mirror of https://github.com/pjreddie/darknet.git
806 lines
20 KiB
C
806 lines
20 KiB
C
#include "data.h"
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#include "utils.h"
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#include "image.h"
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#include <stdio.h>
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#include <stdlib.h>
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#include <string.h>
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unsigned int data_seed;
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typedef struct load_args{
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char **paths;
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int n;
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int m;
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char **labels;
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int k;
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int h;
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int w;
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int nh;
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int nw;
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int num_boxes;
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int classes;
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int background;
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data *d;
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char *path;
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image *im;
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image *resized;
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} load_args;
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list *get_paths(char *filename)
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{
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char *path;
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FILE *file = fopen(filename, "r");
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if(!file) file_error(filename);
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list *lines = make_list();
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while((path=fgetl(file))){
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list_insert(lines, path);
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}
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fclose(file);
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return lines;
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}
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char **get_random_paths(char **paths, int n, int m)
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{
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char **random_paths = calloc(n, sizeof(char*));
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int i;
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for(i = 0; i < n; ++i){
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int index = rand_r(&data_seed)%m;
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random_paths[i] = paths[index];
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if(i == 0) printf("%s\n", paths[index]);
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}
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return random_paths;
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}
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char **find_replace_paths(char **paths, int n, char *find, char *replace)
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{
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char **replace_paths = calloc(n, sizeof(char*));
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int i;
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for(i = 0; i < n; ++i){
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char *replaced = find_replace(paths[i], find, replace);
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replace_paths[i] = copy_string(replaced);
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}
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return replace_paths;
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}
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matrix load_image_paths_gray(char **paths, int n, int w, int h)
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{
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int i;
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matrix X;
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X.rows = n;
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X.vals = calloc(X.rows, sizeof(float*));
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X.cols = 0;
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for(i = 0; i < n; ++i){
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image im = load_image(paths[i], w, h, 1);
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X.vals[i] = im.data;
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X.cols = im.h*im.w*im.c;
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}
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return X;
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}
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matrix load_image_paths(char **paths, int n, int w, int h)
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{
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int i;
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matrix X;
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X.rows = n;
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X.vals = calloc(X.rows, sizeof(float*));
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X.cols = 0;
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for(i = 0; i < n; ++i){
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image im = load_image_color(paths[i], w, h);
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X.vals[i] = im.data;
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X.cols = im.h*im.w*im.c;
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}
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return X;
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}
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typedef struct{
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int id;
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float x,y,w,h;
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float left, right, top, bottom;
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} box_label;
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box_label *read_boxes(char *filename, int *n)
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{
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box_label *boxes = calloc(1, sizeof(box_label));
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FILE *file = fopen(filename, "r");
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if(!file) file_error(filename);
