From 0f1a31648c5292fa49b35eac90a2ee676d6c13e6 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Sat, 31 Jan 2015 06:05:23 +0000
Subject: [PATCH] idk, probably something changed
---
src/data.c | 479 ++++++++++++++++++++++++++++++++++++++++++++++++++---------
1 files changed, 402 insertions(+), 77 deletions(-)
diff --git a/src/data.c b/src/data.c
index 9e5791f..3a37411 100644
--- a/src/data.c
+++ b/src/data.c
@@ -1,27 +1,30 @@
#include "data.h"
-#include "list.h"
#include "utils.h"
+#include "image.h"
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
-batch make_batch(int n, int k)
-{
- batch b;
- b.n = n;
- if(k < 3) k = 1;
- b.images = calloc(n, sizeof(image));
- b.truth = calloc(n, sizeof(double *));
- int i;
- for(i =0 ; i < n; ++i) b.truth[i] = calloc(k, sizeof(double));
- return b;
-}
+struct load_args{
+ char **paths;
+ int n;
+ int m;
+ char **labels;
+ int k;
+ int h;
+ int w;
+ int nh;
+ int nw;
+ float scale;
+ data *d;
+};
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);
@@ -30,86 +33,408 @@
return lines;
}
-void fill_truth(char *path, char **labels, int k, double *truth)
+void fill_truth_detection(char *path, float *truth, int height, int width, int num_height, int num_width, float scale, int dx, int dy)
+{
+ int box_height = height/num_height;
+ int box_width = width/num_width;
+ char *labelpath = find_replace(path, "imgs", "det");
+ labelpath = find_replace(labelpath, ".JPEG", ".txt");
+ FILE *file = fopen(labelpath, "r");
+ if(!file) file_error(labelpath);
+ int x, y, h, w;
+ while(fscanf(file, "%d %d %d %d", &x, &y, &w, &h) == 4){
+ x -= dx;
+ y -= dy;
+ int i = x/box_width;
+ int j = y/box_height;
+
+ if(i < 0) i = 0;
+ if(i >= num_width) i = num_width-1;
+ if(j < 0) j = 0;
+ if(j >= num_height) j = num_height-1;
+
+ float dw = (float)(x%box_width)/box_height;
+ float dh = (float)(y%box_width)/box_width;
+ float sh = h/scale;
+ float sw = w/scale;
+ //printf("%d %d %f %f\n", i, j, dh, dw);
+ int index = (i+j*num_width)*5;
+ truth[index++] = 1;
+ truth[index++] = dh;
+ truth[index++] = dw;
+ truth[index++] = sh;
+ truth[index++] = sw;
+ }
+ fclose(file);
+}
+
+void fill_truth(char *path, char **labels, int k, float *truth)
{
int i;
- memset(truth, 0, k*sizeof(double));
+ memset(truth, 0, k*sizeof(float));
+ int count = 0;
for(i = 0; i < k; ++i){
if(strstr(path, labels[i])){
truth[i] = 1;
+ ++count;
}
}
+ if(count != 1) printf("%d, %s\n", count, path);
}
-batch load_list(list *paths, char **labels, int k)
-{
- char *path;
- batch data = make_batch(paths->size, 2);
- node *n = paths->front;
- int i;
- for(i = 0; i < data.n; ++i){
- path = (char *)n->val;
- data.images[i] = load_image(path);
- fill_truth(path, labels, k, data.truth[i]);
- n = n->next;
- }
- return data;
-}
-
-batch get_all_data(char *filename, char **labels, int k)
-{
- list *paths = get_paths(filename);
- batch b = load_list(paths, labels, k);
- free_list_contents(paths);
- free_list(paths);
- return b;
-}
-
-void free_batch(batch b)
+matrix load_image_paths(char **paths, int n, int h, int w)
{
int i;
- for(i = 0; i < b.n; ++i){
- free_image(b.images[i]);
- free(b.truth[i]);
- }
- free(b.images);
- free(b.truth);
-}
+ matrix X;
+ X.rows = n;
+ X.vals = calloc(X.rows, sizeof(float*));
+ X.cols = 0;
-batch get_batch(char *filename, int curr, int total, char **labels, int k)
-{
- list *plist = get_paths(filename);
- char **paths = (char **)list_to_array(plist);
- int i;
- int start = curr*plist->size/total;
- int end = (curr+1)*plist->size/total;
- batch b = make_batch(end-start, 2);
- for(i = start; i < end; ++i){
- b.images[i-start] = load_image(paths[i]);
- fill_truth(paths[i], labels, k, b.truth[i-start]);
- }
- free_list_contents(plist);
- free_list(plist);
- free(paths);
- return b;
-}
-
-batch random_batch(char *filename, int n, char **labels, int k)
-{
- list *plist = get_paths(filename);
- char **paths = (char **)list_to_array(plist);
- int i;
- batch b = make_batch(n, 2);
for(i = 0; i < n; ++i){
- int index = rand()%plist->size;
- b.images[i] = load_image(paths[index]);
- //scale_image(b.images[i], 1./255.);
