From 2ce6460c79e06caa33eab3991ee3e7fd9f0909d6 Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Tue, 10 Apr 2018 18:08:24 +0000
Subject: [PATCH] Remove truth only if smaller than 1x1 pix during training
---
src/data.c | 154 +++++++++++++++++++++++++++++++++++++++------------
1 files changed, 118 insertions(+), 36 deletions(-)
diff --git a/src/data.c b/src/data.c
index f3fa04f..abdb043 100644
--- a/src/data.c
+++ b/src/data.c
@@ -39,17 +39,6 @@
}
*/
-inline unsigned int random_gen()
-{
- unsigned int Num = 0;
-#ifdef WIN32
- rand_s(&Num);
-#else
- Num = rand();
-#endif
- return Num;
-}
-
char **get_random_paths(char **paths, int n, int m)
{
char **random_paths = calloc(n, sizeof(char*));
@@ -280,7 +269,7 @@
h = boxes[i].h;
id = boxes[i].id;
- if (w < .01 || h < .01) continue;
+ if (w < .001 || h < .001) continue;
int col = (int)(x*num_boxes);
int row = (int)(y*num_boxes);
@@ -303,7 +292,8 @@
free(boxes);
}
-void fill_truth_detection(char *path, int num_boxes, float *truth, int classes, int flip, float dx, float dy, float sx, float sy)
+void fill_truth_detection(char *path, int num_boxes, float *truth, int classes, int flip, float dx, float dy, float sx, float sy,
+ int small_object, int net_w, int net_h)
{
char labelpath[4096];
find_replace(path, "images", "labels", labelpath);
@@ -315,13 +305,21 @@
find_replace(labelpath, ".JPG", ".txt", labelpath);
find_replace(labelpath, ".JPEG", ".txt", labelpath);
int count = 0;
+ int i;
box_label *boxes = read_boxes(labelpath, &count);
+ float lowest_w = 1.F / net_w;
+ float lowest_h = 1.F / net_h;
+ if (small_object == 1) {
+ for (i = 0; i < count; ++i) {
+ if (boxes[i].w < lowest_w) boxes[i].w = lowest_w;
+ if (boxes[i].h < lowest_h) boxes[i].h = lowest_h;
+ }
+ }
randomize_boxes(boxes, count);
correct_boxes(boxes, count, dx, dy, sx, sy, flip);
if(count > num_boxes) count = num_boxes;
float x,y,w,h;
int id;
- int i;
for (i = 0; i < count; ++i) {
x = boxes[i].x;
@@ -330,7 +328,10 @@
h = boxes[i].h;
id = boxes[i].id;
- if ((w < .01 || h < .01)) continue;
+ // not detect small objects
+ //if ((w < 0.001F || h < 0.001F)) continue;
+ // if truth (box for object) is smaller than 1x1 pix
+ if ((w < lowest_w || h < lowest_h)) continue;
truth[i*5+0] = x;
truth[i*5+1] = y;
@@ -672,7 +673,18 @@
return d;
}
-data load_data_detection(int n, char **paths, int m, int w, int h, int boxes, int classes, float jitter, float hue, float saturation, float exposure)
+#ifdef OPENCV
+#include "opencv2/highgui/highgui_c.h"
+#include "opencv2/imgproc/imgproc_c.h"
+#include "opencv2/core/version.hpp"
+#ifndef CV_VERSION_EPOCH
+#include "opencv2/videoio/videoio_c.h"
+#include "opencv2/imgcodecs/imgcodecs_c.h"
+#endif
+
+#include "http_stream.h"
+
+data load_data_detection(int n, char **paths, int m, int w, int h, int boxes, int classes, float jitter, float hue, float saturation, float exposure, int small_object)
{
char **random_paths = get_random_paths(paths, n, m);
int i;
@@ -685,18 +697,30 @@
d.y = make_matrix(n, 5*boxes);
for(i = 0; i < n; ++i){
- image orig = load_image_color(random_paths[i], 0, 0);
+ const char *filename = random_paths[i];
- int oh = orig.h;
- int ow = orig.w;
+ int flag = 1;
+ IplImage *src;
+ if ((src = cvLoadImage(filename, flag)) == 0)
+ {
+ fprintf(stderr, "Cannot load image \"%s\"\n", filename);
+ char buff[256];
+ sprintf(buff, "echo %s >> bad.list", filename);
+ system(buff);
+ continue;
+ //exit(0);
+ }
+
+ int oh = src->height;
+ int ow = src->width;
int dw = (ow*jitter);
int dh = (oh*jitter);
- int pleft = rand_uniform(-dw, dw);
- int pright = rand_uniform(-dw, dw);
- int ptop = rand_uniform(-dh, dh);
- int pbot = rand_uniform(-dh, dh);
+ int pleft = rand_uniform_strong(-dw, dw);
+ int pright = rand_uniform_strong(-dw, dw);
+ int ptop = rand_uniform_strong(-dh, dh);
+ int pbot = rand_uniform_strong(-dh, dh);
int swidth = ow - pleft - pright;
int sheight = oh - ptop - pbot;
@@ -705,25 +729,80 @@
float sy = (float)sheight / oh;
int flip = random_gen()%2;
- image cropped = crop_image(orig, pleft, ptop, swidth, sheight);