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float x, y, h, w;
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int id;
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int count = 0;
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while(fscanf(file, "%d %f %f %f %f", &id, &x, &y, &w, &h) == 5){
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boxes = realloc(boxes, (count+1)*sizeof(box_label));
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boxes[count].id = id;
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boxes[count].x = x;
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boxes[count].y = y;
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boxes[count].h = h;
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boxes[count].w = w;
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boxes[count].left = x - w/2;
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boxes[count].right = x + w/2;
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boxes[count].top = y - h/2;
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boxes[count].bottom = y + h/2;
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++count;
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}
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fclose(file);
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*n = count;
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return boxes;
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}
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void randomize_boxes(box_label *b, int n)
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{
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int i;
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for(i = 0; i < n; ++i){
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box_label swap = b[i];
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int index = rand_r(&data_seed)%n;
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b[i] = b[index];
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b[index] = swap;
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}
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}
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void fill_truth_detection(char *path, float *truth, int classes, int num_boxes, int flip, int background, float dx, float dy, float sx, float sy)
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{
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char *labelpath = find_replace(path, "JPEGImages", "labels");
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labelpath = find_replace(labelpath, ".jpg", ".txt");
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labelpath = find_replace(labelpath, ".JPEG", ".txt");
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int count = 0;
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box_label *boxes = read_boxes(labelpath, &count);
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randomize_boxes(boxes, count);
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float x,y,w,h;
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float left, top, right, bot;
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int id;
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int i;
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if(background){
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for(i = 0; i < num_boxes*num_boxes*(4+classes+background); i += 4+classes+background){
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truth[i] = 1;
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}
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}
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for(i = 0; i < count; ++i){
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left = boxes[i].left * sx - dx;
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right = boxes[i].right * sx - dx;
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top = boxes[i].top * sy - dy;
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bot = boxes[i].bottom* sy - dy;
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id = boxes[i].id;
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if(flip){
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float swap = left;
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left = 1. - right;
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right = 1. - swap;
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}
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left = constrain(0, 1, left);
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right = constrain(0, 1, right);
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top = constrain(0, 1, top);
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bot = constrain(0, 1, bot);
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x = (left+right)/2;
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y = (top+bot)/2;
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w = (right - left);
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h = (bot - top);
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if (x <= 0 || x >= 1 || y <= 0 || y >= 1) continue;
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int i = (int)(x*num_boxes);
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int j = (int)(y*num_boxes);
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x = x*num_boxes - i;
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y = y*num_boxes - j;
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/*
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float maxwidth = distance_from_edge(i, num_boxes);
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float maxheight = distance_from_edge(j, num_boxes);
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w = w/maxwidth;
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h = h/maxheight;
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*/
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w = constrain(0, 1, w);
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h = constrain(0, 1, h);
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if (w < .01 || h < .01) continue;
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if(1){
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//w = sqrt(w);
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//h = sqrt(h);
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w = pow(w, 1./2.);
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h = pow(h, 1./2.);
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}
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int index = (i+j*num_boxes)*(4+classes+background);
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if(truth[index+classes+background+2]) continue;
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if(background) truth[index++] = 0;
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truth[index+id] = 1;
