From f39160f6e8f4465e9325e235e18f0d9413d1f672 Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Sun, 04 Mar 2018 00:09:40 +0000
Subject: [PATCH] Added: calc_anchors
---
src/detector.c | 112 +++++++++++++++++++++++++++++++++++++++++++++++++++++--
1 files changed, 107 insertions(+), 5 deletions(-)
diff --git a/src/detector.c b/src/detector.c
index 02c1560..8eaffce 100644
--- a/src/detector.c
+++ b/src/detector.c
@@ -10,7 +10,9 @@
#ifdef OPENCV
#include "opencv2/highgui/highgui_c.h"
#include "opencv2/core/core_c.h"
+//#include "opencv2/core/core.hpp"
#include "opencv2/core/version.hpp"
+#include "opencv2/imgproc/imgproc_c.h"
#ifndef CV_VERSION_EPOCH
#include "opencv2/videoio/videoio_c.h"
@@ -495,7 +497,7 @@
return 0;
}
-void validate_detector_map(char *datacfg, char *cfgfile, char *weightfile)
+void validate_detector_map(char *datacfg, char *cfgfile, char *weightfile, float thresh_calc_avg_iou)
{
int j;
list *options = read_data_cfg(datacfg);
@@ -552,7 +554,7 @@
args.h = net.h;
args.type = IMAGE_DATA;
- const float thresh_calc_avg_iou = 0.24;
+ //const float thresh_calc_avg_iou = 0.24;
float avg_iou = 0;
int tp_for_thresh = 0;
int fp_for_thresh = 0;
@@ -772,7 +774,7 @@
}
}
}
- //printf("point = %d, cur_recall = %.4f, cur_precision = %.4f \n", point, cur_recall, cur_precision);
+ //printf("class_id = %d, point = %d, cur_recall = %.4f, cur_precision = %.4f \n", i, point, cur_recall, cur_precision);
avg_precision += cur_precision;
}
@@ -781,6 +783,12 @@
mean_average_precision += avg_precision;
}
+ const float cur_precision = (float)tp_for_thresh / ((float)tp_for_thresh + (float)fp_for_thresh);
+ const float cur_recall = (float)tp_for_thresh / ((float)tp_for_thresh + (float)(unique_truth_count - tp_for_thresh));
+ const float f1_score = 2.F * cur_precision * cur_recall / (cur_precision + cur_recall);
+ printf(" for thresh = %1.2f, precision = %1.2f, recall = %1.2f, F1-score = %1.2f \n",
+ thresh_calc_avg_iou, cur_precision, cur_recall, f1_score);
+
printf(" for thresh = %0.2f, TP = %d, FP = %d, FN = %d, average IoU = %2.2f %% \n",
thresh_calc_avg_iou, tp_for_thresh, fp_for_thresh, unique_truth_count - tp_for_thresh, avg_iou * 100);
@@ -798,6 +806,95 @@
fprintf(stderr, "Total Detection Time: %f Seconds\n", (double)(time(0) - start));
}
+#ifdef OPENCV
+void calc_anchors(char *datacfg, int num_of_clusters, int final_width, int final_height)
+{
+ printf("\n num_of_clusters = %d, final_width = %d, final_height = %d \n", num_of_clusters, final_width, final_height);
+
+ //float pointsdata[] = { 1,1, 2,2, 6,6, 5,5, 10,10 };
+ float *rel_width_height_array = calloc(1000, sizeof(float));
+
+ list *options = read_data_cfg(datacfg);
+ char *train_images = option_find_str(options, "train", "data/train.list");
+ list *plist = get_paths(train_images);
+ int number_of_images = plist->size;
+ char **paths = (char **)list_to_array(plist);
+
+ int number_of_boxes = 0;
+ printf(" read labels from %d images \n", number_of_images);
+
+ int i, j;
+ for (i = 0; i < number_of_images; ++i) {
+ char *path = paths[i];
+ char labelpath[4096];
+ find_replace(path, "images", "labels", labelpath);
+ find_replace(labelpath, "JPEGImages", "labels", labelpath);
+ find_replace(labelpath, ".jpg", ".txt", labelpath);
+ find_replace(labelpath, ".JPEG", ".txt", labelpath);
+ find_replace(labelpath, ".png", ".txt", labelpath);
+ int num_labels = 0;
+ box_label *truth = read_boxes(labelpath, &num_labels);
+ //printf(" new path: %s \n", labelpath);
+ for (j = 0; j < num_labels; ++j)
+ {
+ number_of_boxes++;
+ rel_width_height_array = realloc(rel_width_height_array, 2 * number_of_boxes * sizeof(float));
