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 | 256 +++++++++++++++++++++++++++++++++++++++-----------
1 files changed, 198 insertions(+), 58 deletions(-)
diff --git a/src/data.c b/src/data.c
index 20d5748..abdb043 100644
--- a/src/data.c
+++ b/src/data.c
@@ -29,7 +29,7 @@
int i;
pthread_mutex_lock(&mutex);
for(i = 0; i < n; ++i){
- int index = rand()%m;
+ int index = random_gen()%m;
indexes[i] = index;
random_paths[i] = paths[index];
if(i == 0) printf("%s\n", paths[index]);
@@ -44,10 +44,12 @@
char **random_paths = calloc(n, sizeof(char*));
int i;
pthread_mutex_lock(&mutex);
- for(i = 0; i < n; ++i){
- int index = rand()%m;
+ //printf("n = %d \n", n);
+ for(i = 0; i < n; ++i){
+ int index = random_gen() % m;
random_paths[i] = paths[index];
//if(i == 0) printf("%s\n", paths[index]);
+ //printf("grp: %s\n", paths[index]);
}
pthread_mutex_unlock(&mutex);
return random_paths;
@@ -113,7 +115,7 @@
for(i = 0; i < n; ++i){
image im = load_image_color(paths[i], 0, 0);
image crop = random_augment_image(im, angle, aspect, min, max, size);
- int flip = rand()%2;
+ int flip = random_gen()%2;
if (flip) flip_image(crop);
random_distort_image(crop, hue, saturation, exposure);
@@ -161,7 +163,7 @@
int i;
for(i = 0; i < n; ++i){
box_label swap = b[i];
- int index = rand()%n;
+ int index = random_gen()%n;
b[i] = b[index];
b[index] = swap;
}
@@ -171,6 +173,13 @@
{
int i;
for(i = 0; i < n; ++i){
+ if(boxes[i].x == 0 && boxes[i].y == 0) {
+ boxes[i].x = 999999;
+ boxes[i].y = 999999;
+ boxes[i].w = 999999;
+ boxes[i].h = 999999;
+ continue;
+ }
boxes[i].left = boxes[i].left * sx - dx;
boxes[i].right = boxes[i].right * sx - dx;
boxes[i].top = boxes[i].top * sy - dy;
@@ -260,7 +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);
@@ -283,24 +292,34 @@
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);
find_replace(labelpath, "JPEGImages", "labels", labelpath);
+ find_replace(labelpath, "raw", "labels", labelpath);
find_replace(labelpath, ".jpg", ".txt", labelpath);
find_replace(labelpath, ".png", ".txt", labelpath);
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;
@@ -309,7 +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;
@@ -388,12 +410,47 @@
if(count != 1) printf("Too many or too few labels: %d, %s\n", count, path);
}
-matrix load_labels_paths(char **paths, int n, char **labels, int k)
+void fill_hierarchy(float *truth, int k, tree *hierarchy)
+{
+ int j;
+ for(j = 0; j < k; ++j){
+ if(truth[j]){
+ int parent = hierarchy->parent[j];
+ while(parent >= 0){
+ truth[parent] = 1;
+ parent = hierarchy->parent[parent];
+ }
+ }
+ }
+ int i;
+ int count = 0;
+ for(j = 0; j < hierarchy->groups; ++j){
+ //printf("%d\n", count);
+ int mask = 1;
+ for(i = 0; i < hierarchy->group_size[j]; ++i){
+ if(truth[count + i]){
+ mask = 0;
+ break;
+ }
+ }
+ if (mask) {
+ for(i = 0; i < hierarchy->group_size[j]; ++i){
+ truth[count + i] = SECRET_NUM;
+ }
+ }
+ count += hierarchy->group_size[j];
+ }
+}
+
+matrix load_labels_paths(char **paths, int n, char **labels, int k, tree *hierarchy)
{
matrix y = make_matrix(n, k);
int i;
for(i = 0; i < n && labels; ++i){
fill_truth(paths[i], labels, k, y.vals[i]);
+ if(hierarchy){
+ fill_hierarchy(y.vals[i], k, hierarchy);
+ }
}
return y;
}
@@ -479,7 +536,7 @@
float sx = (float)swidth / ow;
float sy = (float)sheight / oh;
- int flip = rand()%2;
+ int flip = random_gen()%2;
image cropped = crop_image(orig, pleft, ptop, swidth, sheight);
float dx = ((float)pleft/ow)/sx;
@@ -540,7 +597,7 @@
while(fscanf(fp2, "%d %f", &id, &iou) == 2){
if (d.y.vals[i][2*id + 1] < iou) d.y.vals[i][2*id + 1] = iou;
}
-
+
for (j = 0; j < classes; ++j){
if (d.y.vals[i][2*j] > .5 && d.y.vals[i][2*j+1] < .5){
d.y.vals[i][2*j] = 1;
@@ -565,9 +622,9 @@
data load_data_swag(char **paths, int n, int classes, float jitter)
{
- int index = rand()%n;
+ int index = random_gen()%n;
char *random_path = paths[index];
-
+
image orig = load_image_color(random_path, 0, 0);
int h = orig.h;
int w = orig.w;
@@ -598,7 +655,7 @@
float sx = (float)swidth / w;
float sy = (float)sheight / h;
- int flip = rand()%2;
+ int flip = random_gen()%2;
image cropped = crop_image(orig, pleft, ptop, swidth, sheight);
float dx = ((float)pleft/w)/sx;
@@ -616,7 +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;
@@ -629,18 +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;
@@ -648,30 +728,86 @@
float sx = (float)swidth / ow;
float sy = (float)sheight / oh;