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index += classes;
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truth[index++] = x;
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truth[index++] = y;
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truth[index++] = w;
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truth[index++] = h;
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}
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free(boxes);
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}
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void fill_truth_localization(char *path, float *truth, int classes, int flip, float dx, float dy, float sx, float sy)
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{
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char *labelpath = find_replace(path, "objects", "object_labels");
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labelpath = find_replace(labelpath, ".jpg", ".txt");
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labelpath = find_replace(labelpath, ".JPEG", ".txt");
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int count;
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box_label *boxes = read_boxes(labelpath, &count);
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box_label box = boxes[0];
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free(boxes);
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float x,y,w,h;
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float left, top, right, bot;
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int id;
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int i;
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for(i = 0; i < count; ++i){
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left = box.left * sx - dx;
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right = box.right * sx - dx;
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top = box.top * sy - dy;
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bot = box.bottom* sy - dy;
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id = box.id;
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if(flip){
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float swap = left;
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left = 1. - right;
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right = 1. - swap;
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}
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left = constrain(0, 1, left);
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right = constrain(0, 1, right);
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top = constrain(0, 1, top);
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bot = constrain(0, 1, bot);
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x = (left+right)/2;
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y = (top+bot)/2;
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w = (right - left);
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h = (bot - top);
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if (x <= 0 || x >= 1 || y <= 0 || y >= 1) continue;
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w = constrain(0, 1, w);
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h = constrain(0, 1, h);
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if (w == 0 || h == 0) continue;
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int index = id*4;
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truth[index++] = x;
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truth[index++] = y;
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truth[index++] = w;
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truth[index++] = h;
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}
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}
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#define NUMCHARS 37
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void print_letters(float *pred, int n)
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{
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int i;
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for(i = 0; i < n; ++i){
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int index = max_index(pred+i*NUMCHARS, NUMCHARS);
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printf("%c", int_to_alphanum(index));
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}
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printf("\n");
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}
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void fill_truth_captcha(char *path, int n, float *truth)
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{
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char *begin = strrchr(path, '/');
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++begin;
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int i;
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for(i = 0; i < strlen(begin) && i < n && begin[i] != '.'; ++i){
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int index = alphanum_to_int(begin[i]);
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if(index > 35) printf("Bad %c\n", begin[i]);
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truth[i*NUMCHARS+index] = 1;
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}
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for(;i < n; ++i){
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truth[i*NUMCHARS + NUMCHARS-1] = 1;
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}
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}
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data load_data_captcha(char **paths, int n, int m, int k, int w, int h)
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{
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if(m) paths = get_random_paths(paths, n, m);
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data d;
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d.shallow = 0;
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d.X = load_image_paths(paths, n, w, h);
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d.y = make_matrix(n, k*NUMCHARS);
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int i;
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for(i = 0; i < n; ++i){
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fill_truth_captcha(paths[i], k, d.y.vals[i]);
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}
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if(m) free(paths);
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return d;
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}
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data load_data_captcha_encode(char **paths, int n, int m, int w, int h)
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{
