11 static inline float distance_from_edge(
int x,
int max)
15 dx = (max/2) + 1 - dx;
17 float dist = (float)dx/max;
18 if (dist > 1) dist = 1;
27 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);
28 data load_data_tag(
char **paths,
int n,
int m,
int k,
int min,
int max,
int size,
float angle,
float aspect,
float hue,
float saturation,
float exposure);
29 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 center);
31 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,
int center);
32 data load_data_regression(
char **paths,
int n,
int m,
int classes,
int min,
int max,
int size,
float angle,
float aspect,
float hue,
float saturation,
float exposure);
48 void fill_truth(
char *path,
char **labels,
int k,
float *truth);
void scale_data_rows(data d, float s)
void get_random_batch(data d, int n, float *X, float *y)
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, int center)
data load_categorical_data_csv(char *filename, int target, int k)
void randomize_data(data d)
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 center)
data concat_datas(data *d, int n)
void fill_truth(char *path, char **labels, int k, float *truth)
data load_data_super(char **paths, int n, int m, int w, int h, int scale)
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)
void load_data_blocking(load_args args)
data get_data_part(data d, int part, int total)
data * split_data(data d, int part, int total)
data get_random_data(data d, int num)
data load_go(char *filename)
void translate_data_rows(data d, float s)
data load_data_regression(char **paths, int n, int m, int classes, int min, int max, int size, float angle, float aspect, float hue, float saturation, float exposure)
data load_data_captcha(char **paths, int n, int m, int k, int w, int h)
data load_data_tag(char **paths, int n, int m, int k, int min, int max, int size, float angle, float aspect, float hue, float saturation, float exposure)
void normalize_data_rows(data d)
void print_letters(float *pred, int n)
data load_data_writing(char **paths, int n, int m, int w, int h, int out_w, int out_h)
data load_data_captcha_encode(char **paths, int n, int m, int w, int h)