| | |
| | | #include "data.h"
|
| | | #include "utils.h"
|
| | | #include "image.h"
|
| | | #include "dark_cuda.h"
|
| | | #include "box.h"
|
| | | #include "http_stream.h"
|
| | |
|
| | | #include <stdio.h>
|
| | | #include <stdlib.h>
|
| | | #include <string.h>
|
| | |
|
| | | extern int check_mistakes;
|
| | |
|
| | | #define NUMCHARS 37
|
| | |
|
| | | 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 = random_gen()%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_sequential_paths(char **paths, int n, int m, int mini_batch, int augment_speed)
|
| | | {
|
| | | int speed = rand_int(1, augment_speed);
|
| | | if (speed < 1) speed = 1;
|
| | | char** sequentia_paths = (char**)xcalloc(n, sizeof(char*));
|
| | | int i;
|
| | | pthread_mutex_lock(&mutex);
|
| | | //printf("n = %d, mini_batch = %d \n", n, mini_batch);
|
| | | unsigned int *start_time_indexes = (unsigned int *)xcalloc(mini_batch, sizeof(unsigned int));
|
| | | for (i = 0; i < mini_batch; ++i) {
|
| | | start_time_indexes[i] = random_gen() % m;
|
| | | //printf(" start_time_indexes[i] = %u, ", start_time_indexes[i]);
|
| | | }
|
| | |
|
| | | for (i = 0; i < n; ++i) {
|
| | | do {
|
| | | int time_line_index = i % mini_batch;
|
| | | unsigned int index = start_time_indexes[time_line_index] % m;
|
| | | start_time_indexes[time_line_index] += speed;
|
| | |
|
| | | //int index = random_gen() % m;
|
| | | sequentia_paths[i] = paths[index];
|
| | | //if(i == 0) printf("%s\n", paths[index]);
|
| | | //printf(" index = %u - grp: %s \n", index, paths[index]);
|
| | | if (strlen(sequentia_paths[i]) <= 4) printf(" Very small path to the image: %s \n", sequentia_paths[i]);
|
| | | } while (strlen(sequentia_paths[i]) == 0);
|
| | | }
|
| | | free(start_time_indexes);
|
| | | pthread_mutex_unlock(&mutex);
|
| | | return sequentia_paths;
|
| | | }
|
| | |
|
| | | char **get_random_paths(char **paths, int n, int m)
|
| | | {
|
| | | char** random_paths = (char**)xcalloc(n, sizeof(char*));
|
| | | int i;
|
| | | pthread_mutex_lock(&mutex);
|
| | | //printf("n = %d \n", n);
|
| | | for(i = 0; i < n; ++i){
|
| | | do {
|
| | | int index = random_gen() % m;
|
| | | random_paths[i] = paths[index];
|
| | | //if(i == 0) printf("%s\n", paths[index]);
|
| | | //printf("grp: %s\n", paths[index]);
|
| | | if (strlen(random_paths[i]) <= 4) printf(" Very small path to the image: %s \n", random_paths[i]);
|
| | | } while (strlen(random_paths[i]) == 0);
|
| | | }
|
| | | pthread_mutex_unlock(&mutex);
|
| | | return random_paths;
|
| | | }
|
| | |
|
| | | char **find_replace_paths(char **paths, int n, char *find, char *replace)
|
| | | {
|
| | | char** replace_paths = (char**)xcalloc(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 = (float**)xcalloc(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 = (float**)xcalloc(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 use_flip, int min, int max, int w, int h, float angle, float aspect, float hue, float saturation, float exposure, int dontuse_opencv)
|
| | | {
|
| | | int i;
|
| | | matrix X;
|
| | | X.rows = n;
|
| | | X.vals = (float**)xcalloc(X.rows, sizeof(float*));
|
| | | X.cols = 0;
|
| | |
|
| | | for(i = 0; i < n; ++i){
|
| | | int size = w > h ? w : h;
|
| | | image im;
|
| | | if(dontuse_opencv) im = load_image_stb_resize(paths[i], 0, 0, 3);
|
| | | else im = load_image_color(paths[i], 0, 0);
|
| | |
|
| | | image crop = random_augment_image(im, angle, aspect, min, max, size);
|
| | | int flip = use_flip ? random_gen() % 2 : 0;
|
| | | if (flip)
|
| | | flip_image(crop);
|
| | | random_distort_image(crop, hue, saturation, exposure);
|
| | |
|
| | | image sized = resize_image(crop, w, h);
|
| | |
|
| | | //show_image(im, "orig");
|
| | | //show_image(sized, "sized");
|
| | | //show_image(sized, paths[i]);
|
| | | //wait_until_press_key_cv();
|
| | | //printf("w = %d, h = %d \n", sized.w, sized.h);
|
| | |
|
| | | free_image(im);
|
| | | free_image(crop);
|
| | | X.vals[i] = sized.data;
|
| | | X.cols = sized.h*sized.w*sized.c;
|
| | | }
|
| | | return X;
|
| | | }
|
| | |
|
| | |
|
| | | box_label *read_boxes(char *filename, int *n)
|
| | | {
|
| | | box_label* boxes = (box_label*)xcalloc(1, sizeof(box_label));
|
| | | FILE *file = fopen(filename, "r");
|
| | | if (!file) {
|
| | | printf("Can't open label file. (This can be normal only if you use MSCOCO): %s \n", filename);
|
| | | //file_error(filename);
|
| | | FILE* fw = fopen("bad.list", "a");
|
| | | fwrite(filename, sizeof(char), strlen(filename), fw);
|
| | | char *new_line = "\n";
|
| | | fwrite(new_line, sizeof(char), strlen(new_line), fw);
|
| | | fclose(fw);
|
| | | if (check_mistakes) {
|
| | | printf("\n Error in read_boxes() \n");
|
| | | getchar();
|
| | | }
|
| | |
|
| | | *n = 0;
|
| | | return boxes;
|
| | | }
|
| | | 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 = (box_label*)xrealloc(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 = random_gen()%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;
|
| | | }
|
| | | if ((boxes[i].x + boxes[i].w / 2) < 0 || (boxes[i].y + boxes[i].h / 2) < 0 ||
|
| | | (boxes[i].x - boxes[i].w / 2) > 1 || (boxes[i].y - boxes[i].h / 2) > 1)
|
| | | {
|
| | | 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];
|
| | | replace_image_to_label(path, 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];
|
| | | replace_image_to_label(path, 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 < .001 || h < .001) 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;
|
| | | truth[index++] = 1;
|
| | |
|
| | | if (id < classes) truth[index+id] = 1;
|
| | | index += classes;
|
| | |
|
| | | truth[index++] = x;
|
| | | truth[index++] = y;
|
| | | truth[index++] = w;
|
| | | truth[index++] = h;
|
| | | }
|
| | | free(boxes);
|
| | | }
|
| | |
|
| | | int fill_truth_detection(const char *path, int num_boxes, float *truth, int classes, int flip, float dx, float dy, float sx, float sy,
|
| | | int net_w, int net_h)
|
| | | {
|
| | | char labelpath[4096];
|
| | | replace_image_to_label(path, labelpath);
|
| | |
|
| | | int count = 0;
|
| | | int i;
|
| | | box_label *boxes = read_boxes(labelpath, &count);
|
| | | int min_w_h = 0;
|
| | | float lowest_w = 1.F / net_w;
|
| | | float lowest_h = 1.F / net_h;
|
| | | randomize_boxes(boxes, count);
|
| | | correct_boxes(boxes, count, dx, dy, sx, sy, flip);
|
| | | if (count > num_boxes) count = num_boxes;
|
| | | float x, y, w, h;
|
| | | int id;
|
| | | int sub = 0;
|
| | |
|
| | | 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;
|
| | |
|
| | | // not detect small objects
|
| | | //if ((w < 0.001F || h < 0.001F)) continue;
|
| | | // if truth (box for object) is smaller than 1x1 pix
|
| | | char buff[256];
|
| | | if (id >= classes) {
|
| | | printf("\n Wrong annotation: class_id = %d. But class_id should be [from 0 to %d], file: %s \n", id, (classes-1), labelpath);
|
| | | sprintf(buff, "echo %s \"Wrong annotation: class_id = %d. But class_id should be [from 0 to %d]\" >> bad_label.list", labelpath, id, (classes-1));
|
| | | system(buff);
|
| | | if (check_mistakes) getchar();
|
| | | ++sub;
|
| | | continue;
|
| | | }
|
| | | if ((w < lowest_w || h < lowest_h)) {
|
| | | //sprintf(buff, "echo %s \"Very small object: w < lowest_w OR h < lowest_h\" >> bad_label.list", labelpath);
|
| | | //system(buff);
|
| | | ++sub;
|
| | | continue;
|
| | | }
|
| | | if (x == 999999 || y == 999999) {
|
| | | printf("\n Wrong annotation: x = 0, y = 0, < 0 or > 1, file: %s \n", labelpath);
|
| | | sprintf(buff, "echo %s \"Wrong annotation: x = 0 or y = 0\" >> bad_label.list", labelpath);
|
| | | system(buff);
|
| | | ++sub;
|
| | | if (check_mistakes) getchar();
|
| | | continue;
|
| | | }
|
| | | if (x <= 0 || x > 1 || y <= 0 || y > 1) {
|
| | | printf("\n Wrong annotation: x = %f, y = %f, file: %s \n", x, y, labelpath);
|
| | | sprintf(buff, "echo %s \"Wrong annotation: x = %f, y = %f\" >> bad_label.list", labelpath, x, y);
|
| | | system(buff);
|
| | | ++sub;
|
| | | if (check_mistakes) getchar();
|
| | | continue;
|
| | | }
|
| | | if (w > 1) {
|
| | | printf("\n Wrong annotation: w = %f, file: %s \n", w, labelpath);
|
| | | sprintf(buff, "echo %s \"Wrong annotation: w = %f\" >> bad_label.list", labelpath, w);
|
| | | system(buff);
|
| | | w = 1;
|
| | | if (check_mistakes) getchar();
|
| | | }
|
| | | if (h > 1) {
|
| | | printf("\n Wrong annotation: h = %f, file: %s \n", h, labelpath);
|
| | | sprintf(buff, "echo %s \"Wrong annotation: h = %f\" >> bad_label.list", labelpath, h);
|
| | | system(buff);
|
| | | h = 1;
|
| | | if (check_mistakes) getchar();
|
| | | }
|
| | | if (x == 0) x += lowest_w;
|
| | | if (y == 0) y += lowest_h;
|
| | |
|
| | | truth[(i-sub)*5+0] = x;
|
| | | truth[(i-sub)*5+1] = y;
|
| | | truth[(i-sub)*5+2] = w;
|
| | | truth[(i-sub)*5+3] = h;
|
| | | truth[(i-sub)*5+4] = id;
|
| | |
|
| | | if (min_w_h == 0) min_w_h = w*net_w;
|
| | | if (min_w_h > w*net_w) min_w_h = w*net_w;
|
| | | if (min_w_h > h*net_h) min_w_h = h*net_h;
|
| | | }
|
| | | free(boxes);
|
| | | return min_w_h;
|
| | | }
|
| | |
|
| | |
|
| | | void print_letters(float *pred, int n)
|
| | | {
|
| | | int i;
|
| | | for(i = 0; i < n; ++i){
|
| | | int index = max_index(pred+i*NUMCHARS, NUMCHARS);
|
| | | printf("%c", int_to_alphanum(index));
|
| | | }
|
| | | printf("\n");
|
| | | }
|
| | |
|
| | | void fill_truth_captcha(char *path, int n, float *truth)
|
| | | {
|
| | | char *begin = strrchr(path, '/');
|
| | | ++begin;
|
| | | int i;
|
| | | for(i = 0; i < strlen(begin) && i < n && begin[i] != '.'; ++i){
|
| | | int index = alphanum_to_int(begin[i]);
|
| | | if(index > 35) printf("Bad %c\n", begin[i]);
|
| | | truth[i*NUMCHARS+index] = 1;
|
| | | }
|
| | | for(;i < n; ++i){
|
| | | truth[i*NUMCHARS + NUMCHARS-1] = 1;
|
| | | }
|
| | | }
|
| | |
|
| | | 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 = {0};
|
| | | d.shallow = 0;
|
| | | d.X = load_image_paths(paths, n, w, h);
|
| | | d.y = make_matrix(n, k*NUMCHARS);
|
| | | int i;
|
| | | for(i = 0; i < n; ++i){
|
| | | fill_truth_captcha(paths[i], k, d.y.vals[i]);
