darknet裏樣本的存儲是以如下形式進行排列的
flag | class_info | box_info
flag爲0或者1，表示有沒有物體
class_info表示類別信息，其長度是num_class
box_info表示標註信息，其長度是5(x, y, w, h, o)
d.X.val指向實際的圖像數據，其經過深度網絡後，變成detection_layer或者region_layer裏的l.output
d.y.val指向實際的標註信息，其範圍已經轉換到[0,1]，其在detection_layer或者region_layer裏是state.truth
#include "data.h"
#include "utils.h"
#include "image.h"
#include "cuda.h"
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
pthread_mutex_t mutex = PTHREAD_MUTEX_INITIALIZER;
list *get_paths(char *filename)
{
char *path;
FILE *file = fopen(filename, "r");
if(!file) file_error(filename);
list *lines = make_list();
while((path=fgetl(file))){
list_insert(lines, path);
}
fclose(file);
return lines;
}
/*
char **get_random_paths_indexes(char **paths, int n, int m, int *indexes)
{
char **random_paths = calloc(n, sizeof(char*));
int i;
pthread_mutex_lock(&mutex);
for(i = 0; i < n; ++i){
int index = rand()%m;
indexes[i] = index;
random_paths[i] = paths[index];
if(i == 0) printf("%s\n", paths[index]);
}
pthread_mutex_unlock(&mutex);
return random_paths;
}
*/
char **get_random_paths(char **paths, int n, int m)
{
char **random_paths = calloc(n, sizeof(char*));
int i;
pthread_mutex_lock(&mutex);
for(i = 0; i < n; ++i){
int index = rand()%m;
random_paths[i] = paths[index];
//if(i == 0) printf("%s\n", paths[index]);
}
pthread_mutex_unlock(&mutex);
return random_paths;
}
char **find_replace_paths(char **paths, int n, char *find, char *replace)
{
char **replace_paths = calloc(n, sizeof(char*));
int i;
for(i = 0; i < n; ++i){
char replaced[4096];
find_replace(paths[i], find, replace, replaced);
replace_paths[i] = copy_string(replaced);
}
return replace_paths;
}
matrix load_image_paths_gray(char **paths, int n, int w, int h)
{
int i;
matrix X;
X.rows = n;
X.vals = calloc(X.rows, sizeof(float*));
X.cols = 0;
for(i = 0; i < n; ++i){
image im = load_image(paths[i], w, h, 3);
image gray = grayscale_image(im);
free_image(im);
im = gray;
X.vals[i] = im.data;
X.cols = im.h*im.w*im.c;
}
return X;
}
matrix load_image_paths(char **paths, int n, int w, int h)
{
int i;
matrix X;
X.rows = n;
X.vals = calloc(X.rows, sizeof(float*));
X.cols = 0;
for(i = 0; i < n; ++i){
image im = load_image_color(paths[i], w, h);
X.vals[i] = im.data;
X.cols = im.h*im.w*im.c;
}
return X;
}
matrix load_image_augment_paths(char **paths, int n, int min, int max, int size, float angle, float aspect, float hue, float saturation, float exposure)
{
int i;
matrix X;
X.rows = n;
X.vals = calloc(X.rows, sizeof(float*));
X.cols = 0;
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;
if (flip) flip_image(crop);
random_distort_image(crop, hue, saturation, exposure);
/*
show_image(im, "orig");
show_image(crop, "crop");
cvWaitKey(0);
*/
free_image(im);
X.vals[i] = crop.data;
X.cols = crop.h*crop.w*crop.c;
}
return X;
}
box_label *read_boxes(char *filename, int *n)
{
box_label *boxes = calloc(1, sizeof(box_label));
FILE *file = fopen(filename, "r");
if(!file) file_error(filename);
float x, y, h, w;
int id;
int count = 0;
while(fscanf(file, "%d %f %f %f %f", &id, &x, &y, &w, &h) == 5){
boxes = realloc(boxes, (count+1)*sizeof(box_label));