float dx = ((float)pleft/ow)/sx;
float dy = ((float)ptop /oh)/sy;
- image sized = resize_image(cropped, w, h);
- if(flip) flip_image(sized);
- random_distort_image(sized, hue, saturation, exposure);
- d.X.vals[i] = sized.data;
+ float dhue = rand_uniform_strong(-hue, hue);
+ float dsat = rand_scale(saturation);
+ float dexp = rand_scale(exposure);
- fill_truth_detection(random_paths[i], boxes, d.y.vals[i], classes, flip, dx, dy, 1./sx, 1./sy);
+ image ai = image_data_augmentation(src, w, h, pleft, ptop, swidth, sheight, flip, jitter, dhue, dsat, dexp);
+ d.X.vals[i] = ai.data;
+
+ //show_image(ai, "aug");
+ //cvWaitKey(0);
- free_image(orig);
- free_image(cropped);
+ fill_truth_detection(filename, boxes, d.y.vals[i], classes, flip, dx, dy, 1./sx, 1./sy, small_object, w, h);
+
+ cvReleaseImage(&src);
}
free(random_paths);
return d;
}
+#else // OPENCV
+data load_data_detection(int n, char **paths, int m, int w, int h, int boxes, int classes, float jitter, float hue, float saturation, float exposure, int small_object)
+{
+ char **random_paths = get_random_paths(paths, n, m);
+ int i;
+ data d = { 0 };
+ d.shallow = 0;
+ d.X.rows = n;
+ d.X.vals = calloc(d.X.rows, sizeof(float*));
+ d.X.cols = h*w * 3;
+
+ d.y = make_matrix(n, 5 * boxes);
+ for (i = 0; i < n; ++i) {
+ image orig = load_image_color(random_paths[i], 0, 0);
+
+ int oh = orig.h;
+ int ow = orig.w;
+
+ int dw = (ow*jitter);
+ int dh = (oh*jitter);
+
+ int pleft = rand_uniform_strong(-dw, dw);
+ int pright = rand_uniform_strong(-dw, dw);
+ int ptop = rand_uniform_strong(-dh, dh);
+ int pbot = rand_uniform_strong(-dh, dh);
+
+ int swidth = ow - pleft - pright;
+ int sheight = oh - ptop - pbot;
+
+ float sx = (float)swidth / ow;
+ float sy = (float)sheight / oh;
+
+ int flip = random_gen() % 2;
+ image cropped = crop_image(orig, pleft, ptop, swidth, sheight);
+
+ float dx = ((float)pleft / ow) / sx;
+ float dy = ((float)ptop / oh) / sy;
+
+ image sized = resize_image(cropped, w, h);
+ if (flip) flip_image(sized);
+ random_distort_image(sized, hue, saturation, exposure);
+ d.X.vals[i] = sized.data;
+
+ fill_truth_detection(random_paths[i], boxes, d.y.vals[i], classes, flip, dx, dy, 1. / sx, 1. / sy, small_object, w, h);
+
+ free_image(orig);
+ free_image(cropped);
+ }
+ free(random_paths);
+ return d;
+}
+#endif // OPENCV
void *load_thread(void *ptr)
{
@@ -745,7 +824,7 @@
} else if (a.type == REGION_DATA){
*a.d = load_data_region(a.n, a.paths, a.m, a.w, a.h, a.num_boxes, a.classes, a.jitter, a.hue, a.saturation, a.exposure);
} else if (a.type == DETECTION_DATA){
- *a.d = load_data_detection(a.n, a.paths, a.m, a.w, a.h, a.num_boxes, a.classes, a.jitter, a.hue, a.saturation, a.exposure);
+ *a.d = load_data_detection(a.n, a.paths, a.m, a.w, a.h, a.num_boxes, a.classes, a.jitter, a.hue, a.saturation, a.exposure, a.small_object);
} else if (a.type == SWAG_DATA){
*a.d = load_data_swag(a.paths, a.n, a.classes, a.jitter);
} else if (a.type == COMPARE_DATA){
@@ -753,6 +832,9 @@
} else if (a.type == IMAGE_DATA){
*(a.im) = load_image_color(a.path, 0, 0);
*(a.resized) = resize_image(*(a.im), a.w, a.h);
+ }else if (a.type == LETTERBOX_DATA) {
+ *(a.im) = load_image_color(a.path, 0, 0);
+ *(a.resized) = letterbox_image(*(a.im), a.w, a.h);
} else if (a.type == TAG_DATA){
*a.d = load_data_tag(a.paths, a.n, a.m, a.classes, a.min, a.max, a.size, a.angle, a.aspect, a.hue, a.saturation, a.exposure);
}
@@ -971,8 +1053,8 @@
for(i = 0; i < 10000; ++i){
unsigned char bytes[3073];
fread(bytes, 1, 3073, fp);
- int class = bytes[0];
- y.vals[i][class] = 1;
+ int class_id = bytes[0];
+ y.vals[i][class_id] = 1;
for(j = 0; j < X.cols; ++j){
X.vals[i][j] = (double)bytes[j+1];
}
@@ -1035,8 +1117,8 @@
for(i = 0; i < 10000; ++i){
unsigned char bytes[3073];
fread(bytes, 1, 3073, fp);
- int class = bytes[0];
- y.vals[i+b*10000][class] = 1;
+ int class_id = bytes[0];
+ y.vals[i+b*10000][class_id] = 1;
for(j = 0; j < X.cols; ++j){
X.vals[i+b*10000][j] = (double)bytes[j+1];
}
--
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