|
| | | }
|
| | | if(m) free(paths);
|
| | | return d;
|
| | | }
|
| | |
|
| | | 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 = {0};
|
| | | d.shallow = 0;
|
| | | d.X = load_image_paths(paths, n, w, h);
|
| | | d.X.cols = 17100;
|
| | | d.y = d.X;
|
| | | if(m) free(paths);
|
| | | return d;
|
| | | }
|
| | |
|
| | | void fill_truth(char *path, char **labels, int k, float *truth)
|
| | | {
|
| | | int i;
|
| | | 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("Too many or too few labels: %d, %s\n", count, path);
|
| | | count = 0;
|
| | | for (i = 0; i < k; ++i) {
|
| | | if (strstr(path, labels[i])) {
|
| | | printf("\t label %d: %s \n", count, labels[i]);
|
| | | count++;
|
| | | }
|
| | | }
|
| | | }
|
| | | }
|
| | |
|
| | | void fill_truth_smooth(char *path, char **labels, int k, float *truth, float label_smooth_eps)
|
| | | {
|
| | | int i;
|
| | | memset(truth, 0, k * sizeof(float));
|
| | | int count = 0;
|
| | | for (i = 0; i < k; ++i) {
|
| | | if (strstr(path, labels[i])) {
|
| | | truth[i] = (1 - label_smooth_eps);
|
| | | ++count;
|
| | | }
|
| | | else {
|
| | | truth[i] = label_smooth_eps / (k - 1);
|
| | | }
|
| | | }
|
| | | if (count != 1) {
|
| | | printf("Too many or too few labels: %d, %s\n", count, path);
|
| | | count = 0;
|
| | | for (i = 0; i < k; ++i) {
|
| | | if (strstr(path, labels[i])) {
|
| | | printf("\t label %d: %s \n", count, labels[i]);
|
| | | count++;
|
| | | }
|
| | | }
|
| | | }
|
| | | }
|
| | |
|
| | | void fill_hierarchy(float *truth, int k, tree *hierarchy)
|
| | | {
|
| | | int j;
|
| | | for(j = 0; j < k; ++j){
|
| | | if(truth[j]){
|
| | | int parent = hierarchy->parent[j];
|
| | | while(parent >= 0){
|
| | | truth[parent] = 1;
|
| | | parent = hierarchy->parent[parent];
|
| | | }
|
| | | }
|
| | | }
|
| | | int i;
|
| | | int count = 0;
|
| | | for(j = 0; j < hierarchy->groups; ++j){
|
| | | //printf("%d\n", count);
|
| | | int mask = 1;
|
| | | for(i = 0; i < hierarchy->group_size[j]; ++i){
|
| | | if(truth[count + i]){
|
| | | mask = 0;
|
| | | break;
|
| | | }
|
| | | }
|
| | | if (mask) {
|
| | | for(i = 0; i < hierarchy->group_size[j]; ++i){
|
| | | truth[count + i] = SECRET_NUM;
|
| | | }
|
| | | }
|
| | | count += hierarchy->group_size[j];
|
| | | }
|
| | | }
|
| | |
|
| | | matrix load_labels_paths(char **paths, int n, char **labels, int k, tree *hierarchy, float label_smooth_eps)
|
| | | {
|
| | | matrix y = make_matrix(n, k);
|
| | | int i;
|
| | | for(i = 0; i < n && labels; ++i){
|
| | | fill_truth_smooth(paths[i], labels, k, y.vals[i], label_smooth_eps);
|
| | | if(hierarchy){
|
| | | fill_hierarchy(y.vals[i], k, hierarchy);
|
| | | }
|
| | | }
|
| | | return y;
|
| | | }
|
| | |
|
| | | matrix load_tags_paths(char **paths, int n, int k)
|
| | | {
|
| | | matrix y = make_matrix(n, k);
|
| | | int i;
|
| | | int count = 0;
|
| | | for(i = 0; i < n; ++i){
|
| | | char label[4096];
|
| | | find_replace(paths[i], "imgs", "labels", label);
|
| | | find_replace(label, "_iconl.jpeg", ".txt", label);
|
| | | FILE *file = fopen(label, "r");
|
| | | if(!file){
|
| | | find_replace(label, "labels", "labels2", label);
|
| | | file = fopen(label, "r");
|
| | | if(!file) continue;
|
| | | }
|
| | | ++count;
|
| | | int tag;
|
| | | while(fscanf(file, "%d", &tag) == 1){
|
| | | if(tag < k){
|
| | | y.vals[i][tag] = 1;
|
| | | }
|
| | | }
|
| | | fclose(file);
|
| | | }
|
| | | printf("%d/%d\n", count, n);
|
| | | return y;
|
| | | }
|
| | |
|
| | | char **get_labels_custom(char *filename, int *size)
|
| | | {
|
| | | list *plist = get_paths(filename);
|
| | | if(size) *size = plist->size;
|
| | | char **labels = (char **)list_to_array(plist);
|
| | | free_list(plist);
|
| | | return labels;
|
| | | }
|
| | |
|
| | | char **get_labels(char *filename)
|
| | | {
|
| | | return get_labels_custom(filename, NULL);
|
| | | }
|
| | |
|
| | | 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_region(int n, char **paths, int m, int w, int h, int size, int classes, float jitter, float hue, float saturation, float exposure)
|
| | | {
|
| | | char **random_paths = get_random_paths(paths, n, m);
|
| | | int i;
|
| | | data d = {0};
|
| | | d.shallow = 0;
|
| | |
|
| | | d.X.rows = n;
|
| | | d.X.vals = (float**)xcalloc(d.X.rows, sizeof(float*));
|
| | | d.X.cols = h*w*3;
|
| | |
|
| | |
|
| | | int k = size*size*(5+classes);
|
| | | d.y = make_matrix(n, k);
|
| | | for(i = 0; i < n; ++i){
|
| | | image orig = load_image_color(random_paths[i], 0, 0);
|
| | |
|
| | | int oh = orig.h;
|
| | | int ow = orig.w;
|
| | |
|
| | | int dw = (ow*jitter);
|
| | | int dh = (oh*jitter);
|
| | |
|
| | | int pleft = rand_uniform(-dw, dw);
|
| | | int pright = rand_uniform(-dw, dw);
|
| | | int ptop = rand_uniform(-dh, dh);
|
| | | int pbot = rand_uniform(-dh, dh);
|
| | |
|
| | | int swidth = ow - pleft - pright;
|
| | | int sheight = oh - ptop - pbot;
|
| | |
|
| | | float sx = (float)swidth / ow;
|
| | | float sy = (float)sheight / oh;
|
| | |
|
| | | int flip = random_gen()%2;
|
| | | image cropped = crop_image(orig, pleft, ptop, swidth, sheight);
|
| | |
|
| | | float dx = ((float)pleft/ow)/sx;
|
| | | float dy = ((float)ptop /oh)/sy;
|
| | |
|
| | | image sized = resize_image(cropped, w, h);
|
| | | if(flip) flip_image(sized);
|
| | | random_distort_image(sized, hue, saturation, exposure);
|
| | | d.X.vals[i] = sized.data;
|
| | |
|
| | | fill_truth_region(random_paths[i], d.y.vals[i], classes, size, flip, dx, dy, 1./sx, 1./sy);
|
| | |
|
| | | free_image(orig);
|
| | | free_image(cropped);
|
| | | }
|
| | | free(random_paths);
|
| | | return d;
|
| | | }
|
| | |
|
| | | data load_data_compare(int n, char **paths, int m, int classes, int w, int h)
|
| | | {
|
| | | if(m) paths = get_random_paths(paths, 2*n, m);
|
| | | int i,j;
|
| | | data d = {0};
|
| | | d.shallow = 0;
|
| | |
|
| | | d.X.rows = n;
|
| | | d.X.vals = (float**)xcalloc(d.X.rows, sizeof(float*));
|
| | | d.X.cols = h*w*6;
|
| | |
|
| | | int k = 2*(classes);
|
| | | d.y = make_matrix(n, k);
|
| | | for(i = 0; i < n; ++i){
|
| | | image im1 = load_image_color(paths[i*2], w, h);
|
| | | image im2 = load_image_color(paths[i*2+1], w, h);
|
| | |
|
| | | d.X.vals[i] = (float*)xcalloc(d.X.cols, sizeof(float));
|
| | | memcpy(d.X.vals[i], im1.data, h*w*3*sizeof(float));
|
| | | memcpy(d.X.vals[i] + h*w*3, im2.data, h*w*3*sizeof(float));
|
| | |
|
| | | int id;
|
| | | float iou;
|
| | |
|
| | | char imlabel1[4096];
|
| | | char imlabel2[4096];
|
| | | find_replace(paths[i*2], "imgs", "labels", imlabel1);
|
| | | find_replace(imlabel1, "jpg", "txt", imlabel1);
|
| | | FILE *fp1 = fopen(imlabel1, "r");
|
| | |
|
| | | while(fscanf(fp1, "%d %f", &id, &iou) == 2){
|
| | | if (d.y.vals[i][2*id] < iou) d.y.vals[i][2*id] = iou;
|
| | | }
|
| | |
|
| | | find_replace(paths[i*2+1], "imgs", "labels", imlabel2);
|
| | | find_replace(imlabel2, "jpg", "txt", imlabel2);
|
| | | FILE *fp2 = fopen(imlabel2, "r");
|
| | |
|
| | | while(fscanf(fp2, "%d %f", &id, &iou) == 2){
|
| | | if (d.y.vals[i][2*id + 1] < iou) d.y.vals[i][2*id + 1] = iou;
|
| | | }
|
| | |
|
| | | for (j = 0; j < classes; ++j){
|
| | | if (d.y.vals[i][2*j] > .5 && d.y.vals[i][2*j+1] < .5){
|
| | | d.y.vals[i][2*j] = 1;
|
| | | d.y.vals[i][2*j+1] = 0;
|
| | | } else if (d.y.vals[i][2*j] < .5 && d.y.vals[i][2*j+1] > .5){
|
| | | d.y.vals[i][2*j] = 0;
|
| | | d.y.vals[i][2*j+1] = 1;
|
| | | } else {
|
| | | d.y.vals[i][2*j] = SECRET_NUM;
|
| | | d.y.vals[i][2*j+1] = SECRET_NUM;
|
| | | }
|
| | | }
|
| | | fclose(fp1);
|
| | | fclose(fp2);
|
| | |
|
| | | free_image(im1);
|
| | | free_image(im2);
|
| | | }
|
| | | if(m) free(paths);
|
| | | return d;
|
| | | }
|
| | |
|
| | | data load_data_swag(char **paths, int n, int classes, float jitter)
|
| | | {
|
| | | int index = random_gen()%n;
|
| | | char *random_path = paths[index];
|
| | |
|
| | | image orig = load_image_color(random_path, 0, 0);
|
| | | int h = orig.h;
|
| | | int w = orig.w;
|
| | |
|
| | | data d = {0};
|
| | | d.shallow = 0;
|
| | | d.w = w;
|
| | | d.h = h;
|
| | |
|
| | | d.X.rows = 1;
|
| | | d.X.vals = (float**)xcalloc(d.X.rows, sizeof(float*));
|
| | | d.X.cols = h*w*3;
|
| | |
|
| | | int k = (4+classes)*30;
|
| | | d.y = make_matrix(1, k);
|
| | |
|
| | | int dw = w*jitter;
|
| | | int dh = h*jitter;
|
| | |
|
| | | int pleft = rand_uniform(-dw, dw);
|
| | | int pright = rand_uniform(-dw, dw);
|
| | | int ptop = rand_uniform(-dh, dh);
|
| | | int pbot = rand_uniform(-dh, dh);
|
| | |
|
| | | int swidth = w - pleft - pright;
|
| | | int sheight = h - ptop - pbot;
|
| | |
|
| | | float sx = (float)swidth / w;
|
| | | float sy = (float)sheight / h;
|
| | |
|
| | | int flip = random_gen()%2;
|
| | | image cropped = crop_image(orig, pleft, ptop, swidth, sheight);
|
| | |
|
| | | float dx = ((float)pleft/w)/sx;
|
| | | float dy = ((float)ptop /h)/sy;
|
| | |
|
| | | image sized = resize_image(cropped, w, h);
|
| | | if(flip) flip_image(sized);
|
| | | d.X.vals[0] = sized.data;
|
| | |
|
| | | fill_truth_swag(random_path, d.y.vals[0], classes, flip, dx, dy, 1./sx, 1./sy);
|
| | |
|
| | | free_image(orig);
|
| | | free_image(cropped);
|
| | |
|
| | | return d;
|
| | | }
|
| | |
|
| | | void blend_truth(float *new_truth, int boxes, float *old_truth)
|
| | | {
|
| | | const int t_size = 4 + 1;
|
| | | int count_new_truth = 0;
|
| | | int t;
|
| | | for (t = 0; t < boxes; ++t) {
|
| | | float x = new_truth[t*(4 + 1)];
|
| | | if (!x) break;
|
| | | count_new_truth++;
|
| | |
|
| | | }
|
| | | for (t = count_new_truth; t < boxes; ++t) {
|
| | | float *new_truth_ptr = new_truth + t*t_size;
|
| | | float *old_truth_ptr = old_truth + (t - count_new_truth)*t_size;
|
| | | float x = old_truth_ptr[0];
|
| | | if (!x) break;
|
| | |
|
| | | new_truth_ptr[0] = old_truth_ptr[0];
|
| | | new_truth_ptr[1] = old_truth_ptr[1];
|
| | | new_truth_ptr[2] = old_truth_ptr[2];
|
| | | new_truth_ptr[3] = old_truth_ptr[3];
|
| | | new_truth_ptr[4] = old_truth_ptr[4];
|
| | | }
|
| | | //printf("\n was %d bboxes, now %d bboxes \n", count_new_truth, t);