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if(m) paths = get_random_paths(paths, n, m);
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data d;
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d.shallow = 0;
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d.X = load_image_paths(paths, n, w, h);
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d.X.cols = 17100;
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d.y = d.X;
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if(m) free(paths);
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return d;
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}
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void fill_truth(char *path, char **labels, int k, float *truth)
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{
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int i;
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memset(truth, 0, k*sizeof(float));
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int count = 0;
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for(i = 0; i < k; ++i){
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if(strstr(path, labels[i])){
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truth[i] = 1;
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++count;
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}
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}
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if(count != 1) printf("Too many or too few labels: %d, %s\n", count, path);
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}
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matrix load_labels_paths(char **paths, int n, char **labels, int k)
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{
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matrix y = make_matrix(n, k);
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int i;
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for(i = 0; i < n && labels; ++i){
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fill_truth(paths[i], labels, k, y.vals[i]);
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}
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return y;
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}
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char **get_labels(char *filename)
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{
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list *plist = get_paths(filename);
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char **labels = (char **)list_to_array(plist);
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free_list(plist);
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return labels;
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}
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void free_data(data d)
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{
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if(!d.shallow){
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free_matrix(d.X);
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free_matrix(d.y);
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}else{
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free(d.X.vals);
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free(d.y.vals);
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}
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}
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data load_data_localization(int n, char **paths, int m, int classes, int w, int h)
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{
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char **random_paths = get_random_paths(paths, n, m);
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int i;
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data d;
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d.shallow = 0;
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d.X.rows = n;
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d.X.vals = calloc(d.X.rows, sizeof(float*));
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d.X.cols = h*w*3;
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int k = (4*classes);
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d.y = make_matrix(n, k);
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for(i = 0; i < n; ++i){
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image orig = load_image_color(random_paths[i], 0, 0);
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int oh = orig.h;
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int ow = orig.w;
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int dw = 32;
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int dh = 32;
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int pleft = (rand_uniform() * dw);
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int pright = (rand_uniform() * dw);
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int ptop = (rand_uniform() * dh);
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int pbot = (rand_uniform() * dh);
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int swidth = ow - pleft - pright;
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int sheight = oh - ptop - pbot;
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float sx = (float)swidth / ow;
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float sy = (float)sheight / oh;
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int flip = rand_r(&data_seed)%2;
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image cropped = crop_image(orig, pleft, ptop, swidth, sheight);
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float dx = ((float)pleft/ow)/sx;
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float dy = ((float)ptop /oh)/sy;
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free_image(orig);
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image sized = resize_image(cropped, w, h);
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free_image(cropped);
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if(flip) flip_image(sized);
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d.X.vals[i] = sized.data;
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fill_truth_localization(random_paths[i], d.y.vals[i], classes, flip, dx, dy, 1./sx, 1./sy);
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}
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free(random_paths);
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return d;
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}
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data load_data_detection_jitter_random(int n, char **paths, int m, int classes, int w, int h, int num_boxes, int background)
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{
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char **random_paths = get_random_paths(paths, n, m);