+ rel_width_height_array[number_of_boxes * 2 - 2] = truth[j].w * final_width;
+ rel_width_height_array[number_of_boxes * 2 - 1] = truth[j].h * final_height;
+ printf("\r loaded \t image: %d \t box: %d", i+1, number_of_boxes);
+ }
+ }
+ printf("\n all loaded. \n");
+
+ //int number_of_boxes = 10;
+ CvMat* points = cvCreateMat(number_of_boxes, 2, CV_32FC1);
+ CvMat* centers = cvCreateMat(num_of_clusters, 2, CV_32FC1);
+ CvMat* labels = cvCreateMat(number_of_boxes, 1, CV_32SC1);
+
+ for (i = 0; i < number_of_boxes; ++i) {
+ points->data.fl[i * 2] = rel_width_height_array[i * 2];
+ points->data.fl[i * 2 + 1] = rel_width_height_array[i * 2 + 1];
+ //cvSet1D(points, i * 2, cvScalar(rel_width_height_array[i * 2], 0, 0, 0));
+ //cvSet1D(points, i * 2 + 1, cvScalar(rel_width_height_array[i * 2 + 1], 0, 0, 0));
+ }
+
+
+ const int attemps = 1000;
+ double compactness;
+
+ enum {
+ KMEANS_RANDOM_CENTERS = 0,
+ KMEANS_USE_INITIAL_LABELS = 1,
+ KMEANS_PP_CENTERS = 2
+ };
+
+ printf("\n calculating k-means++ ...");
+ // Should be used: distance(box, centroid) = 1 - IoU(box, centroid)
+ cvKMeans2(points, num_of_clusters, labels,
+ cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 1000, 0), attemps,
+ 0, KMEANS_RANDOM_CENTERS,
+ centers, &compactness);
+
+ printf("\n");
+ printf("anchors = ");
+ for (i = 0; i < num_of_clusters; ++i) {
+ printf("%2.2f,%2.2f, ", centers->data.fl[i * 2], centers->data.fl[i * 2 + 1]);
+ }
+
+ //for (i = 0; i < number_of_boxes; ++i)
+ // printf("%2.2f,%2.2f, ", points->data.fl[i * 2], points->data.fl[i * 2 + 1]);
+
+ free(rel_width_height_array);
+ cvReleaseMat(&points);
+ cvReleaseMat(¢ers);
+ cvReleaseMat(&labels);
+}
+#else
+void calc_anchors(char *datacfg, int num_of_clusters, int final_width, int final_height) {
+ printf(" k-means++ can't be used without OpenCV, because there is used cvKMeans2 implementation \n");
+}
+#endif // OPENCV
+
void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filename, float thresh, int dont_show)
{
list *options = read_data_cfg(datacfg);
@@ -870,6 +967,9 @@
float thresh = find_float_arg(argc, argv, "-thresh", .24);
int cam_index = find_int_arg(argc, argv, "-c", 0);
int frame_skip = find_int_arg(argc, argv, "-s", 0);
+ int num_of_clusters = find_int_arg(argc, argv, "-num_of_clusters", 5);
+ int final_width = find_int_arg(argc, argv, "-final_width", 13);
+ int final_heigh = find_int_arg(argc, argv, "-final_heigh", 13);
if(argc < 4){
fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]);
return;
@@ -909,7 +1009,8 @@
else if(0==strcmp(argv[2], "train")) train_detector(datacfg, cfg, weights, gpus, ngpus, clear);
else if(0==strcmp(argv[2], "valid")) validate_detector(datacfg, cfg, weights);
else if(0==strcmp(argv[2], "recall")) validate_detector_recall(datacfg, cfg, weights);
- else if(0==strcmp(argv[2], "map")) validate_detector_map(datacfg, cfg, weights);
+ else if(0==strcmp(argv[2], "map")) validate_detector_map(datacfg, cfg, weights, thresh);
+ else if(0==strcmp(argv[2], "calc_anchors")) calc_anchors(datacfg, num_of_clusters, final_width, final_heigh);
else if(0==strcmp(argv[2], "demo")) {
list *options = read_data_cfg(datacfg);
int classes = option_find_int(options, "classes", 20);
@@ -917,6 +1018,7 @@
char **names = get_labels(name_list);
if(filename)
if (filename[strlen(filename) - 1] == 0x0d) filename[strlen(filename) - 1] = 0;
- demo(cfg, weights, thresh, cam_index, filename, names, classes, frame_skip, prefix, out_filename, http_stream_port, dont_show);
+ demo(cfg, weights, thresh, cam_index, filename, names, classes, frame_skip, prefix, out_filename,
+ http_stream_port, dont_show);
}
}
--
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