|
| | | }
|
| | |
|
| | |
|
| | | void blend_truth_mosaic(float *new_truth, int boxes, float *old_truth, int w, int h, float cut_x, float cut_y, int i_mixup,
|
| | | int left_shift, int right_shift, int top_shift, int bot_shift)
|
| | | {
|
| | | const int t_size = 4 + 1;
|
| | | int count_new_truth = 0;
|
| | | int t;
|
| | | for (t = 0; t < boxes; ++t) {
|
| | | float x = new_truth[t*(4 + 1)];
|
| | | if (!x) break;
|
| | | count_new_truth++;
|
| | |
|
| | | }
|
| | | int new_t = count_new_truth;
|
| | | for (t = count_new_truth; t < boxes; ++t) {
|
| | | float *new_truth_ptr = new_truth + new_t*t_size;
|
| | | new_truth_ptr[0] = 0;
|
| | | float *old_truth_ptr = old_truth + (t - count_new_truth)*t_size;
|
| | | float x = old_truth_ptr[0];
|
| | | if (!x) break;
|
| | |
|
| | | float xb = old_truth_ptr[0];
|
| | | float yb = old_truth_ptr[1];
|
| | | float wb = old_truth_ptr[2];
|
| | | float hb = old_truth_ptr[3];
|
| | |
|
| | |
|
| | |
|
| | | // shift 4 images
|
| | | if (i_mixup == 0) {
|
| | | xb = xb - (float)(w - cut_x - right_shift) / w;
|
| | | yb = yb - (float)(h - cut_y - bot_shift) / h;
|
| | | }
|
| | | if (i_mixup == 1) {
|
| | | xb = xb + (float)(cut_x - left_shift) / w;
|
| | | yb = yb - (float)(h - cut_y - bot_shift) / h;
|
| | | }
|
| | | if (i_mixup == 2) {
|
| | | xb = xb - (float)(w - cut_x - right_shift) / w;
|
| | | yb = yb + (float)(cut_y - top_shift) / h;
|
| | | }
|
| | | if (i_mixup == 3) {
|
| | | xb = xb + (float)(cut_x - left_shift) / w;
|
| | | yb = yb + (float)(cut_y - top_shift) / h;
|
| | | }
|
| | |
|
| | | int left = (xb - wb / 2)*w;
|
| | | int right = (xb + wb / 2)*w;
|
| | | int top = (yb - hb / 2)*h;
|
| | | int bot = (yb + hb / 2)*h;
|
| | |
|
| | | /*
|
| | | {
|
| | | // fix out of Mosaic-bound
|
| | | float left_bound = 0, right_bound = 0, top_bound = 0, bot_bound = 0;
|
| | | if (i_mixup == 0) {
|
| | | left_bound = 0;
|
| | | right_bound = cut_x;
|
| | | top_bound = 0;
|
| | | bot_bound = cut_y;
|
| | | }
|
| | | if (i_mixup == 1) {
|
| | | left_bound = cut_x;
|
| | | right_bound = w;
|
| | | top_bound = 0;
|
| | | bot_bound = cut_y;
|
| | | }
|
| | | if (i_mixup == 2) {
|
| | | left_bound = 0;
|
| | | right_bound = cut_x;
|
| | | top_bound = cut_y;
|
| | | bot_bound = h;
|
| | | }
|
| | | if (i_mixup == 3) {
|
| | | left_bound = cut_x;
|
| | | right_bound = w;
|
| | | top_bound = cut_y;
|
| | | bot_bound = h;
|
| | | }
|
| | |
|
| | |
|
| | | if (left < left_bound) {
|
| | | //printf(" i_mixup = %d, left = %d, left_bound = %f \n", i_mixup, left, left_bound);
|
| | | left = left_bound;
|
| | | }
|
| | | if (right > right_bound) {
|
| | | //printf(" i_mixup = %d, right = %d, right_bound = %f \n", i_mixup, right, right_bound);
|
| | | right = right_bound;
|
| | | }
|
| | | if (top < top_bound) top = top_bound;
|
| | | if (bot > bot_bound) bot = bot_bound;
|
| | |
|
| | |
|
| | | xb = ((float)(right + left) / 2) / w;
|
| | | wb = ((float)(right - left)) / w;
|
| | | yb = ((float)(bot + top) / 2) / h;
|
| | | hb = ((float)(bot - top)) / h;
|
| | | }
|
| | | */
|
| | |
|
| | | {
|
| | | // fix out of bound
|
| | | if (left < 0) {
|
| | | float diff = (float)left / w;
|
| | | xb = xb - diff / 2;
|
| | | wb = wb + diff;
|
| | | }
|
| | |
|
| | | if (right > w) {
|
| | | float diff = (float)(right - w) / w;
|
| | | xb = xb - diff / 2;
|
| | | wb = wb - diff;
|
| | | }
|
| | |
|
| | | if (top < 0) {
|
| | | float diff = (float)top / h;
|
| | | yb = yb - diff / 2;
|
| | | hb = hb + diff;
|
| | | }
|
| | |
|
| | | if (bot > h) {
|
| | | float diff = (float)(bot - h) / h;
|
| | | yb = yb - diff / 2;
|
| | | hb = hb - diff;
|
| | | }
|
| | |
|
| | | left = (xb - wb / 2)*w;
|
| | | right = (xb + wb / 2)*w;
|
| | | top = (yb - hb / 2)*h;
|
| | | bot = (yb + hb / 2)*h;
|
| | | }
|
| | |
|
| | | // leave only within the image
|
| | | if(left >= 0 && right <= w && top >= 0 && bot <= h &&
|
| | | wb > 0 && wb < 1 && hb > 0 && hb < 1 &&
|
| | | xb > 0 && xb < 1 && yb > 0 && yb < 1)
|
| | | {
|
| | | new_truth_ptr[0] = xb;
|
| | | new_truth_ptr[1] = yb;
|
| | | new_truth_ptr[2] = wb;
|
| | | new_truth_ptr[3] = hb;
|
| | | new_truth_ptr[4] = old_truth_ptr[4];
|
| | | new_t++;
|
| | | }
|
| | | }
|
| | | //printf("\n was %d bboxes, now %d bboxes \n", count_new_truth, t);
|
| | | }
|
| | |
|
| | | #ifdef OPENCV
|
| | |
|
| | | #include "http_stream.h"
|
| | |
|
| | | data load_data_detection(int n, char **paths, int m, int w, int h, int c, int boxes, int classes, int use_flip, int use_gaussian_noise, int use_blur, int use_mixup,
|
| | | float jitter, float resize, float hue, float saturation, float exposure, int mini_batch, int track, int augment_speed, int letter_box, int show_imgs)
|
| | | {
|
| | | const int random_index = random_gen();
|
| | | c = c ? c : 3;
|
| | |
|
| | | if (use_mixup == 2 || use_mixup == 4) {
|
| | | printf("\n cutmix=1 - isn't supported for Detector (use cutmix=1 only for Classifier) \n");
|
| | | if (check_mistakes) getchar();
|
| | | if(use_mixup == 2) use_mixup = 0;
|
| | | else use_mixup = 3;
|
| | | }
|
| | | if (use_mixup == 3 && letter_box) {
|
| | | printf("\n Combination: letter_box=1 & mosaic=1 - isn't supported, use only 1 of these parameters \n");
|
| | | if (check_mistakes) getchar();
|
| | | exit(0);
|
| | | }
|
| | | if (random_gen() % 2 == 0) use_mixup = 0;
|
| | | int i;
|
| | |
|
| | | int *cut_x = NULL, *cut_y = NULL;
|
| | | if (use_mixup == 3) {
|
| | | cut_x = (int*)calloc(n, sizeof(int));
|
| | | cut_y = (int*)calloc(n, sizeof(int));
|
| | | const float min_offset = 0.2; // 20%
|
| | | for (i = 0; i < n; ++i) {
|
| | | cut_x[i] = rand_int(w*min_offset, w*(1 - min_offset));
|
| | | cut_y[i] = rand_int(h*min_offset, h*(1 - min_offset));
|
| | | }
|
| | | }
|
| | |
|
| | | data d = {0};
|
| | | d.shallow = 0;
|
| | |
|
| | | d.X.rows = n;
|
| | | d.X.vals = (float**)xcalloc(d.X.rows, sizeof(float*));
|
| | | d.X.cols = h*w*c;
|
| | |
|
| | | float r1 = 0, r2 = 0, r3 = 0, r4 = 0, r_scale = 0;
|
| | | float resize_r1 = 0, resize_r2 = 0;
|
| | | float dhue = 0, dsat = 0, dexp = 0, flip = 0, blur = 0;
|
| | | int augmentation_calculated = 0, gaussian_noise = 0;
|
| | |
|
| | | d.y = make_matrix(n, 5*boxes);
|
| | | int i_mixup = 0;
|
| | | for (i_mixup = 0; i_mixup <= use_mixup; i_mixup++) {
|
| | | if (i_mixup) augmentation_calculated = 0; // recalculate augmentation for the 2nd sequence if(track==1)
|
| | |
|
| | | char **random_paths;
|
| | | if (track) random_paths = get_sequential_paths(paths, n, m, mini_batch, augment_speed);
|
| | | else random_paths = get_random_paths(paths, n, m);
|
| | |
|
| | | for (i = 0; i < n; ++i) {
|
| | | float *truth = (float*)xcalloc(5 * boxes, sizeof(float));
|
| | | const char *filename = random_paths[i];
|
| | |
|
| | | int flag = (c >= 3);
|
| | | mat_cv *src;
|
| | | src = load_image_mat_cv(filename, flag);
|
| | | if (src == NULL) {
|
| | | printf("\n Error in load_data_detection() - OpenCV \n");
|
| | | fflush(stdout);
|
| | | if (check_mistakes) {
|
| | | getchar();
|
| | | }
|
| | | continue;
|
| | | }
|
| | |
|
| | | int oh = get_height_mat(src);
|
| | | int ow = get_width_mat(src);
|
| | |
|
| | | int dw = (ow*jitter);
|
| | | int dh = (oh*jitter);
|
| | |
|
| | | float resize_down = resize, resize_up = resize;
|
| | | if (resize_down > 1.0) resize_down = 1 / resize_down;
|
| | | int min_rdw = ow*(1 - (1 / resize_down)) / 2; // < 0
|
| | | int min_rdh = oh*(1 - (1 / resize_down)) / 2; // < 0
|
| | |
|
| | | if (resize_up < 1.0) resize_up = 1 / resize_up;
|
| | | int max_rdw = ow*(1 - (1 / resize_up)) / 2; // > 0
|
| | | int max_rdh = oh*(1 - (1 / resize_up)) / 2; // > 0
|
| | | //printf(" down = %f, up = %f \n", (1 - (1 / resize_down)) / 2, (1 - (1 / resize_up)) / 2);
|
| | |
|
| | | if (!augmentation_calculated || !track)
|
| | | {
|
| | | augmentation_calculated = 1;
|
| | | resize_r1 = random_float();
|
| | | resize_r2 = random_float();
|
| | |
|
| | | r1 = random_float();
|
| | | r2 = random_float();
|
| | | r3 = random_float();
|
| | | r4 = random_float();
|
| | |
|
| | | r_scale = random_float();
|
| | |
|
| | | dhue = rand_uniform_strong(-hue, hue);
|
| | | dsat = rand_scale(saturation);
|
| | | dexp = rand_scale(exposure);
|
| | |
|
| | | flip = use_flip ? random_gen() % 2 : 0;
|
| | |
|
| | | if (use_blur) {
|
| | | int tmp_blur = rand_int(0, 2); // 0 - disable, 1 - blur background, 2 - blur the whole image
|
| | | if (tmp_blur == 0) blur = 0;
|
| | | else if (tmp_blur == 1) blur = 1;
|
| | | else blur = use_blur;
|
| | | }
|
| | |
|
| | | if (use_gaussian_noise && rand_int(0, 1) == 1) gaussian_noise = use_gaussian_noise;
|
| | | else gaussian_noise = 0;
|
| | | }
|
| | |
|
| | | int pleft = rand_precalc_random(-dw, dw, r1);
|
| | | int pright = rand_precalc_random(-dw, dw, r2);
|
| | | int ptop = rand_precalc_random(-dh, dh, r3);
|
| | | int pbot = rand_precalc_random(-dh, dh, r4);
|
| | |
|
| | | if (resize < 1) {
|
| | | // downsize only
|
| | | pleft += rand_precalc_random(min_rdw, 0, resize_r1);
|
| | | pright += rand_precalc_random(min_rdw, 0, resize_r2);
|
| | | ptop += rand_precalc_random(min_rdh, 0, resize_r1);
|
| | | pbot += rand_precalc_random(min_rdh, 0, resize_r2);
|
| | | }
|
| | | else {
|
| | | pleft += rand_precalc_random(min_rdw, max_rdw, resize_r1);
|
| | | pright += rand_precalc_random(min_rdw, max_rdw, resize_r2);
|
| | | ptop += rand_precalc_random(min_rdh, max_rdh, resize_r1);
|
| | | pbot += rand_precalc_random(min_rdh, max_rdh, resize_r2);
|
| | | }
|
| | |
|
| | | //printf("\n pleft = %d, pright = %d, ptop = %d, pbot = %d, ow = %d, oh = %d \n", pleft, pright, ptop, pbot, ow, oh);
|
| | |
|
| | | //float scale = rand_precalc_random(.25, 2, r_scale); // unused currently
|
| | |
|
| | | if (letter_box)
|
| | | {
|
| | | float img_ar = (float)ow / (float)oh;
|
| | | float net_ar = (float)w / (float)h;
|
| | | float result_ar = img_ar / net_ar;
|
| | | //printf(" ow = %d, oh = %d, w = %d, h = %d, img_ar = %f, net_ar = %f, result_ar = %f \n", ow, oh, w, h, img_ar, net_ar, result_ar);
|
