| | |
| | | return lines; |
| | | } |
| | | |
| | | char **get_random_paths_indexes(char **paths, int n, int m, int *indexes) |
| | | { |
| | | char **random_paths = calloc(n, sizeof(char*)); |
| | | int i; |
| | | for(i = 0; i < n; ++i){ |
| | | int index = rand_r(&data_seed)%m; |
| | | indexes[i] = index; |
| | | random_paths[i] = paths[index]; |
| | | if(i == 0) printf("%s\n", paths[index]); |
| | | } |
| | | return random_paths; |
| | | } |
| | | |
| | | char **get_random_paths(char **paths, int n, int m) |
| | | { |
| | | char **random_paths = calloc(n, sizeof(char*)); |
| | |
| | | data load_data_captcha(char **paths, int n, int m, int k, int w, int h) |
| | | { |
| | | if(m) paths = get_random_paths(paths, n, m); |
| | | data d; |
| | | data d = {0}; |
| | | d.shallow = 0; |
| | | d.X = load_image_paths(paths, n, w, h); |
| | | d.y = make_matrix(n, k*NUMCHARS); |
| | |
| | | data load_data_captcha_encode(char **paths, int n, int m, int w, int h) |
| | | { |
| | | if(m) paths = get_random_paths(paths, n, m); |
| | | data d; |
| | | data d = {0}; |
| | | d.shallow = 0; |
| | | d.X = load_image_paths(paths, n, w, h); |
| | | d.X.cols = 17100; |
| | |
| | | |
| | | void free_data(data d) |
| | | { |
| | | if(d.indexes){ |
| | | free(d.indexes); |
| | | } |
| | | if(!d.shallow){ |
| | | free_matrix(d.X); |
| | | free_matrix(d.y); |
| | |
| | | { |
| | | char **random_paths = get_random_paths(paths, n, m); |
| | | int i; |
| | | data d; |
| | | data d = {0}; |
| | | d.shallow = 0; |
| | | |
| | | d.X.rows = n; |
| | |
| | | { |
| | | if(m) paths = get_random_paths(paths, 2*n, m); |
| | | int i,j; |
| | | data d; |
| | | data d = {0}; |
| | | d.shallow = 0; |
| | | |
| | | d.X.rows = n; |
| | |
| | | int h = orig.h; |
| | | int w = orig.w; |
| | | |
| | | data d; |
| | | data d = {0}; |
| | | d.shallow = 0; |
| | | d.w = w; |
| | | d.h = h; |
| | |
| | | { |
| | | char **random_paths = get_random_paths(paths, n, m); |
| | | int i; |
| | | data d; |
| | | data d = {0}; |
| | | d.shallow = 0; |
| | | |
| | | d.X.rows = n; |
| | |
| | | *a.d = load_data(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); |
| | | } else if (a.type == STUDY_DATA){ |
| | | *a.d = load_data_study(a.paths, a.n, a.m, a.labels, a.classes, a.min, a.max, a.size); |
| | | } else if (a.type == DETECTION_DATA){ |
| | | *a.d = load_data_detection(a.n, a.paths, a.m, a.classes, a.w, a.h, a.num_boxes, a.background); |
| | | } else if (a.type == WRITING_DATA){ |
| | |
| | | { |
| | | if(m) paths = get_random_paths(paths, n, m); |
| | | char **replace_paths = find_replace_paths(paths, n, ".png", "-label.png"); |
| | | data d; |
| | | data d = {0}; |
| | | d.shallow = 0; |
| | | d.X = load_image_paths(paths, n, w, h); |
| | | d.y = load_image_paths_gray(replace_paths, n, out_w, out_h); |
| | |
| | | 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; |
| | | data d = {0}; |
| | | d.shallow = 0; |
| | | d.X = load_image_paths(paths, n, w, h); |
| | | d.y = load_labels_paths(paths, n, labels, k); |
| | |
| | | return d; |
| | | } |
| | | |
| | | data load_data_study(char **paths, int n, int m, char **labels, int k, int min, int max, int size) |
| | | { |
| | | 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_cropped_paths(paths, n, min, max, size); |
| | | d.y = load_labels_paths(paths, n, labels, k); |
| | | if(m) free(paths); |
| | | return d; |
| | | } |
| | | |
| | | data load_data_augment(char **paths, int n, int m, char **labels, int k, int min, int max, int size) |
| | | { |
| | | if(m) paths = get_random_paths(paths, n, m); |
| | | data d; |
| | | data d = {0}; |
| | | d.shallow = 0; |
| | | d.X = load_image_cropped_paths(paths, n, min, max, size); |
| | | d.y = load_labels_paths(paths, n, labels, k); |
| | |
| | | |
| | | data concat_data(data d1, data d2) |
| | | { |
| | | data d; |
| | | data d = {0}; |
| | | d.shallow = 1; |
| | | d.X = concat_matrix(d1.X, d2.X); |
| | | d.y = concat_matrix(d1.y, d2.y); |
| | |
| | | |
| | | data load_categorical_data_csv(char *filename, int target, int k) |
| | | { |
| | | data d; |
| | | data d = {0}; |
| | | d.shallow = 0; |
| | | matrix X = csv_to_matrix(filename); |
| | | float *truth_1d = pop_column(&X, target); |
| | |
| | | |
| | | data load_cifar10_data(char *filename) |
| | | { |
| | | data d; |
| | | data d = {0}; |
| | | d.shallow = 0; |
| | | long i,j; |
| | | matrix X = make_matrix(10000, 3072); |
| | |
| | | |
| | | data load_all_cifar10() |
| | | { |
| | | data d; |
| | | data d = {0}; |
| | | d.shallow = 0; |
| | | int i,j,b; |
| | | matrix X = make_matrix(50000, 3072); |
| | |
| | | //normalize_data_rows(d); |
| | | //translate_data_rows(d, -128); |
| | | scale_data_rows(d, 1./255); |
| | | // smooth_data(d); |
| | | smooth_data(d); |
| | | return d; |
| | | } |
| | | |
| | |
| | | X = resize_matrix(X, count); |
| | | y = resize_matrix(y, count); |
| | | |
| | | data d; |
| | | data d = {0}; |
| | | d.shallow = 0; |
| | | d.X = X; |
| | | d.y = y; |