- z_normalize_image(b.images[i]);
- fill_truth(paths[index], labels, k, b.truth[i]);
- //print_image(b.images[i]);
+ image im = load_image_color(paths[i], h, w);
+ X.vals[i] = im.data;
+ X.cols = im.h*im.w*im.c;
}
+ return X;
+}
+
+char **get_random_paths(char **paths, int n, int m)
+{
+ char **random_paths = calloc(n, sizeof(char*));
+ int i;
+ for(i = 0; i < n; ++i){
+ int index = rand()%m;
+ random_paths[i] = paths[index];
+ if(i == 0) printf("%s\n", paths[index]);
+ }
+ return random_paths;
+}
+
+matrix load_labels_paths(char **paths, int n, char **labels, int k)
+{
+ matrix y = make_matrix(n, k);
+ int i;
+ for(i = 0; i < n && labels; ++i){
+ fill_truth(paths[i], labels, k, y.vals[i]);
+ }
+ return y;
+}
+
+matrix load_labels_detection(char **paths, int n, int height, int width, int num_height, int num_width, float scale)
+{
+ int k = num_height*num_width*5;
+ matrix y = make_matrix(n, k);
+ int i;
+ for(i = 0; i < n; ++i){
+ fill_truth_detection(paths[i], y.vals[i], height, width, num_height, num_width, scale,0,0);
+ }
+ return y;
+}
+
+data load_data_image_pathfile(char *filename, char **labels, int k, int h, int w)
+{
+ list *plist = get_paths(filename);
+ char **paths = (char **)list_to_array(plist);
+ int n = plist->size;
+ data d;
+ d.shallow = 0;
+ d.X = load_image_paths(paths, n, h, w);
+ d.y = load_labels_paths(paths, n, labels, k);
free_list_contents(plist);
free_list(plist);
free(paths);
- return b;
+ return d;
}
+
+char **get_labels(char *filename)
+{
+ list *plist = get_paths(filename);
+ char **labels = (char **)list_to_array(plist);
+ free_list(plist);
+ return labels;
+}
+
+void free_data(data d)
+{
+ if(!d.shallow){
+ free_matrix(d.X);
+ free_matrix(d.y);
+ }else{
+ free(d.X.vals);
+ free(d.y.vals);
+ }
+}
+
+data load_data_detection_jitter_random(int n, char **paths, int m, int h, int w, int nh, int nw, float scale)
+{
+ char **random_paths = get_random_paths(paths, n, m);
+ int i;
+ data d;
+ d.shallow = 0;
+ d.X = load_image_paths(random_paths, n, h, w);
+ int k = nh*nw*5;
+ d.y = make_matrix(n, k);
+ for(i = 0; i < n; ++i){
+ int dx = rand()%32;
+ int dy = rand()%32;
+ fill_truth_detection(random_paths[i], d.y.vals[i], 224, 224, nh, nw, scale, dx, dy);
+ image a = float_to_image(h, w, 3, d.X.vals[i]);
+ jitter_image(a,224,224,dy,dx);
+ }
+ d.X.cols = 224*224*3;
+ free(random_paths);
+ return d;
+}
+
+void *load_detection_thread(void *ptr)
+{
+ struct load_args a = *(struct load_args*)ptr;
+ *a.d = load_data_detection_jitter_random(a.n, a.paths, a.m, a.h, a.w, a.nh, a.nw, a.scale);
+ free(ptr);
+ return 0;
+}
+
+pthread_t load_data_detection_thread(int n, char **paths, int m, int h, int w, int nh, int nw, float scale, 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->scale = scale;
+ args->d = d;
+ if(pthread_create(&thread, 0, load_detection_thread, args)) {
+ error("Thread creation failed");
+ }
+ return thread;
+}
+
+data load_data_detection_random(int n, char **paths, int m, int h, int w, int nh, int nw, float scale)
+{
+ char **random_paths = get_random_paths(paths, n, m);
+ data d;
+ d.shallow = 0;
+ d.X = load_image_paths(random_paths, n, h, w);
+ d.y = load_labels_detection(random_paths, n, h, w, nh, nw, scale);
+ free(random_paths);
+ return d;
+}
+
+data load_data(char **paths, int n, int m, char **labels, int k, int h, int w)
+{
+ if(m) paths = get_random_paths(paths, n, m);
+ data d;
+ d.shallow = 0;
+ d.X = load_image_paths(paths, n, h, w);
+ 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.h, a.w);
+ translate_data_rows(*a.d, -128);
+ scale_data_rows(*a.d, 1./128);
+ free(ptr);
+ return 0;
+}
+
+pthread_t load_data_thread(char **paths, int n, int m, char **labels, int k, int h, int w, 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;
+}
+
+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, -144);
+ 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()%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, -144);
+ 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()%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;
+}
+
--
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