| | | if (result_ar > 1) // sheight - should be increased
|
| | | {
|
| | | float oh_tmp = ow / net_ar;
|
| | | float delta_h = (oh_tmp - oh)/2;
|
| | | ptop = ptop - delta_h;
|
| | | pbot = pbot - delta_h;
|
| | | //printf(" result_ar = %f, oh_tmp = %f, delta_h = %d, ptop = %f, pbot = %f \n", result_ar, oh_tmp, delta_h, ptop, pbot);
|
| | | }
|
| | | else // swidth - should be increased
|
| | | {
|
| | | float ow_tmp = oh * net_ar;
|
| | | float delta_w = (ow_tmp - ow)/2;
|
| | | pleft = pleft - delta_w;
|
| | | pright = pright - delta_w;
|
| | | //printf(" result_ar = %f, ow_tmp = %f, delta_w = %d, pleft = %f, pright = %f \n", result_ar, ow_tmp, delta_w, pleft, pright);
|
| | | }
|
| | |
|
| | | //printf("\n pleft = %d, pright = %d, ptop = %d, pbot = %d, ow = %d, oh = %d \n", pleft, pright, ptop, pbot, ow, oh);
|
| | | }
|
| | |
|
| | | /*
|
| | | // move each 2nd image to the corner - so that most of it was visible
|
| | | if (use_mixup == 3 && random_gen() % 2 == 0) {
|
| | | if (flip) {
|
| | | if (i_mixup == 0) pleft += pright, pright = 0, pbot += ptop, ptop = 0;
|
| | | if (i_mixup == 1) pright += pleft, pleft = 0, pbot += ptop, ptop = 0;
|
| | | if (i_mixup == 2) pleft += pright, pright = 0, ptop += pbot, pbot = 0;
|
| | | if (i_mixup == 3) pright += pleft, pleft = 0, ptop += pbot, pbot = 0;
|
| | | }
|
| | | else {
|
| | | if (i_mixup == 0) pright += pleft, pleft = 0, pbot += ptop, ptop = 0;
|
| | | if (i_mixup == 1) pleft += pright, pright = 0, pbot += ptop, ptop = 0;
|
| | | if (i_mixup == 2) pright += pleft, pleft = 0, ptop += pbot, pbot = 0;
|
| | | if (i_mixup == 3) pleft += pright, pright = 0, ptop += pbot, pbot = 0;
|
| | | }
|
| | | }
|
| | | */
|
| | |
|
| | | int swidth = ow - pleft - pright;
|
| | | int sheight = oh - ptop - pbot;
|
| | |
|
| | | float sx = (float)swidth / ow;
|
| | | float sy = (float)sheight / oh;
|
| | |
|
| | | float dx = ((float)pleft / ow) / sx;
|
| | | float dy = ((float)ptop / oh) / sy;
|
| | |
|
| | |
|
| | | int min_w_h = fill_truth_detection(filename, boxes, truth, classes, flip, dx, dy, 1. / sx, 1. / sy, w, h);
|
| | |
|
| | | if ((min_w_h / 8) < blur && blur > 1) blur = min_w_h / 8; // disable blur if one of the objects is too small
|
| | |
|
| | | image ai = image_data_augmentation(src, w, h, pleft, ptop, swidth, sheight, flip, dhue, dsat, dexp,
|
| | | gaussian_noise, blur, boxes, truth);
|
| | |
|
| | | if (use_mixup == 0) {
|
| | | d.X.vals[i] = ai.data;
|
| | | memcpy(d.y.vals[i], truth, 5 * boxes * sizeof(float));
|
| | | }
|
| | | else if (use_mixup == 1) {
|
| | | if (i_mixup == 0) {
|
| | | d.X.vals[i] = ai.data;
|
| | | memcpy(d.y.vals[i], truth, 5 * boxes * sizeof(float));
|
| | | }
|
| | | else if (i_mixup == 1) {
|
| | | image old_img = make_empty_image(w, h, c);
|
| | | old_img.data = d.X.vals[i];
|
| | | //show_image(ai, "new");
|
| | | //show_image(old_img, "old");
|
| | | //wait_until_press_key_cv();
|
| | | blend_images_cv(ai, 0.5, old_img, 0.5);
|
| | | blend_truth(d.y.vals[i], boxes, truth);
|
| | | free_image(old_img);
|
| | | d.X.vals[i] = ai.data;
|
| | | }
|
| | | }
|
| | | else if (use_mixup == 3) {
|
| | | if (i_mixup == 0) {
|
| | | image tmp_img = make_image(w, h, c);
|
| | | d.X.vals[i] = tmp_img.data;
|
| | | }
|
| | |
|
| | | if (flip) {
|
| | | int tmp = pleft;
|
| | | pleft = pright;
|
| | | pright = tmp;
|
| | | }
|
| | |
|
| | | const int left_shift = min_val_cmp(cut_x[i], max_val_cmp(0, (-pleft*w / ow)));
|
| | | const int top_shift = min_val_cmp(cut_y[i], max_val_cmp(0, (-ptop*h / oh)));
|
| | |
|
| | | const int right_shift = min_val_cmp((w - cut_x[i]), max_val_cmp(0, (-pright*w / ow)));
|
| | | const int bot_shift = min_val_cmp(h - cut_y[i], max_val_cmp(0, (-pbot*h / oh)));
|
| | |
|
| | |
|
| | | int k, x, y;
|
| | | for (k = 0; k < c; ++k) {
|
| | | for (y = 0; y < h; ++y) {
|
| | | int j = y*w + k*w*h;
|
| | | if (i_mixup == 0 && y < cut_y[i]) {
|
| | | int j_src = (w - cut_x[i] - right_shift) + (y + h - cut_y[i] - bot_shift)*w + k*w*h;
|
| | | memcpy(&d.X.vals[i][j + 0], &ai.data[j_src], cut_x[i] * sizeof(float));
|
| | | }
|
| | | if (i_mixup == 1 && y < cut_y[i]) {
|
| | | int j_src = left_shift + (y + h - cut_y[i] - bot_shift)*w + k*w*h;
|
| | | memcpy(&d.X.vals[i][j + cut_x[i]], &ai.data[j_src], (w-cut_x[i]) * sizeof(float));
|
| | | }
|
| | | if (i_mixup == 2 && y >= cut_y[i]) {
|
| | | int j_src = (w - cut_x[i] - right_shift) + (top_shift + y - cut_y[i])*w + k*w*h;
|
| | | memcpy(&d.X.vals[i][j + 0], &ai.data[j_src], cut_x[i] * sizeof(float));
|
| | | }
|
| | | if (i_mixup == 3 && y >= cut_y[i]) {
|
| | | int j_src = left_shift + (top_shift + y - cut_y[i])*w + k*w*h;
|
| | | memcpy(&d.X.vals[i][j + cut_x[i]], &ai.data[j_src], (w - cut_x[i]) * sizeof(float));
|
| | | }
|
| | | }
|
| | | }
|
| | |
|
| | | blend_truth_mosaic(d.y.vals[i], boxes, truth, w, h, cut_x[i], cut_y[i], i_mixup, left_shift, right_shift, top_shift, bot_shift);
|
| | |
|
| | | free_image(ai);
|
| | | ai.data = d.X.vals[i];
|
| | | }
|
| | |
|
| | |
|
| | | if (show_imgs && i_mixup == use_mixup) // delete i_mixup
|
| | | {
|
| | | image tmp_ai = copy_image(ai);
|
| | | char buff[1000];
|
| | | //sprintf(buff, "aug_%d_%d_%s_%d", random_index, i, basecfg((char*)filename), random_gen());
|
| | | sprintf(buff, "aug_%d_%d_%d", random_index, i, random_gen());
|
| | | int t;
|
| | | for (t = 0; t < boxes; ++t) {
|
| | | box b = float_to_box_stride(d.y.vals[i] + t*(4 + 1), 1);
|
| | | if (!b.x) break;
|
| | | int left = (b.x - b.w / 2.)*ai.w;
|
| | | int right = (b.x + b.w / 2.)*ai.w;
|
| | | int top = (b.y - b.h / 2.)*ai.h;
|
| | | int bot = (b.y + b.h / 2.)*ai.h;
|
| | | draw_box_width(tmp_ai, left, top, right, bot, 1, 150, 100, 50); // 3 channels RGB
|
| | | }
|
| | |
|
| | | save_image(tmp_ai, buff);
|
| | | if (show_imgs == 1) {
|
| | | //char buff_src[1000];
|
| | | //sprintf(buff_src, "src_%d_%d_%s_%d", random_index, i, basecfg((char*)filename), random_gen());
|
| | | //show_image_mat(src, buff_src);
|
| | | show_image(tmp_ai, buff);
|
| | | wait_until_press_key_cv();
|
| | | }
|
| | | printf("\nYou use flag -show_imgs, so will be saved aug_...jpg images. Click on window and press ESC button \n");
|
| | | free_image(tmp_ai);
|
| | | }
|
| | |
|
| | | release_mat(&src);
|
| | | free(truth);
|
| | | }
|
| | | if (random_paths) free(random_paths);
|
| | | }
|
| | |
|
| | |
|
| | | return d;
|
| | | }
|
| | | #else // OPENCV
|
| | | void blend_images(image new_img, float alpha, image old_img, float beta)
|
| | | {
|
| | | int data_size = new_img.w * new_img.h * new_img.c;
|
| | | int i;
|
| | | #pragma omp parallel for
|
| | | for (i = 0; i < data_size; ++i)
|
| | | new_img.data[i] = new_img.data[i] * alpha + old_img.data[i] * beta;
|
| | | }
|
| | |
|
| | | data load_data_detection(int n, char **paths, int m, int w, int h, int c, int boxes, int classes, int use_flip, int gaussian_noise, int use_blur, int use_mixup,
|
| | | float jitter, float resize, float hue, float saturation, float exposure, int mini_batch, int track, int augment_speed, int letter_box, int show_imgs)
|
| | | {
|
| | | const int random_index = random_gen();
|
| | | c = c ? c : 3;
|
| | | char **random_paths;
|
| | | char **mixup_random_paths = NULL;
|
| | | if(track) random_paths = get_sequential_paths(paths, n, m, mini_batch, augment_speed);
|
| | | else random_paths = get_random_paths(paths, n, m);
|
| | |
|
| | | //assert(use_mixup < 2);
|
| | | if (use_mixup == 2) {
|
| | | printf("\n cutmix=1 - isn't supported for Detector \n");
|
| | | exit(0);
|
| | | }
|
| | | if (use_mixup == 3 || use_mixup == 4) {
|
| | | printf("\n mosaic=1 - compile Darknet with OpenCV for using mosaic=1 \n");
|
| | | exit(0);
|
| | | }
|
| | | int mixup = use_mixup ? random_gen() % 2 : 0;
|
| | | //printf("\n mixup = %d \n", mixup);
|
| | | if (mixup) {
|
| | | if (track) mixup_random_paths = get_sequential_paths(paths, n, m, mini_batch, augment_speed);
|
| | | else mixup_random_paths = get_random_paths(paths, n, m);
|
| | | }
|
| | |
|
| | | int i;
|
| | | data d = { 0 };
|
| | | d.shallow = 0;
|
| | |
|
| | | d.X.rows = n;
|
| | | d.X.vals = (float**)xcalloc(d.X.rows, sizeof(float*));
|
| | | d.X.cols = h*w*c;
|
| | |
|
| | | float r1 = 0, r2 = 0, r3 = 0, r4 = 0, r_scale;
|
| | | float resize_r1 = 0, resize_r2 = 0;
|
| | | float dhue = 0, dsat = 0, dexp = 0, flip = 0;
|
| | | int augmentation_calculated = 0;
|
| | |
|
| | | d.y = make_matrix(n, 5 * boxes);
|
| | | int i_mixup = 0;
|
| | | for (i_mixup = 0; i_mixup <= mixup; i_mixup++) {
|
| | | if (i_mixup) augmentation_calculated = 0;
|
| | | for (i = 0; i < n; ++i) {
|
| | | float *truth = (float*)xcalloc(5 * boxes, sizeof(float));
|
| | | char *filename = (i_mixup) ? mixup_random_paths[i] : random_paths[i];
|
| | |
|
| | | image orig = load_image(filename, 0, 0, c);
|
| | |
|
| | | int oh = orig.h;
|
| | | int ow = orig.w;
|
| | |
|
| | | int dw = (ow*jitter);
|
| | | int dh = (oh*jitter);
|
| | |
|
| | | float resize_down = resize, resize_up = resize;
|
| | | if (resize_down > 1.0) resize_down = 1 / resize_down;
|
| | | int min_rdw = ow*(1 - (1 / resize_down)) / 2;
|
| | | int min_rdh = oh*(1 - (1 / resize_down)) / 2;
|
| | |
|
| | | if (resize_up < 1.0) resize_up = 1 / resize_up;
|
| | | int max_rdw = ow*(1 - (1 / resize_up)) / 2;
|
| | | int max_rdh = oh*(1 - (1 / resize_up)) / 2;
|
| | |
|
| | | if (!augmentation_calculated || !track)
|
| | | {
|
| | | augmentation_calculated = 1;
|
| | | resize_r1 = random_float();
|
| | | resize_r2 = random_float();
|
| | |
|
| | | r1 = random_float();
|
| | | r2 = random_float();
|
| | | r3 = random_float();
|
| | | r4 = random_float();
|
| | |
|
| | | r_scale = random_float();
|
| | |
|
| | | dhue = rand_uniform_strong(-hue, hue);
|
| | | dsat = rand_scale(saturation);
|
| | | dexp = rand_scale(exposure);
|
| | |
|
| | | flip = use_flip ? random_gen() % 2 : 0;
|
| | | }
|
| | |
|
| | | int pleft = rand_precalc_random(-dw, dw, r1);
|
| | | int pright = rand_precalc_random(-dw, dw, r2);
|
| | | int ptop = rand_precalc_random(-dh, dh, r3);
|
| | | int pbot = rand_precalc_random(-dh, dh, r4);
