=1
---
src/detector.c | 74 ++++++++++++++++++++++++++++++------
1 files changed, 61 insertions(+), 13 deletions(-)
diff --git a/src/detector.c b/src/detector.c
index e891cd7..3b486fb 100644
--- a/src/detector.c
+++ b/src/detector.c
@@ -21,10 +21,10 @@
#ifndef CV_VERSION_EPOCH
#include "opencv2/videoio/videoio_c.h"
-#define OPENCV_VERSION CVAUX_STR(CV_VERSION_MAJOR)""CVAUX_STR(CV_VERSION_MINOR)""CVAUX_STR(CV_VERSION_REVISION)
+#define OPENCV_VERSION CVAUX_STR(CV_VERSION_MAJOR)"" CVAUX_STR(CV_VERSION_MINOR)"" CVAUX_STR(CV_VERSION_REVISION)
#pragma comment(lib, "opencv_world" OPENCV_VERSION ".lib")
#else
-#define OPENCV_VERSION CVAUX_STR(CV_VERSION_EPOCH)""CVAUX_STR(CV_VERSION_MAJOR)""CVAUX_STR(CV_VERSION_MINOR)
+#define OPENCV_VERSION CVAUX_STR(CV_VERSION_EPOCH)"" CVAUX_STR(CV_VERSION_MAJOR)"" CVAUX_STR(CV_VERSION_MINOR)
#pragma comment(lib, "opencv_core" OPENCV_VERSION ".lib")
#pragma comment(lib, "opencv_imgproc" OPENCV_VERSION ".lib")
#pragma comment(lib, "opencv_highgui" OPENCV_VERSION ".lib")
@@ -66,6 +66,11 @@
srand(time(0));
network net = nets[0];
+ if ((net.batch * net.subdivisions) == 1) {
+ printf("\n Error: You set incorrect value batch=1 for Training! You should set batch=64 subdivision=64 \n");
+ getchar();
+ }
+
int imgs = net.batch * net.subdivisions * ngpus;
printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
data train, buffer;
@@ -121,12 +126,18 @@
while(get_current_batch(net) < net.max_batches){
if(l.random && count++%10 == 0){
printf("Resizing\n");
- int dim = (rand() % 12 + (init_w/32 - 5)) * 32; // +-160
- //if (get_current_batch(net)+100 > net.max_batches) dim = 544;
+ //int dim = (rand() % 12 + (init_w/32 - 5)) * 32; // +-160
//int dim = (rand() % 4 + 16) * 32;
- printf("%d\n", dim);
- args.w = dim;
- args.h = dim;
+ //if (get_current_batch(net)+100 > net.max_batches) dim = 544;
+ int random_val = rand() % 12;
+ int dim_w = (random_val + (init_w / 32 - 5)) * 32; // +-160
+ int dim_h = (random_val + (init_h / 32 - 5)) * 32; // +-160
+ if (dim_w < 32) dim_w = 32;
+ if (dim_h < 32) dim_h = 32;
+
+ printf("%d x %d \n", dim_w, dim_h);
+ args.w = dim_w;
+ args.h = dim_h;
pthread_join(load_thread, 0);
train = buffer;
@@ -134,7 +145,7 @@
load_thread = load_data(args);
for(i = 0; i < ngpus; ++i){
- resize_network(nets + i, dim, dim);
+ resize_network(nets + i, dim_w, dim_h);
}
net = nets[0];
}
@@ -416,7 +427,7 @@
fprintf(fp, "\n]\n");
fclose(fp);
}
- fprintf(stderr, "Total Detection Time: %f Seconds\n", time(0) - start);
+ fprintf(stderr, "Total Detection Time: %f Seconds\n", (double)time(0) - start);
}
void validate_detector_recall(char *datacfg, char *cfgfile, char *weightfile)
@@ -470,6 +481,7 @@
find_replace(labelpath, ".bmp", ".txt", labelpath);
find_replace(labelpath, ".JPG", ".txt", labelpath);
find_replace(labelpath, ".JPEG", ".txt", labelpath);
+ find_replace(labelpath, ".ppm", ".txt", labelpath);
int num_labels = 0;
box_label *truth = read_boxes(labelpath, &num_labels);
@@ -627,6 +639,7 @@
find_replace(labelpath, ".bmp", ".txt", labelpath);
find_replace(labelpath, ".JPG", ".txt", labelpath);
find_replace(labelpath, ".JPEG", ".txt", labelpath);
+ find_replace(labelpath, ".ppm", ".txt", labelpath);
int num_labels = 0;
box_label *truth = read_boxes(labelpath, &num_labels);
int i, j;
@@ -890,6 +903,7 @@
find_replace(labelpath, ".bmp", ".txt", labelpath);