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int i;
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data d;
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d.shallow = 0;
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d.X.rows = n;
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d.X.vals = calloc(d.X.rows, sizeof(float*));
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d.X.cols = h*w*3;
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int k = num_boxes*num_boxes*(4+classes+background);
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d.y = make_matrix(n, k);
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for(i = 0; i < n; ++i){
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image orig = load_image_color(random_paths[i], 0, 0);
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int oh = orig.h;
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int ow = orig.w;
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int dw = ow/10;
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int dh = oh/10;
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int pleft = (rand_uniform() * 2*dw - dw);
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int pright = (rand_uniform() * 2*dw - dw);
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int ptop = (rand_uniform() * 2*dh - dh);
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int pbot = (rand_uniform() * 2*dh - dh);
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int swidth = ow - pleft - pright;
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int sheight = oh - ptop - pbot;
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float sx = (float)swidth / ow;
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float sy = (float)sheight / oh;
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/*
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float angle = rand_uniform()*.1 - .05;
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image rot = rotate_image(orig, angle);
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free_image(orig);
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orig = rot;
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*/
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int flip = rand_r(&data_seed)%2;
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image cropped = crop_image(orig, pleft, ptop, swidth, sheight);
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float dx = ((float)pleft/ow)/sx;
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float dy = ((float)ptop /oh)/sy;
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free_image(orig);
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image sized = resize_image(cropped, w, h);
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free_image(cropped);
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if(flip) flip_image(sized);
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d.X.vals[i] = sized.data;
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fill_truth_detection(random_paths[i], d.y.vals[i], classes, num_boxes, flip, background, dx, dy, 1./sx, 1./sy);
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}
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free(random_paths);
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return d;
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}
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void *load_image_in_thread(void *ptr)
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{
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load_args a = *(load_args*)ptr;
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free(ptr);
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*(a.im) = load_image_color(a.path, 0, 0);
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*(a.resized) = resize_image(*(a.im), a.w, a.h);
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return 0;
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}
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pthread_t load_image_thread(char *path, image *im, image *resized, int w, int h)
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{
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pthread_t thread;
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struct load_args *args = calloc(1, sizeof(struct load_args));
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args->path = path;
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args->w = w;
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args->h = h;
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args->im = im;
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args->resized = resized;
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if(pthread_create(&thread, 0, load_image_in_thread, args)) {
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error("Thread creation failed");
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}
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return thread;
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}
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void *load_localization_thread(void *ptr)
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{
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printf("Loading data: %d\n", rand_r(&data_seed));
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struct load_args a = *(struct load_args*)ptr;
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*a.d = load_data_localization(a.n, a.paths, a.m, a.classes, a.w, a.h);
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free(ptr);
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return 0;
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}
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pthread_t load_data_localization_thread(int n, char **paths, int m, int classes, int w, int h, data *d)
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{
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pthread_t thread;
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struct load_args *args = calloc(1, sizeof(struct load_args));
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args->n = n;
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args->paths = paths;
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args->m = m;
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args->w = w;
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args->h = h;
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args->classes = classes;
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args->d = d;
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if(pthread_create(&thread, 0, load_localization_thread, args)) {
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error("Thread creation failed");
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}
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return thread;
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}