|
| | |
|
| | | if (resize < 1) {
|
| | | // downsize only
|
| | | pleft += rand_precalc_random(min_rdw, 0, resize_r1);
|
| | | pright += rand_precalc_random(min_rdw, 0, resize_r2);
|
| | | ptop += rand_precalc_random(min_rdh, 0, resize_r1);
|
| | | pbot += rand_precalc_random(min_rdh, 0, resize_r2);
|
| | | }
|
| | | else {
|
| | | pleft += rand_precalc_random(min_rdw, max_rdw, resize_r1);
|
| | | pright += rand_precalc_random(min_rdw, max_rdw, resize_r2);
|
| | | ptop += rand_precalc_random(min_rdh, max_rdh, resize_r1);
|
| | | pbot += rand_precalc_random(min_rdh, max_rdh, resize_r2);
|
| | | }
|
| | |
|
| | | if (letter_box)
|
| | | {
|
| | | float img_ar = (float)ow / (float)oh;
|
| | | float net_ar = (float)w / (float)h;
|
| | | float result_ar = img_ar / net_ar;
|
| | | //printf(" ow = %d, oh = %d, w = %d, h = %d, img_ar = %f, net_ar = %f, result_ar = %f \n", ow, oh, w, h, img_ar, net_ar, result_ar);
|
| | | if (result_ar > 1) // sheight - should be increased
|
| | | {
|
| | | float oh_tmp = ow / net_ar;
|
| | | float delta_h = (oh_tmp - oh) / 2;
|
| | | ptop = ptop - delta_h;
|
| | | pbot = pbot - delta_h;
|
| | | //printf(" result_ar = %f, oh_tmp = %f, delta_h = %d, ptop = %f, pbot = %f \n", result_ar, oh_tmp, delta_h, ptop, pbot);
|
| | | }
|
| | | else // swidth - should be increased
|
| | | {
|
| | | float ow_tmp = oh * net_ar;
|
| | | float delta_w = (ow_tmp - ow) / 2;
|
| | | pleft = pleft - delta_w;
|
| | | pright = pright - delta_w;
|
| | | //printf(" result_ar = %f, ow_tmp = %f, delta_w = %d, pleft = %f, pright = %f \n", result_ar, ow_tmp, delta_w, pleft, pright);
|
| | | }
|
| | | }
|
| | |
|
| | | int swidth = ow - pleft - pright;
|
| | | int sheight = oh - ptop - pbot;
|
| | |
|
| | | float sx = (float)swidth / ow;
|
| | | float sy = (float)sheight / oh;
|
| | |
|
| | | image cropped = crop_image(orig, pleft, ptop, swidth, sheight);
|
| | |
|
| | | float dx = ((float)pleft / ow) / sx;
|
| | | float dy = ((float)ptop / oh) / sy;
|
| | |
|
| | | image sized = resize_image(cropped, w, h);
|
| | | if (flip) flip_image(sized);
|
| | | distort_image(sized, dhue, dsat, dexp);
|
| | | //random_distort_image(sized, hue, saturation, exposure);
|
| | |
|
| | | fill_truth_detection(filename, boxes, truth, classes, flip, dx, dy, 1. / sx, 1. / sy, w, h);
|
| | |
|
| | | if (i_mixup) {
|
| | | image old_img = sized;
|
| | | old_img.data = d.X.vals[i];
|
| | | //show_image(sized, "new");
|
| | | //show_image(old_img, "old");
|
| | | //wait_until_press_key_cv();
|
| | | blend_images(sized, 0.5, old_img, 0.5);
|
| | | blend_truth(truth, boxes, d.y.vals[i]);
|
| | | free_image(old_img);
|
| | | }
|
| | |
|
| | | d.X.vals[i] = sized.data;
|
| | | memcpy(d.y.vals[i], truth, 5 * boxes * sizeof(float));
|
| | |
|
| | | if (show_imgs)// && i_mixup)
|
| | | {
|
| | | char buff[1000];
|
| | | sprintf(buff, "aug_%d_%d_%s_%d", random_index, i, basecfg(filename), random_gen());
|
| | |
|
| | | int t;
|
| | | for (t = 0; t < boxes; ++t) {
|
| | | box b = float_to_box_stride(d.y.vals[i] + t*(4 + 1), 1);
|
| | | if (!b.x) break;
|
| | | int left = (b.x - b.w / 2.)*sized.w;
|
| | | int right = (b.x + b.w / 2.)*sized.w;
|
| | | int top = (b.y - b.h / 2.)*sized.h;
|
| | | int bot = (b.y + b.h / 2.)*sized.h;
|
| | | draw_box_width(sized, left, top, right, bot, 1, 150, 100, 50); // 3 channels RGB
|
| | | }
|
| | |
|
| | | save_image(sized, buff);
|
| | | if (show_imgs == 1) {
|
| | | show_image(sized, buff);
|
| | | wait_until_press_key_cv();
|
| | | }
|
| | | printf("\nYou use flag -show_imgs, so will be saved aug_...jpg images. Press Enter: \n");
|
| | | //getchar();
|
| | | }
|
| | |
|
| | | free_image(orig);
|
| | | free_image(cropped);
|
| | | free(truth);
|
| | | }
|
| | | }
|
| | | free(random_paths);
|
| | | if (mixup_random_paths) free(mixup_random_paths);
|
| | | return d;
|
| | | }
|
| | | #endif // OPENCV
|
| | |
|
| | | void *load_thread(void *ptr)
|
| | | {
|
| | | //srand(time(0));
|
| | | //printf("Loading data: %d\n", random_gen());
|
| | | load_args a = *(struct load_args*)ptr;
|
| | | if(a.exposure == 0) a.exposure = 1;
|
| | | if(a.saturation == 0) a.saturation = 1;
|
| | | if(a.aspect == 0) a.aspect = 1;
|
| | |
|
| | | if (a.type == OLD_CLASSIFICATION_DATA){
|
| | | *a.d = load_data_old(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.hierarchy, a.flip, a.min, a.max, a.w, a.h, a.angle, a.aspect, a.hue, a.saturation, a.exposure, a.mixup, a.blur, a.show_imgs, a.label_smooth_eps, a.dontuse_opencv);
|
| | | } else if (a.type == SUPER_DATA){
|
| | | *a.d = load_data_super(a.paths, a.n, a.m, a.w, a.h, a.scale);
|
| | | } else if (a.type == WRITING_DATA){
|
| | | *a.d = load_data_writing(a.paths, a.n, a.m, a.w, a.h, a.out_w, a.out_h);
|
| | | } else if (a.type == REGION_DATA){
|
| | | *a.d = load_data_region(a.n, a.paths, a.m, a.w, a.h, a.num_boxes, a.classes, a.jitter, a.hue, a.saturation, a.exposure);
|
| | | } else if (a.type == DETECTION_DATA){
|
| | | *a.d = load_data_detection(a.n, a.paths, a.m, a.w, a.h, a.c, a.num_boxes, a.classes, a.flip, a.gaussian_noise, a.blur, a.mixup, a.jitter, a.resize,
|
| | | a.hue, a.saturation, a.exposure, a.mini_batch, a.track, a.augment_speed, a.letter_box, a.show_imgs);
|
| | | } else if (a.type == SWAG_DATA){
|
| | | *a.d = load_data_swag(a.paths, a.n, a.classes, a.jitter);
|
| | | } else if (a.type == COMPARE_DATA){
|
| | | *a.d = load_data_compare(a.n, a.paths, a.m, a.classes, a.w, a.h);
|
| | | } else if (a.type == IMAGE_DATA){
|
| | | *(a.im) = load_image(a.path, 0, 0, a.c);
|
| | | *(a.resized) = resize_image(*(a.im), a.w, a.h);
|
| | | }else if (a.type == LETTERBOX_DATA) {
|
| | | *(a.im) = load_image(a.path, 0, 0, a.c);
|
| | | *(a.resized) = letterbox_image(*(a.im), a.w, a.h);
|
| | | } else if (a.type == TAG_DATA){
|
| | | *a.d = load_data_tag(a.paths, a.n, a.m, a.classes, a.flip, a.min, a.max, a.w, a.h, a.angle, a.aspect, a.hue, a.saturation, a.exposure);
|
| | | }
|
| | | free(ptr);
|
| | | return 0;
|
| | | }
|
| | |
|
| | | pthread_t load_data_in_thread(load_args args)
|
| | | {
|
| | | pthread_t thread;
|
| | | struct load_args* ptr = (load_args*)xcalloc(1, sizeof(struct load_args));
|
| | | *ptr = args;
|
| | | if(pthread_create(&thread, 0, load_thread, ptr)) error("Thread creation failed");
|
| | | return thread;
|
| | | }
|
| | |
|
| | | static const int thread_wait_ms = 5;
|
| | | static volatile int flag_exit;
|
| | | static volatile int * run_load_data = NULL;
|
| | | static load_args * args_swap = NULL;
|
| | | static pthread_t* threads = NULL;
|
| | |
|
| | | pthread_mutex_t mtx_load_data = PTHREAD_MUTEX_INITIALIZER;
|
| | |
|
| | | void *run_thread_loop(void *ptr)
|
| | | {
|
| | | const int i = *(int *)ptr;
|
| | |
|
| | | while (!custom_atomic_load_int(&flag_exit)) {
|
| | | while (!custom_atomic_load_int(&run_load_data[i])) {
|
| | | if (custom_atomic_load_int(&flag_exit)) {
|
| | | free(ptr);
|
| | | return 0;
|
| | | }
|
| | | this_thread_sleep_for(thread_wait_ms);
|
| | | }
|
| | |
|
| | | pthread_mutex_lock(&mtx_load_data);
|
| | | load_args *args_local = (load_args *)xcalloc(1, sizeof(load_args));
|
| | | *args_local = args_swap[i];
|
| | | pthread_mutex_unlock(&mtx_load_data);
|
| | |
|
| | | load_thread(args_local);
|
| | |
|
| | | custom_atomic_store_int(&run_load_data[i], 0);
|
| | | }
|
| | | free(ptr);
|
| | | return 0;
|
| | | }
|
| | |
|
| | | void *load_threads(void *ptr)
|
| | | {
|
| | | //srand(time(0));
|
| | | int i;
|
| | | load_args args = *(load_args *)ptr;
|
| | | if (args.threads == 0) args.threads = 1;
|
| | | data *out = args.d;
|
| | | int total = args.n;
|
| | | free(ptr);
|
| | | data* buffers = (data*)xcalloc(args.threads, sizeof(data));
|
| | | if (!threads) {
|
| | | threads = (pthread_t*)xcalloc(args.threads, sizeof(pthread_t));
|
| | | run_load_data = (volatile int *)xcalloc(args.threads, sizeof(int));
|
| | | args_swap = (load_args *)xcalloc(args.threads, sizeof(load_args));
|
| | | fprintf(stderr, " Create %d permanent cpu-threads \n", args.threads);
|
| | |
|
| | | for (i = 0; i < args.threads; ++i) {
|
| | | int* ptr = (int*)xcalloc(1, sizeof(int));
|
| | | *ptr = i;
|
| | | if (pthread_create(&threads[i], 0, run_thread_loop, ptr)) error("Thread creation failed");
|
| | | }
|
| | | }
|
| | |
|
| | | for (i = 0; i < args.threads; ++i) {
|
| | | args.d = buffers + i;
|
| | | args.n = (i + 1) * total / args.threads - i * total / args.threads;
|
| | |
|
| | | pthread_mutex_lock(&mtx_load_data);
|
| | | args_swap[i] = args;
|
| | | pthread_mutex_unlock(&mtx_load_data);
|
| | |
|
| | | custom_atomic_store_int(&run_load_data[i], 1); // run thread
|
| | | }
|
| | | for (i = 0; i < args.threads; ++i) {
|
| | | while (custom_atomic_load_int(&run_load_data[i])) this_thread_sleep_for(thread_wait_ms); // join
|
| | | }
|
| | |
|
| | | /*
|
| | | pthread_t* threads = (pthread_t*)xcalloc(args.threads, sizeof(pthread_t));
|
| | | for(i = 0; i < args.threads; ++i){
|
| | | args.d = buffers + i;
|
| | | args.n = (i+1) * total/args.threads - i * total/args.threads;
|
| | | threads[i] = load_data_in_thread(args);
|
| | | }
|
| | | for(i = 0; i < args.threads; ++i){
|
| | | pthread_join(threads[i], 0);
|
| | | }
|
| | | */
|
| | |
|
| | | *out = concat_datas(buffers, args.threads);
|
| | | out->shallow = 0;
|
| | | for(i = 0; i < args.threads; ++i){
|
| | | buffers[i].shallow = 1;
|
| | | free_data(buffers[i]);
|
| | | }
|
| | | free(buffers);
|
| | | //free(threads);
|
| | | return 0;
|
| | | }
|
| | |
|
| | | void free_load_threads(void *ptr)
|
| | | {
|
| | | load_args args = *(load_args *)ptr;
|
| | | if (args.threads == 0) args.threads = 1;
|
| | | int i;
|
| | | if (threads) {
|
| | | custom_atomic_store_int(&flag_exit, 1);
|
| | | for (i = 0; i < args.threads; ++i) {
|
| | | pthread_join(threads[i], 0);
|
| | | }
|
| | | free((void*)run_load_data);
|
| | | free(args_swap);
|
| | | free(threads);
|
| | | threads = NULL;
|
| | | custom_atomic_store_int(&flag_exit, 0);
|
| | | }
|
| | | }
|
| | |
|
| | | pthread_t load_data(load_args args)
|
| | | {
|