find_replace(labelpath, ".JPG", ".txt", labelpath);
find_replace(labelpath, ".JPEG", ".txt", labelpath);
+ find_replace(labelpath, ".ppm", ".txt", labelpath);
int num_labels = 0;
box_label *truth = read_boxes(labelpath, &num_labels);
//printf(" new path: %s \n", labelpath);
@@ -1041,7 +1055,8 @@
}
#endif // OPENCV
-void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filename, float thresh, float hier_thresh, int dont_show)
+void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filename, float thresh,
+ float hier_thresh, int dont_show, int ext_output)
{
list *options = read_data_cfg(datacfg);
char *name_list = option_find_str(options, "names", "data/names.list");
@@ -1093,13 +1108,43 @@
int nboxes = 0;
detection *dets = get_network_boxes(&net, im.w, im.h, thresh, hier_thresh, 0, 1, &nboxes, letterbox);
if (nms) do_nms_sort(dets, nboxes, l.classes, nms);
- draw_detections_v3(im, dets, nboxes, thresh, names, alphabet, l.classes);
- free_detections(dets, nboxes);
+ draw_detections_v3(im, dets, nboxes, thresh, names, alphabet, l.classes, ext_output);
save_image(im, "predictions");
if (!dont_show) {
show_image(im, "predictions");
}
+/*
+ // pseudo labeling concept - fast.ai
+ {
+ char labelpath[4096];
+ find_replace(input, ".jpg", ".txt", labelpath);
+ find_replace(labelpath, ".png", ".txt", labelpath);
+ find_replace(labelpath, ".bmp", ".txt", labelpath);
+ find_replace(labelpath, ".JPG", ".txt", labelpath);
+ find_replace(labelpath, ".JPEG", ".txt", labelpath);
+ find_replace(labelpath, ".ppm", ".txt", labelpath);
+ FILE* fw = fopen(labelpath, "wb");
+ int i;
+ for (i = 0; i < nboxes; ++i) {
+ char buff[1024];
+ int class_id = -1;
+ float prob = 0;
+ for (j = 0; j < l.classes; ++j) {
+ if (dets[i].prob[j] > thresh && dets[i].prob[j] > prob) {
+ prob = dets[i].prob[j];
+ class_id = j;
+ }
+ }
+ if (class_id >= 0) {
+ sprintf(buff, "%d %2.4f %2.4f %2.4f %2.4f\n", class_id, dets[i].bbox.x, dets[i].bbox.y, dets[i].bbox.w, dets[i].bbox.h);
+ fwrite(buff, sizeof(char), strlen(buff), fw);
+ }
+ }
+ fclose(fw);
+ }
+*/
+ free_detections(dets, nboxes);
free_image(im);
free_image(sized);
//free(boxes);
@@ -1145,6 +1190,9 @@
int num_of_clusters = find_int_arg(argc, argv, "-num_of_clusters", 5);
int width = find_int_arg(argc, argv, "-width", -1);
int height = find_int_arg(argc, argv, "-height", -1);
+ // extended output in test mode (output of rect bound coords)
+ // and for recall mode (extended output table-like format with results for best_class fit)
+ int ext_output = find_arg(argc, argv, "-ext_output");
if(argc < 4){
fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]);
return;
@@ -1181,7 +1229,7 @@
if(strlen(weights) > 0)
if (weights[strlen(weights) - 1] == 0x0d) weights[strlen(weights) - 1] = 0;
char *filename = (argc > 6) ? argv[6]: 0;
- if(0==strcmp(argv[2], "test")) test_detector(datacfg, cfg, weights, filename, thresh, hier_thresh, dont_show);
+ if(0==strcmp(argv[2], "test")) test_detector(datacfg, cfg, weights, filename, thresh, hier_thresh, dont_show, ext_output);
else if(0==strcmp(argv[2], "train")) train_detector(datacfg, cfg, weights, gpus, ngpus, clear, dont_show);
else if(0==strcmp(argv[2], "valid")) validate_detector(datacfg, cfg, weights, outfile);
else if(0==strcmp(argv[2], "recall")) validate_detector_recall(datacfg, cfg, weights);
--
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