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void *load_detection_thread(void *ptr)
|
|
{
|
|
printf("Loading data: %d\n", rand_r(&data_seed));
|
|
struct load_args a = *(struct load_args*)ptr;
|
|
*a.d = load_data_detection_jitter_random(a.n, a.paths, a.m, a.classes, a.w, a.h, a.num_boxes, a.background);
|
|
free(ptr);
|
|
return 0;
|
|
}
|
|
|
|
pthread_t load_data_detection_thread(int n, char **paths, int m, int classes, int w, int h, int nh, int nw, int background, data *d)
|
|
{
|
|
pthread_t thread;
|
|
struct load_args *args = calloc(1, sizeof(struct load_args));
|
|
args->n = n;
|
|
args->paths = paths;
|
|
args->m = m;
|
|
args->h = h;
|
|
args->w = w;
|
|
args->nh = nh;
|
|
args->nw = nw;
|
|
args->num_boxes = nw;
|
|
args->classes = classes;
|
|
args->background = background;
|
|
args->d = d;
|
|
if(pthread_create(&thread, 0, load_detection_thread, args)) {
|
|
error("Thread creation failed");
|
|
}
|
|
return thread;
|
|
}
|
|
|
|
data load_data_writing(char **paths, int n, int m, int w, int h)
|
|
{
|
|
if(m) paths = get_random_paths(paths, n, m);
|
|
char **replace_paths = find_replace_paths(paths, n, ".png", "-label.png");
|
|
data d;
|
|
d.shallow = 0;
|
|
d.X = load_image_paths(paths, n, w, h);
|
|
d.y = load_image_paths_gray(replace_paths, n, w/8, h/8);
|
|
if(m) free(paths);
|
|
int i;
|
|
for(i = 0; i < n; ++i) free(replace_paths[i]);
|
|
free(replace_paths);
|
|
return d;
|
|
}
|
|
|
|
data load_data(char **paths, int n, int m, char **labels, int k, int w, int h)
|
|
{
|
|
if(m) paths = get_random_paths(paths, n, m);
|
|
data d;
|
|
d.shallow = 0;
|
|
d.X = load_image_paths(paths, n, w, h);
|
|
d.y = load_labels_paths(paths, n, labels, k);
|
|
if(m) free(paths);
|
|
return d;
|
|
}
|
|
|
|
void *load_in_thread(void *ptr)
|
|
{
|
|
struct load_args a = *(struct load_args*)ptr;
|
|
*a.d = load_data(a.paths, a.n, a.m, a.labels, a.k, a.w, a.h);
|
|
free(ptr);
|
|
return 0;
|
|
}
|
|
|
|
pthread_t load_data_thread(char **paths, int n, int m, char **labels, int k, int w, int h, data *d)
|
|
{
|
|
pthread_t thread;
|
|
struct load_args *args = calloc(1, sizeof(struct load_args));
|
|
args->n = n;
|
|
args->paths = paths;
|
|
args->m = m;
|
|
args->labels = labels;
|
|
args->k = k;
|
|
args->h = h;
|
|
args->w = w;
|
|
args->d = d;
|
|
if(pthread_create(&thread, 0, load_in_thread, args)) {
|
|
error("Thread creation failed");
|
|
}
|
|
return thread;
|
|
}
|
|
|
|
matrix concat_matrix(matrix m1, matrix m2)
|
|
{
|
|
int i, count = 0;
|
|
matrix m;
|
|
m.cols = m1.cols;
|
|
m.rows = m1.rows+m2.rows;
|
|
m.vals = calloc(m1.rows + m2.rows, sizeof(float*));
|
|
for(i = 0; i < m1.rows; ++i){
|
|
m.vals[count++] = m1.vals[i];
|
|
}
|
|
for(i = 0; i < m2.rows; ++i){
|
|
m.vals[count++] = m2.vals[i];
|
|
}
|
|
return m;
|
|
}
|
|
|
|
data concat_data(data d1, data d2)
|
|
{
|
|
data d;
|
|
d.shallow = 1;
|
|
d.X = concat_matrix(d1.X, d2.X);
|
|
d.y = concat_matrix(d1.y, d2.y);
|
|
return d;
|
|
}
|
|
|
|
data load_categorical_data_csv(char *filename, int target, int k)
|
|
{
|
|
data d;
|
|
d.shallow = 0;
|
|
matrix X = csv_to_matrix(filename);
|
|
float *truth_1d = pop_column(&X, target);
|
|
float **truth = one_hot_encode(truth_1d, X.rows, k);
|
|
matrix y;
|
|
y.rows = X.rows;
|
|
y.cols = k;
|
|
y.vals = truth;
|
|
d.X = X;
|
|
d.y = y;
|
|
free(truth_1d);
|
|
return d;
|
|
}
|
|
|
|
data load_cifar10_data(char *filename)
|
|
{
|
|
data d;
|
|
d.shallow = 0;
|
|
long i,j;
|
|
matrix X = make_matrix(10000, 3072);
|
|
matrix y = make_matrix(10000, 10);
|
|
d.X = X;
|
|
d.y = y;
|
|
|
|
FILE *fp = fopen(filename, "rb");
|
|
if(!fp) file_error(filename);
|
|
for(i = 0; i < 10000; ++i){
|
|
unsigned char bytes[3073];
|
|
fread(bytes, 1, 3073, fp);
|
|
int class = bytes[0];
|
|
y.vals[i][class] = 1;
|
|
for(j = 0; j < X.cols; ++j){
|
|
X.vals[i][j] = (double)bytes[j+1];
|
|
}
|
|
}
|
|
translate_data_rows(d, -128);
|
|
scale_data_rows(d, 1./128);
|
|
//normalize_data_rows(d);
|
|
fclose(fp);
|
|
return d;
|
|
}
|
|
|
|
void get_random_batch(data d, int n, float *X, float *y)
|
|
{
|
|
int j;
|
|
for(j = 0; j < n; ++j){
|
|
int index = rand_r(&data_seed)%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));
|
|
}
|
|
}
|
|
|
|
void get_next_batch(data d, int n, int offset, float *X, float *y)
|
|
{
|
|
int j;
|
|
for(j = 0; j < n; ++j){
|
|
int index = offset + j;
|
|
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));
|
|
}
|
|
}
|
|
|
|
|
|
data load_all_cifar10()
|
|
{
|
|
data d;
|
|
d.shallow = 0;
|
|
int i,j,b;
|
|
matrix X = make_matrix(50000, 3072);
|
|
matrix y = make_matrix(50000, 10);
|
|
d.X = X;
|
|
d.y = y;
|
|
|
|
|
|
for(b = 0; b < 5; ++b){
|
|
char buff[256];
|
|
sprintf(buff, "data/cifar10/data_batch_%d.bin", b+1);
|
|
FILE *fp = fopen(buff, "rb");
|
|
if(!fp) file_error(buff);
|
|
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;
|
|
for(j = 0; j < X.cols; ++j){
|
|
X.vals[i+b*10000][j] = (double)bytes[j+1];
|
|
}
|
|
}
|
|
fclose(fp);
|
|
}
|
|
//normalize_data_rows(d);
|
|
translate_data_rows(d, -128);
|
|
scale_data_rows(d, 1./128);
|
|
return d;
|
|
}
|
|
|
|
void randomize_data(data d)
|
|
{
|
|
int i;
|
|
for(i = d.X.rows-1; i > 0; --i){
|
|
int index = rand_r(&data_seed)%i;
|
|
float *swap = d.X.vals[index];
|
|
d.X.vals[index] = d.X.vals[i];
|
|
d.X.vals[i] = swap;
|
|
|
|
swap = d.y.vals[index];
|
|
d.y.vals[index] = d.y.vals[i];
|
|
d.y.vals[i] = swap;
|
|
}
|
|
}
|
|
|
|
void scale_data_rows(data d, float s)
|
|
{
|
|
int i;
|
|
for(i = 0; i < d.X.rows; ++i){
|
|
scale_array(d.X.vals[i], d.X.cols, s);
|
|
}
|
|
}
|
|
|
|
void translate_data_rows(data d, float s)
|
|
{
|
|
int i;
|
|
for(i = 0; i < d.X.rows; ++i){
|
|
translate_array(d.X.vals[i], d.X.cols, s);
|
|
}
|
|
}
|
|
|
|
void normalize_data_rows(data d)
|
|
{
|
|
int i;
|
|
for(i = 0; i < d.X.rows; ++i){
|
|
normalize_array(d.X.vals[i], d.X.cols);
|
|
}
|
|
}
|
|
|
|
data *split_data(data d, int part, int total)
|
|
{
|
|
data *split = calloc(2, sizeof(data));
|
|
int i;
|
|
int start = part*d.X.rows/total;
|
|
int end = (part+1)*d.X.rows/total;
|
|
data train;
|
|
data test;
|
|
train.shallow = test.shallow = 1;
|
|
|
|
test.X.rows = test.y.rows = end-start;
|
|
train.X.rows = train.y.rows = d.X.rows - (end-start);
|
|
train.X.cols = test.X.cols = d.X.cols;
|
|
train.y.cols = test.y.cols = d.y.cols;
|
|
|
|
train.X.vals = calloc(train.X.rows, sizeof(float*));
|
|
test.X.vals = calloc(test.X.rows, sizeof(float*));
|
|
train.y.vals = calloc(train.y.rows, sizeof(float*));
|
|
test.y.vals = calloc(test.y.rows, sizeof(float*));
|
|
|
|
for(i = 0; i < start; ++i){
|
|
train.X.vals[i] = d.X.vals[i];
|
|
train.y.vals[i] = d.y.vals[i];
|
|
}
|
|
for(i = start; i < end; ++i){
|
|
test.X.vals[i-start] = d.X.vals[i];
|
|
test.y.vals[i-start] = d.y.vals[i];
|
|
}
|
|
for(i = end; i < d.X.rows; ++i){
|
|
train.X.vals[i-(end-start)] = d.X.vals[i];
|
|
train.y.vals[i-(end-start)] = d.y.vals[i];
|
|
}
|
|
split[0] = train;
|
|
split[1] = test;
|
|
return split;
|
|
}
|
|
|