| | | pthread_t thread;
|
| | | struct load_args* ptr = (load_args*)xcalloc(1, sizeof(struct load_args));
|
| | | *ptr = args;
|
| | | if(pthread_create(&thread, 0, load_threads, ptr)) error("Thread creation failed");
|
| | | return thread;
|
| | | }
|
| | |
|
| | | data load_data_writing(char **paths, int n, int m, int w, int h, int out_w, int out_h)
|
| | | {
|
| | | if(m) paths = get_random_paths(paths, n, m);
|
| | | char **replace_paths = find_replace_paths(paths, n, ".png", "-label.png");
|
| | | 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);
|
| | | if(m) free(paths);
|
| | | int i;
|
| | | for(i = 0; i < n; ++i) free(replace_paths[i]);
|
| | | free(replace_paths);
|
| | | return d;
|
| | | }
|
| | |
|
| | | data load_data_old(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 = {0};
|
| | | d.shallow = 0;
|
| | | d.X = load_image_paths(paths, n, w, h);
|
| | | d.y = load_labels_paths(paths, n, labels, k, 0, 0);
|
| | | if(m) free(paths);
|
| | | return d;
|
| | | }
|
| | |
|
| | | /*
|
| | | data load_data_study(char **paths, int n, int m, char **labels, int k, int min, int max, int size, float angle, float aspect, float hue, float saturation, float exposure)
|
| | | {
|
| | | 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_augment_paths(paths, n, flip, min, max, size, angle, aspect, hue, saturation, exposure);
|
| | | d.y = load_labels_paths(paths, n, labels, k);
|
| | | if(m) free(paths);
|
| | | return d;
|
| | | }
|
| | | */
|
| | |
|
| | | data load_data_super(char **paths, int n, int m, int w, int h, int scale)
|
| | | {
|
| | | if(m) paths = get_random_paths(paths, n, m);
|
| | | data d = {0};
|
| | | d.shallow = 0;
|
| | |
|
| | | int i;
|
| | | d.X.rows = n;
|
| | | d.X.vals = (float**)xcalloc(n, sizeof(float*));
|
| | | d.X.cols = w*h*3;
|
| | |
|
| | | d.y.rows = n;
|
| | | d.y.vals = (float**)xcalloc(n, sizeof(float*));
|
| | | d.y.cols = w*scale * h*scale * 3;
|
| | |
|
| | | for(i = 0; i < n; ++i){
|
| | | image im = load_image_color(paths[i], 0, 0);
|
| | | image crop = random_crop_image(im, w*scale, h*scale);
|
| | | int flip = random_gen()%2;
|
| | | if (flip) flip_image(crop);
|
| | | image resize = resize_image(crop, w, h);
|
| | | d.X.vals[i] = resize.data;
|
| | | d.y.vals[i] = crop.data;
|
| | | free_image(im);
|
| | | }
|
| | |
|
| | | if(m) free(paths);
|
| | | return d;
|
| | | }
|
| | |
|
| | | data load_data_augment(char **paths, int n, int m, char **labels, int k, tree *hierarchy, int use_flip, int min, int max, int w, int h, float angle, float aspect, float hue, float saturation, float exposure, int use_mixup, int use_blur, int show_imgs, float label_smooth_eps, int dontuse_opencv)
|
| | | {
|
| | | char **paths_stored = paths;
|
| | | if(m) paths = get_random_paths(paths, n, m);
|
| | | data d = {0};
|
| | | d.shallow = 0;
|
| | | d.X = load_image_augment_paths(paths, n, use_flip, min, max, w, h, angle, aspect, hue, saturation, exposure, dontuse_opencv);
|
| | | d.y = load_labels_paths(paths, n, labels, k, hierarchy, label_smooth_eps);
|
| | |
|
| | | if (use_mixup && rand_int(0, 1)) {
|
| | | char **paths_mix = get_random_paths(paths_stored, n, m);
|
| | | data d2 = { 0 };
|
| | | d2.shallow = 0;
|
| | | d2.X = load_image_augment_paths(paths_mix, n, use_flip, min, max, w, h, angle, aspect, hue, saturation, exposure, dontuse_opencv);
|
| | | d2.y = load_labels_paths(paths_mix, n, labels, k, hierarchy, label_smooth_eps);
|
| | | free(paths_mix);
|
| | |
|
| | | data d3 = { 0 };
|
| | | d3.shallow = 0;
|
| | | data d4 = { 0 };
|
| | | d4.shallow = 0;
|
| | | if (use_mixup >= 3) {
|
| | | char **paths_mix3 = get_random_paths(paths_stored, n, m);
|
| | | d3.X = load_image_augment_paths(paths_mix3, n, use_flip, min, max, w, h, angle, aspect, hue, saturation, exposure, dontuse_opencv);
|
| | | d3.y = load_labels_paths(paths_mix3, n, labels, k, hierarchy, label_smooth_eps);
|
| | | free(paths_mix3);
|
| | |
|
| | | char **paths_mix4 = get_random_paths(paths_stored, n, m);
|
| | | d4.X = load_image_augment_paths(paths_mix4, n, use_flip, min, max, w, h, angle, aspect, hue, saturation, exposure, dontuse_opencv);
|
| | | d4.y = load_labels_paths(paths_mix4, n, labels, k, hierarchy, label_smooth_eps);
|
| | | free(paths_mix4);
|
| | | }
|
| | |
|
| | |
|
| | | // mix
|
| | | int i, j;
|
| | | for (i = 0; i < d2.X.rows; ++i) {
|
| | |
|
| | | int mixup = use_mixup;
|
| | | if (use_mixup == 4) mixup = rand_int(2, 3); // alternate CutMix and Mosaic
|
| | |
|
| | | // MixUp -----------------------------------
|
| | | if (mixup == 1) {
|
| | | // mix images
|
| | | for (j = 0; j < d2.X.cols; ++j) {
|
| | | d.X.vals[i][j] = (d.X.vals[i][j] + d2.X.vals[i][j]) / 2.0f;
|
| | | }
|
| | |
|
| | | // mix labels
|
| | | for (j = 0; j < d2.y.cols; ++j) {
|
| | | d.y.vals[i][j] = (d.y.vals[i][j] + d2.y.vals[i][j]) / 2.0f;
|
| | | }
|
| | | }
|
| | | // CutMix -----------------------------------
|
| | | else if (mixup == 2) {
|
| | | const float min = 0.3; // 0.3*0.3 = 9%
|
| | | const float max = 0.8; // 0.8*0.8 = 64%
|
| | | const int cut_w = rand_int(w*min, w*max);
|
| | | const int cut_h = rand_int(h*min, h*max);
|
| | | const int cut_x = rand_int(0, w - cut_w - 1);
|
| | | const int cut_y = rand_int(0, h - cut_h - 1);
|
| | | const int left = cut_x;
|
| | | const int right = cut_x + cut_w;
|
| | | const int top = cut_y;
|
| | | const int bot = cut_y + cut_h;
|
| | |
|
| | | assert(cut_x >= 0 && cut_x <= w);
|
| | | assert(cut_y >= 0 && cut_y <= h);
|
| | | assert(cut_w >= 0 && cut_w <= w);
|
| | | assert(cut_h >= 0 && cut_h <= h);
|
| | |
|
| | | assert(right >= 0 && right <= w);
|
| | | assert(bot >= 0 && bot <= h);
|
| | |
|
| | | assert(top <= bot);
|
| | | assert(left <= right);
|
| | |
|
| | | const float alpha = (float)(cut_w*cut_h) / (float)(w*h);
|
| | | const float beta = 1 - alpha;
|
| | |
|
| | | int c, x, y;
|
| | | for (c = 0; c < 3; ++c) {
|
| | | for (y = top; y < bot; ++y) {
|
| | | for (x = left; x < right; ++x) {
|
| | | int j = x + y*w + c*w*h;
|
| | | d.X.vals[i][j] = d2.X.vals[i][j];
|
| | | }
|
| | | }
|
| | | }
|
| | |
|
| | | //printf("\n alpha = %f, beta = %f \n", alpha, beta);
|
| | | // mix labels
|
| | | for (j = 0; j < d.y.cols; ++j) {
|
| | | d.y.vals[i][j] = d.y.vals[i][j] * beta + d2.y.vals[i][j] * alpha;
|
| | | }
|
| | | }
|
| | | // Mosaic -----------------------------------
|
| | | else if (mixup == 3)
|
| | | {
|
| | | const float min_offset = 0.2; // 20%
|
| | | const int cut_x = rand_int(w*min_offset, w*(1 - min_offset));
|
| | | const int cut_y = rand_int(h*min_offset, h*(1 - min_offset));
|
| | |
|
| | | float s1 = (float)(cut_x * cut_y) / (w*h);
|
| | | float s2 = (float)((w - cut_x) * cut_y) / (w*h);
|
| | | float s3 = (float)(cut_x * (h - cut_y)) / (w*h);
|
| | | float s4 = (float)((w - cut_x) * (h - cut_y)) / (w*h);
|
| | |
|
| | | int c, x, y;
|
| | | for (c = 0; c < 3; ++c) {
|
| | | for (y = 0; y < h; ++y) {
|
| | | for (x = 0; x < w; ++x) {
|
| | | int j = x + y*w + c*w*h;
|
| | | if (x < cut_x && y < cut_y) d.X.vals[i][j] = d.X.vals[i][j];
|
| | | if (x >= cut_x && y < cut_y) d.X.vals[i][j] = d2.X.vals[i][j];
|
| | | if (x < cut_x && y >= cut_y) d.X.vals[i][j] = d3.X.vals[i][j];
|
| | | if (x >= cut_x && y >= cut_y) d.X.vals[i][j] = d4.X.vals[i][j];
|
| | | }
|
| | | }
|
| | | }
|
| | |
|
| | | for (j = 0; j < d.y.cols; ++j) {
|
| | | const float max_s = 1;// max_val_cmp(s1, max_val_cmp(s2, max_val_cmp(s3, s4)));
|
| | |
|
| | | d.y.vals[i][j] = d.y.vals[i][j] * s1 / max_s + d2.y.vals[i][j] * s2 / max_s + d3.y.vals[i][j] * s3 / max_s + d4.y.vals[i][j] * s4 / max_s;
|
| | | }
|
| | | }
|
| | | }
|
| | |
|
| | | free_data(d2);
|
| | |
|
| | | if (use_mixup >= 3) {
|
| | | free_data(d3);
|
| | | free_data(d4);
|
| | | }
|
| | | }
|
| | |
|
| | | #ifdef OPENCV
|
| | | if (use_blur) {
|
| | | int i;
|
| | | for (i = 0; i < d.X.rows; ++i) {
|
| | | if (random_gen() % 2) {
|
| | | image im = make_empty_image(w, h, 3);
|
| | | im.data = d.X.vals[i];
|
| | | int ksize = use_blur;
|
| | | if (use_blur == 1) ksize = 17;
|
| | | image blurred = blur_image(im, ksize);
|
| | | free_image(im);
|
| | | d.X.vals[i] = blurred.data;
|
| | | //if (i == 0) {
|
| | | // show_image(im, "Not blurred");
|
| | | // show_image(blurred, "blurred");
|
| | | // wait_until_press_key_cv();
|
| | | //}
|
| | | }
|
| | | }
|
| | | }
|
| | | #endif // OPENCV
|
| | |
|
| | | if (show_imgs) {
|
| | | int i, j;
|
| | | for (i = 0; i < d.X.rows; ++i) {
|
| | | image im = make_empty_image(w, h, 3);
|
| | | im.data = d.X.vals[i];
|
| | | char buff[1000];
|
| | | sprintf(buff, "aug_%d_%s_%d", i, basecfg((char*)paths[i]), random_gen());
|
| | | save_image(im, buff);
|
| | |
|
| | | char buff_string[1000];
|
| | | sprintf(buff_string, "\n Classes: ");
|
| | | for (j = 0; j < d.y.cols; ++j) {
|
| | | if (d.y.vals[i][j] > 0) {
|
| | | char buff_tmp[100];
|
| | | sprintf(buff_tmp, " %d (%f), ", j, d.y.vals[i][j]);
|
| | | strcat(buff_string, buff_tmp);
|
| | | }
|
| | | }
|
| | | printf("%s \n", buff_string);
|
| | |
|
| | | if (show_imgs == 1) {
|
| | | show_image(im, buff);
|
| | | wait_until_press_key_cv();
|
| | | }
|
| | | }
|
| | | printf("\nYou use flag -show_imgs, so will be saved aug_...jpg images. Click on window and press ESC button \n");
|
| | | }
|
| | |
|
| | | if (m) free(paths);
|
| | |
|
| | | return d;
|
| | | }
|
| | |
|
| | | data load_data_tag(char **paths, int n, int m, int k, int use_flip, int min, int max, int w, int h, float angle, float aspect, float hue, float saturation, float exposure)
|
| | | {
|
| | | if(m) paths = get_random_paths(paths, n, m);
|
| | | data d = {0};
|
| | | d.w = w;
|
| | | d.h = h;
|
| | | d.shallow = 0;
|
| | | d.X = load_image_augment_paths(paths, n, use_flip, min, max, w, h, angle, aspect, hue, saturation, exposure, 0);
|
| | | d.y = load_tags_paths(paths, n, k);
|
| | | if(m) free(paths);
|
| | | return d;
|
| | | }
|
| | |
|
| | | 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 = (float**)xcalloc(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 = {0};
|