boxes[count].id = id;
boxes[count].x = x;
boxes[count].y = y;
boxes[count].h = h;
boxes[count].w = w;
boxes[count].left = x - w/2;
boxes[count].right = x + w/2;
boxes[count].top = y - h/2;
boxes[count].bottom = y + h/2;
++count;
}
fclose(file);
*n = count;
return boxes;
}
void randomize_boxes(box_label *b, int n)
{
int i;
for(i = 0; i < n; ++i){
box_label swap = b[i];
int index = rand()%n;
b[i] = b[index];
b[index] = swap;
}
}
void correct_boxes(box_label *boxes, int n, float dx, float dy, float sx, float sy, int flip)
{
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;
boxes[i].bottom = boxes[i].bottom* sy - dy;
if(flip){
float swap = boxes[i].left;
boxes[i].left = 1. - boxes[i].right;
boxes[i].right = 1. - swap;
}
boxes[i].left = constrain(0, 1, boxes[i].left);
boxes[i].right = constrain(0, 1, boxes[i].right);
boxes[i].top = constrain(0, 1, boxes[i].top);
boxes[i].bottom = constrain(0, 1, boxes[i].bottom);
boxes[i].x = (boxes[i].left+boxes[i].right)/2;
boxes[i].y = (boxes[i].top+boxes[i].bottom)/2;
boxes[i].w = (boxes[i].right - boxes[i].left);
boxes[i].h = (boxes[i].bottom - boxes[i].top);
boxes[i].w = constrain(0, 1, boxes[i].w);
boxes[i].h = constrain(0, 1, boxes[i].h);
}
}
void fill_truth_swag(char *path, float *truth, int classes, int flip, float dx, float dy, float sx, float sy)
{
char labelpath[4096];
find_replace(path, "images", "labels", labelpath);
find_replace(labelpath, "JPEGImages", "labels", labelpath);
find_replace(labelpath, ".jpg", ".txt", labelpath);
find_replace(labelpath, ".JPG", ".txt", labelpath);
find_replace(labelpath, ".JPEG", ".txt", labelpath);
int count = 0;
box_label *boxes = read_boxes(labelpath, &count);
randomize_boxes(boxes, count);
correct_boxes(boxes, count, dx, dy, sx, sy, flip);
float x,y,w,h;
int id;
int i;
for (i = 0; i < count && i < 30; ++i) {
x = boxes[i].x;
y = boxes[i].y;
w = boxes[i].w;
h = boxes[i].h;
id = boxes[i].id;
if (w < .0 || h < .0) continue;
int index = (4+classes) * i;
truth[index++] = x;
truth[index++] = y;
truth[index++] = w;
truth[index++] = h;
if (id < classes) truth[index+id] = 1;
}
free(boxes);
}
void fill_truth_region(char *path, float *truth, int classes, int num_boxes, int flip, float dx, float dy, float sx, float sy)
{
char labelpath[4096];
find_replace(path, "images", "labels", labelpath);
find_replace(labelpath, "JPEGImages", "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;
box_label *boxes = read_boxes(labelpath, &count);
randomize_boxes(boxes, count);
correct_boxes(boxes, count, dx, dy, sx, sy, flip);
float x,y,w,h;
int id;
int i;
for (i = 0; i < count; ++i) {
x = boxes[i].x;
y = boxes[i].y;
w = boxes[i].w;
h = boxes[i].h;
id = boxes[i].id;
if (w < .01 || h < .01) continue;
int col = (int)(x*num_boxes);
int row = (int)(y*num_boxes);
x = x*num_boxes - col;
y = y*num_boxes - row;
int index = (col+row*num_boxes)*(5+classes);
if (truth[index]) continue; // 從這裏可以看出truth是一個grid*grid*(5+classes)的數組，其中5代表着 // [0] is_obj // [1] x // [2] y // [3] w // [4] h // 然後truth的[5]--[5+classes]就是id了 // batch的索引地址，二級指針指向實際的圖像數據，二級指針的size即爲h*w*c