- int flip = rand()%2;
- image cropped = crop_image(orig, pleft, ptop, swidth, sheight);
+ int flip = random_gen()%2;
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)
{
- //printf("Loading data: %d\n", rand());
+ //srand(time(0));
+ //printf("Loading data: %d\n", random_gen());
load_args a = *(struct load_args*)ptr;
if(a.exposure == 0) a.exposure = 1;
if(a.saturation == 0) a.saturation = 1;
@@ -680,7 +816,7 @@
if (a.type == OLD_CLASSIFICATION_DATA){
*a.d = load_data_old(a.paths, a.n, a.m, a.labels, a.classes, a.w, a.h);
} else if (a.type == CLASSIFICATION_DATA){
- *a.d = load_data_augment(a.paths, a.n, a.m, a.labels, a.classes, a.min, a.max, a.size, a.angle, a.aspect, a.hue, a.saturation, a.exposure);
+ *a.d = load_data_augment(a.paths, a.n, a.m, a.labels, a.classes, a.hierarchy, a.min, a.max, a.size, a.angle, a.aspect, a.hue, a.saturation, a.exposure);
} else if (a.type == SUPER_DATA){
*a.d = load_data_super(a.paths, a.n, a.m, a.w, a.h, a.scale);
} else if (a.type == WRITING_DATA){
@@ -688,7 +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){
@@ -696,6 +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);
}
@@ -714,6 +853,7 @@
void *load_threads(void *ptr)
{
+ //srand(time(0));
int i;
load_args args = *(load_args *)ptr;
if (args.threads == 0) args.threads = 1;
@@ -771,24 +911,24 @@
data d = {0};
d.shallow = 0;
d.X = load_image_paths(paths, n, w, h);
- d.y = load_labels_paths(paths, n, labels, k);
+ d.y = load_labels_paths(paths, n, labels, k, 0);
if(m) free(paths);
return d;
}
/*
-data load_data_study(char **paths, int n, int m, char **labels, int k, int min, int max, int size, float angle, float aspect, float hue, float saturation, float exposure)
-{
- data d = {0};
- d.indexes = calloc(n, sizeof(int));
- if(m) paths = get_random_paths_indexes(paths, n, m, d.indexes);
- d.shallow = 0;
- d.X = load_image_augment_paths(paths, n, min, max, size, angle, aspect, hue, saturation, exposure);
- d.y = load_labels_paths(paths, n, labels, k);
- if(m) free(paths);
- return d;
-}
-*/
+ data load_data_study(char **paths, int n, int m, char **labels, int k, int min, int max, int size, float angle, float aspect, float hue, float saturation, float exposure)
+ {
+ data d = {0};
+ d.indexes = calloc(n, sizeof(int));
+ if(m) paths = get_random_paths_indexes(paths, n, m, d.indexes);
+ d.shallow = 0;
+ d.X = load_image_augment_paths(paths, n, min, max, size, angle, aspect, hue, saturation, exposure);
+ d.y = load_labels_paths(paths, n, labels, k);
+ if(m) free(paths);
+ return d;
+ }
+ */
data load_data_super(char **paths, int n, int m, int w, int h, int scale)
{
@@ -808,7 +948,7 @@
for(i = 0; i < n; ++i){
image im = load_image_color(paths[i], 0, 0);
image crop = random_crop_image(im, w*scale, h*scale);
- int flip = rand()%2;
+ int flip = random_gen()%2;
if (flip) flip_image(crop);
image resize = resize_image(crop, w, h);
d.X.vals[i] = resize.data;
@@ -820,13 +960,13 @@
return d;
}
-data load_data_augment(char **paths, int n, int m, char **labels, int k, int min, int max, int size, float angle, float aspect, float hue, float saturation, float exposure)
+data load_data_augment(char **paths, int n, int m, char **labels, int k, tree *hierarchy, int min, int max, int size, float angle, float aspect, float hue, float saturation, float exposure)
{
if(m) paths = get_random_paths(paths, n, m);
data d = {0};
d.shallow = 0;
d.X = load_image_augment_paths(paths, n, min, max, size, angle, aspect, hue, saturation, exposure);
- d.y = load_labels_paths(paths, n, labels, k);
+ d.y = load_labels_paths(paths, n, labels, k, hierarchy);
if(m) free(paths);
return d;
}
@@ -913,8 +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];
}
@@ -930,7 +1070,7 @@
{
int j;
for(j = 0; j < n; ++j){
- int index = rand()%d.X.rows;
+ int index = random_gen()%d.X.rows;
memcpy(X+j*d.X.cols, d.X.vals[index], d.X.cols*sizeof(float));
memcpy(y+j*d.y.cols, d.y.vals[index], d.y.cols*sizeof(float));
}
@@ -977,8 +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];
}
@@ -1043,7 +1183,7 @@
{
int i;
for(i = d.X.rows-1; i > 0; --i){
- int index = rand()%i;
+ int index = random_gen()%i;
float *swap = d.X.vals[index];
d.X.vals[index] = d.X.vals[i];
d.X.vals[i] = swap;
@@ -1107,7 +1247,7 @@
int i;
for(i = 0; i < num; ++i){
- int index = rand()%d.X.rows;
+ int index = random_gen()%d.X.rows;
r.X.vals[i] = d.X.vals[index];
r.y.vals[i] = d.y.vals[index];
}
--
Gitblit v1.10.0