| | | d.shallow = 1;
|
| | | d.X = concat_matrix(d1.X, d2.X);
|
| | | d.y = concat_matrix(d1.y, d2.y);
|
| | | return d;
|
| | | }
|
| | |
|
| | | data concat_datas(data *d, int n)
|
| | | {
|
| | | int i;
|
| | | data out = {0};
|
| | | for(i = 0; i < n; ++i){
|
| | | data newdata = concat_data(d[i], out);
|
| | | free_data(out);
|
| | | out = newdata;
|
| | | }
|
| | | return out;
|
| | | }
|
| | |
|
| | | data load_categorical_data_csv(char *filename, int target, int k)
|
| | | {
|
| | | data d = {0};
|
| | | 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 = {0};
|
| | | 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_id = bytes[0];
|
| | | y.vals[i][class_id] = 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./255);
|
| | | //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 = random_gen()%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));
|
| | | }
|
| | | }
|
| | |
|
| | | void smooth_data(data d)
|
| | | {
|
| | | int i, j;
|
| | | float scale = 1. / d.y.cols;
|
| | | float eps = .1;
|
| | | for(i = 0; i < d.y.rows; ++i){
|
| | | for(j = 0; j < d.y.cols; ++j){
|
| | | d.y.vals[i][j] = eps * scale + (1-eps) * d.y.vals[i][j];
|
| | | }
|
| | | }
|
| | | }
|
| | |
|
| | | data load_all_cifar10()
|
| | | {
|
| | | data d = {0};
|
| | | 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/cifar/cifar-10-batches-bin/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_id = bytes[0];
|
| | | y.vals[i+b*10000][class_id] = 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./255);
|
| | | smooth_data(d);
|
| | | return d;
|
| | | }
|
| | |
|
| | | data load_go(char *filename)
|
| | | {
|
| | | FILE *fp = fopen(filename, "rb");
|
| | | matrix X = make_matrix(3363059, 361);
|
| | | matrix y = make_matrix(3363059, 361);
|
| | | int row, col;
|
| | |
|
| | | if(!fp) file_error(filename);
|
| | | char *label;
|
| | | int count = 0;
|
| | | while((label = fgetl(fp))){
|
| | | int i;
|
| | | if(count == X.rows){
|
| | | X = resize_matrix(X, count*2);
|
| | | y = resize_matrix(y, count*2);
|
| | | }
|
| | | sscanf(label, "%d %d", &row, &col);
|
| | | char *board = fgetl(fp);
|
| | |
|
| | | int index = row*19 + col;
|
| | | y.vals[count][index] = 1;
|
| | |
|
| | | for(i = 0; i < 19*19; ++i){
|
| | | float val = 0;
|
| | | if(board[i] == '1') val = 1;
|
| | | else if(board[i] == '2') val = -1;
|
| | | X.vals[count][i] = val;
|
| | | }
|
| | | ++count;
|
| | | free(label);
|
| | | free(board);
|
| | | }
|
| | | X = resize_matrix(X, count);
|
| | | y = resize_matrix(y, count);
|
| | |
|
| | | data d = {0};
|
| | | d.shallow = 0;
|
| | | d.X = X;
|
| | | d.y = y;
|
| | |
|
| | |
|
| | | fclose(fp);
|
| | |
|
| | | return d;
|
| | | }
|
| | |
|
| | |
|
| | | void randomize_data(data d)
|
| | | {
|
| | | int i;
|
| | | for(i = d.X.rows-1; i > 0; --i){
|
| | | int index = random_gen()%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 get_data_part(data d, int part, int total)
|
| | | {
|
| | | data p = {0};
|
| | | p.shallow = 1;
|
| | | p.X.rows = d.X.rows * (part + 1) / total - d.X.rows * part / total;
|
| | | p.y.rows = d.y.rows * (part + 1) / total - d.y.rows * part / total;
|
| | | p.X.cols = d.X.cols;
|
| | | p.y.cols = d.y.cols;
|
| | | p.X.vals = d.X.vals + d.X.rows * part / total;
|
| | | p.y.vals = d.y.vals + d.y.rows * part / total;
|
| | | return p;
|
| | | }
|
| | |
|
| | | data get_random_data(data d, int num)
|
| | | {
|
| | | data r = {0};
|
| | | r.shallow = 1;
|
| | |
|
| | | r.X.rows = num;
|
| | | r.y.rows = num;
|
| | |
|
| | | r.X.cols = d.X.cols;
|
| | | r.y.cols = d.y.cols;
|
| | |
|
| | | r.X.vals = (float**)xcalloc(num, sizeof(float*));
|
| | | r.y.vals = (float**)xcalloc(num, sizeof(float*));
|
| | |
|
| | | int i;
|
| | | for(i = 0; i < num; ++i){
|
| | | int index = random_gen()%d.X.rows;
|
| | | r.X.vals[i] = d.X.vals[index];
|
| | | r.y.vals[i] = d.y.vals[index];
|
| | | }
|
| | | return r;
|
| | | }
|
| | |
|
| | | data *split_data(data d, int part, int total)
|
| | | {
|
| | | data* split = (data*)xcalloc(2, sizeof(data));
|
| | | int i;
|
| | | int start = part*d.X.rows/total;
|
| | | int end = (part+1)*d.X.rows/total;
|
| | | data train ={0};
|
| | | data test ={0};
|
| | | 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 = (float**)xcalloc(train.X.rows, sizeof(float*));
|
| | | test.X.vals = (float**)xcalloc(test.X.rows, sizeof(float*));
|
| | | train.y.vals = (float**)xcalloc(train.y.rows, sizeof(float*));
|
| | | test.y.vals = (float**)xcalloc(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;
|
| | | }
|
| | | #include "data.h" |
| | | #include "utils.h" |
| | | #include "image.h" |
| | | #include "dark_cuda.h" |
| | | #include "box.h" |
| | | #include "http_stream.h" |
| | | |
| | | #include <stdio.h> |
| | | #include <stdlib.h> |
| | | #include <string.h> |
| | | |
| | | extern int check_mistakes; |
| | | |
| | | #define NUMCHARS 37 |
| | | |
| | | 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 = random_gen()%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_sequential_paths(char **paths, int n, int m, int mini_batch, int augment_speed, int contrastive) |
| | | { |
| | | int speed = rand_int(1, augment_speed); |
| | | if (speed < 1) speed = 1; |
| | | char** sequentia_paths = (char**)xcalloc(n, sizeof(char*)); |
| | | int i; |
| | | pthread_mutex_lock(&mutex); |
| | | //printf("n = %d, mini_batch = %d \n", n, mini_batch); |
| | | unsigned int *start_time_indexes = (unsigned int *)xcalloc(mini_batch, sizeof(unsigned int)); |
| | | for (i = 0; i < mini_batch; ++i) { |
| | | if (contrastive && (i % 2) == 1) start_time_indexes[i] = start_time_indexes[i - 1]; |
| | | else start_time_indexes[i] = random_gen() % m; |
| | | |
| | | //printf(" start_time_indexes[i] = %u, ", start_time_indexes[i]); |
| | | } |
| | | |
| | | for (i = 0; i < n; ++i) { |
| | | do { |
| | | int time_line_index = i % mini_batch; |
| | | unsigned int index = start_time_indexes[time_line_index] % m; |
| | | start_time_indexes[time_line_index] += speed; |
| | | |
| | | //int index = random_gen() % m; |
| | | sequentia_paths[i] = paths[index]; |
| | | //printf(" index = %d, ", index); |
| | | //if(i == 0) printf("%s\n", paths[index]); |
| | | //printf(" index = %u - grp: %s \n", index, paths[index]); |
| | | if (strlen(sequentia_paths[i]) <= 4) printf(" Very small path to the image: %s \n", sequentia_paths[i]); |
| | | } while (strlen(sequentia_paths[i]) == 0); |
| | | } |
| | | free(start_time_indexes); |
| | | pthread_mutex_unlock(&mutex); |
| | | return sequentia_paths; |
| | | } |
| | | |
| | | char **get_random_paths_custom(char **paths, int n, int m, int contrastive) |
| | | { |
| | | char** random_paths = (char**)xcalloc(n, sizeof(char*)); |
| | | int i; |
| | | pthread_mutex_lock(&mutex); |
| | | int old_index = 0; |
| | | //printf("n = %d \n", n); |
| | | for(i = 0; i < n; ++i){ |
| | | do { |
| | | int index = random_gen() % m; |
| | | if (contrastive && (i % 2 == 1)) index = old_index; |
| | | else old_index = index; |
| | | random_paths[i] = paths[index]; |
| | | //if(i == 0) printf("%s\n", paths[index]); |
| | | //printf("grp: %s\n", paths[index]); |
| | | if (strlen(random_paths[i]) <= 4) printf(" Very small path to the image: %s \n", random_paths[i]); |
| | | } while (strlen(random_paths[i]) == 0); |
| | | } |
| | | pthread_mutex_unlock(&mutex); |
| | | return random_paths; |
| | | } |
| | | |
| | | char **get_random_paths(char **paths, int n, int m) |
| | | { |
| | | return get_random_paths_custom(paths, n, m, 0); |
| | | } |
| | | |
| | | char **find_replace_paths(char **paths, int n, char *find, char *replace) |
| | | { |
| | | char** replace_paths = (char**)xcalloc(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 = (float**)xcalloc(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 = (float**)xcalloc(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 use_flip, int min, int max, int w, int h, float angle, float aspect, float hue, float saturation, float exposure, int dontuse_opencv, int contrastive) |
| | | { |
| | | int i; |
| | | matrix X; |
| | | X.rows = n; |
| | | X.vals = (float**)xcalloc(X.rows, sizeof(float*)); |
| | | X.cols = 0; |
| | | |
| | | for(i = 0; i < n; ++i){ |
| | | int size = w > h ? w : h; |
| | | image im; |
| | | const int img_index = (contrastive) ? (i / 2) : i; |
| | | if(dontuse_opencv) im = load_image_stb_resize(paths[img_index], 0, 0, 3); |
| | | else im = load_image_color(paths[img_index], 0, 0); |
| | | |
| | | image crop = random_augment_image(im, angle, aspect, min, max, size); |
| | | int flip = use_flip ? random_gen() % 2 : 0; |
| | | if (flip) |
| | | flip_image(crop); |
| | | random_distort_image(crop, hue, saturation, exposure); |
| | | |
| | | image sized = resize_image(crop, w, h); |
| | | |
| | | //show_image(im, "orig"); |
| | | //show_image(sized, "sized"); |
| | | //show_image(sized, paths[img_index]); |
| | | //wait_until_press_key_cv(); |
| | | //printf("w = %d, h = %d \n", sized.w, sized.h); |
| | | |
| | | free_image(im); |
| | | free_image(crop); |
| | | X.vals[i] = sized.data; |
| | | X.cols = sized.h*sized.w*sized.c; |
| | | } |
| | | return X; |
| | | } |
| | | |
| | | |
| | | box_label *read_boxes(char *filename, int *n) |
| | | { |
| | | box_label* boxes = (box_label*)xcalloc(1, sizeof(box_label)); |
| | | FILE *file = fopen(filename, "r"); |
| | | if (!file) { |
| | | printf("Can't open label file. (This can be normal only if you use MSCOCO): %s \n", filename); |
| | | //file_error(filename); |
| | | FILE* fw = fopen("bad.list", "a"); |
| | | fwrite(filename, sizeof(char), strlen(filename), fw); |
| | | char *new_line = "\n"; |
| | | fwrite(new_line, sizeof(char), strlen(new_line), fw); |
| | | fclose(fw); |
| | | if (check_mistakes) { |
| | | printf("\n Error in read_boxes() \n"); |
| | | getchar(); |
| | | } |
| | | |
| | | *n = 0; |
| | | return boxes; |
| | | } |
| | | const int max_obj_img = 4000;// 30000; |
| | | const int img_hash = (custom_hash(filename) % max_obj_img)*max_obj_img; |
| | | //printf(" img_hash = %d, filename = %s; ", img_hash, 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 = (box_label*)xrealloc(boxes, (count + 1) * sizeof(box_label)); |
| | | boxes[count].track_id = count + img_hash; |
| | | //printf(" boxes[count].track_id = %d, count = %d \n", boxes[count].track_id, count); |
| | | 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 = random_gen()%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; |
| | | } |
| | | if ((boxes[i].x + boxes[i].w / 2) < 0 || (boxes[i].y + boxes[i].h / 2) < 0 || |
| | | (boxes[i].x - boxes[i].w / 2) > 1 || (boxes[i].y - boxes[i].h / 2) > 1) |
| | | { |
| | | 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]; |
| | | replace_image_to_label(path, 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]; |
| | | replace_image_to_label(path, 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 < .001 || h < .001) 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; |
| | | truth[index++] = 1; |
| | | |
| | | if (id < classes) truth[index+id] = 1; |
| | | index += classes; |
| | | |
| | | truth[index++] = x; |
| | | truth[index++] = y; |
| | | truth[index++] = w; |
| | | truth[index++] = h; |
| | | } |
| | | free(boxes); |
| | | } |
| | | |
| | | int fill_truth_detection(const char *path, int num_boxes, int truth_size, float *truth, int classes, int flip, float dx, float dy, float sx, float sy, |
| | | int net_w, int net_h) |
| | | { |
| | | char labelpath[4096]; |
| | | replace_image_to_label(path, labelpath); |
| | | |
| | | int count = 0; |
| | | int i; |
| | | box_label *boxes = read_boxes(labelpath, &count); |
| | | int min_w_h = 0; |
| | | float lowest_w = 1.F / net_w; |
| | | float lowest_h = 1.F / net_h; |
| | | randomize_boxes(boxes, count); |
| | | correct_boxes(boxes, count, dx, dy, sx, sy, flip); |
| | | if (count > num_boxes) count = num_boxes; |
| | | float x, y, w, h; |
| | | int id; |
| | | int sub = 0; |
| | | |
| | | 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; |
| | | int track_id = boxes[i].track_id; |
| | | |
| | | // not detect small objects |
| | | //if ((w < 0.001F || h < 0.001F)) continue; |
| | | // if truth (box for object) is smaller than 1x1 pix |
| | | char buff[256]; |
| | | if (id >= classes) { |
| | | printf("\n Wrong annotation: class_id = %d. But class_id should be [from 0 to %d], file: %s \n", id, (classes-1), labelpath); |
| | | sprintf(buff, "echo %s \"Wrong annotation: class_id = %d. But class_id should be [from 0 to %d]\" >> bad_label.list", labelpath, id, (classes-1)); |
| | | system(buff); |
| | | if (check_mistakes) getchar(); |
| | | ++sub; |
| | | continue; |
| | | } |
| | | if ((w < lowest_w || h < lowest_h)) { |
| | | //sprintf(buff, "echo %s \"Very small object: w < lowest_w OR h < lowest_h\" >> bad_label.list", labelpath); |
| | | //system(buff); |
| | | ++sub; |
| | | continue; |
| | | } |
| | | if (x == 999999 || y == 999999) { |
| | | printf("\n Wrong annotation: x = 0, y = 0, < 0 or > 1, file: %s \n", labelpath); |
| | | sprintf(buff, "echo %s \"Wrong annotation: x = 0 or y = 0\" >> bad_label.list", labelpath); |
| | | system(buff); |
| | | ++sub; |
| | | if (check_mistakes) getchar(); |
| | | continue; |
| | | } |
| | | if (x <= 0 || x > 1 || y <= 0 || y > 1) { |
| | | printf("\n Wrong annotation: x = %f, y = %f, file: %s \n", x, y, labelpath); |
| | | sprintf(buff, "echo %s \"Wrong annotation: x = %f, y = %f\" >> bad_label.list", labelpath, x, y); |
| | | system(buff); |
| | | ++sub; |
| | | if (check_mistakes) getchar(); |
| | | continue; |
| | | } |
| | | if (w > 1) { |
| | | printf("\n Wrong annotation: w = %f, file: %s \n", w, labelpath); |
| | | sprintf(buff, "echo %s \"Wrong annotation: w = %f\" >> bad_label.list", labelpath, w); |
| | | system(buff); |
| | | w = 1; |
| | | if (check_mistakes) getchar(); |
| | | } |
| | | if (h > 1) { |
| | | printf("\n Wrong annotation: h = %f, file: %s \n", h, labelpath); |
| | | sprintf(buff, "echo %s \"Wrong annotation: h = %f\" >> bad_label.list", labelpath, h); |
| | | system(buff); |
| | | h = 1; |
| | | if (check_mistakes) getchar(); |
| | | } |
| | | if (x == 0) x += lowest_w; |
| | | if (y == 0) y += lowest_h; |
| | | |
| | | truth[(i-sub)*truth_size +0] = x; |
| | | truth[(i-sub)*truth_size +1] = y; |
| | | truth[(i-sub)*truth_size +2] = w; |
| | | truth[(i-sub)*truth_size +3] = h; |
| | | truth[(i-sub)*truth_size +4] = id; |
| | | truth[(i-sub)*truth_size +5] = track_id; |
| | | //float val = track_id; |
| | | //printf(" i = %d, sub = %d, truth_size = %d, track_id = %d, %f, %f\n", i, sub, truth_size, track_id, truth[(i - sub)*truth_size + 5], val); |
| | | |
| | | if (min_w_h == 0) min_w_h = w*net_w; |
| | | if (min_w_h > w*net_w) min_w_h = w*net_w; |
| | | if (min_w_h > h*net_h) min_w_h = h*net_h; |
| | | } |
| | | free(boxes); |
| | | return min_w_h; |
| | | } |
| | | |
| | | |
| | | void print_letters(float *pred, int n) |
| | | { |
| | | int i; |
| | | for(i = 0; i < n; ++i){ |
| | | int index = max_index(pred+i*NUMCHARS, NUMCHARS); |
| | | printf("%c", int_to_alphanum(index)); |
| | | } |
| | | printf("\n"); |
| | | } |
| | | |
| | | void fill_truth_captcha(char *path, int n, float *truth) |
| | | { |
| | | char *begin = strrchr(path, '/'); |
| | | ++begin; |
| | | int i; |
| | | for(i = 0; i < strlen(begin) && i < n && begin[i] != '.'; ++i){ |
| | | int index = alphanum_to_int(begin[i]); |
| | | if(index > 35) printf("Bad %c\n", begin[i]); |
| | | truth[i*NUMCHARS+index] = 1; |
| | | } |
| | | for(;i < n; ++i){ |
| | | truth[i*NUMCHARS + NUMCHARS-1] = 1; |
| | | } |
| | | } |
| | | |
| | | 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 = {0}; |
| | | d.shallow = 0; |
| | | d.X = load_image_paths(paths, n, w, h); |
| | | d.y = make_matrix(n, k*NUMCHARS); |
| | | int i; |
| | | for(i = 0; i < n; ++i){ |
| | | fill_truth_captcha(paths[i], k, d.y.vals[i]); |
| | | } |
| | | if(m) free(paths); |
| | | return d; |
| | | } |
| | | |
| | | 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 = {0}; |
| | | d.shallow = 0; |
| | | d.X = load_image_paths(paths, n, w, h); |
| | | d.X.cols = 17100; |
| | | d.y = d.X; |
| | | if(m) free(paths); |
| | | return d; |
| | | } |
| | | |
| | | void fill_truth(char *path, char **labels, int k, float *truth) |
| | | { |
| | | int i; |
| | | 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("Too many or too few labels: %d, %s\n", count, path); |
| | | count = 0; |
| | | for (i = 0; i < k; ++i) { |
| | | if (strstr(path, labels[i])) { |
| | | printf("\t label %d: %s \n", count, labels[i]); |
| | | count++; |
| | | } |
| | | } |
| | | } |
| | | } |
| | | |
| | | void fill_truth_smooth(char *path, char **labels, int k, float *truth, float label_smooth_eps) |
| | | { |
| | | int i; |
| | | memset(truth, 0, k * sizeof(float)); |
| | | int count = 0; |
| | | for (i = 0; i < k; ++i) { |
| | | if (strstr(path, labels[i])) { |
| | | truth[i] = (1 - label_smooth_eps); |
| | | ++count; |
| | | } |
| | | else { |
| | | truth[i] = label_smooth_eps / (k - 1); |
| | | } |
| | | } |
| | | if (count != 1) { |
| | | printf("Too many or too few labels: %d, %s\n", count, path); |
| | | count = 0; |
| | | for (i = 0; i < k; ++i) { |
| | | if (strstr(path, labels[i])) { |
| | | printf("\t label %d: %s \n", count, labels[i]); |
| | | count++; |
| | | } |
| | | } |
| | | } |
| | | } |
| | | |
| | | void fill_hierarchy(float *truth, int k, tree *hierarchy) |
| | | { |
| | | int j; |
| | | for(j = 0; j < k; ++j){ |
| | | if(truth[j]){ |
| | | int parent = hierarchy->parent[j]; |
| | | while(parent >= 0){ |
| | | truth[parent] = 1; |
| | | parent = hierarchy->parent[parent]; |
| | | } |
| | | } |
| | | } |
| | | int i; |
| | | int count = 0; |
| | | for(j = 0; j < hierarchy->groups; ++j){ |
| | | //printf("%d\n", count); |
| | | int mask = 1; |
| | | for(i = 0; i < hierarchy->group_size[j]; ++i){ |
| | | if(truth[count + i]){ |
| | | mask = 0; |
| | | break; |
| | | } |
| | | } |
| | | if (mask) { |
| | | for(i = 0; i < hierarchy->group_size[j]; ++i){ |
| | | truth[count + i] = SECRET_NUM; |
| | | } |
| | | } |
| | | count += hierarchy->group_size[j]; |
| | | } |
| | | } |
| | | |
| | | int find_max(float *arr, int size) { |
| | | int i; |
| | | float max = 0; |
| | | int n = 0; |
| | | for (i = 0; i < size; ++i) { |
| | | if (arr[i] > max) { |
| | | max = arr[i]; |
| | | n = i; |
| | | } |
| | | } |
| | | return n; |
| | | } |
| | | |
| | | matrix load_labels_paths(char **paths, int n, char **labels, int k, tree *hierarchy, float label_smooth_eps, int contrastive) |
| | | { |
| | | matrix y = make_matrix(n, k); |
| | | int i; |
| | | if (labels) { |
| | | // supervised learning |
| | | for (i = 0; i < n; ++i) { |
| | | const int img_index = (contrastive) ? (i / 2) : i; |
| | | fill_truth_smooth(paths[img_index], labels, k, y.vals[i], label_smooth_eps); |
| | | //printf(" n = %d, i = %d, img_index = %d, class_id = %d \n", n, i, img_index, find_max(y.vals[i], k)); |
| | | if (hierarchy) { |
| | | fill_hierarchy(y.vals[i], k, hierarchy); |
| | | } |
| | | } |
| | | } else { |
| | | // unsupervised learning |
| | | for (i = 0; i < n; ++i) { |
| | | const int img_index = (contrastive) ? (i / 2) : i; |
| | | const uintptr_t path_p = (uintptr_t)paths[img_index];// abs(random_gen()); |
| | | const int class_id = path_p % k; |
| | | int l; |
| | | for (l = 0; l < k; ++l) y.vals[i][l] = 0; |
| | | y.vals[i][class_id] = 1; |
| | | } |
| | | } |
| | | return y; |
| | | } |
| | | |
| | | matrix load_tags_paths(char **paths, int n, int k) |
| | | { |
| | | matrix y = make_matrix(n, k); |
| | | int i; |
| | | int count = 0; |
| | | for(i = 0; i < n; ++i){ |
| | | char label[4096]; |
| | | find_replace(paths[i], "imgs", "labels", label); |
| | | find_replace(label, "_iconl.jpeg", ".txt", label); |
| | | FILE *file = fopen(label, "r"); |
| | | if(!file){ |
| | | find_replace(label, "labels", "labels2", label); |
| | | file = fopen(label, "r"); |
| | | if(!file) continue; |
| | | } |
| | | ++count; |
| | | int tag; |
| | | while(fscanf(file, "%d", &tag) == 1){ |
| | | if(tag < k){ |
| | | y.vals[i][tag] = 1; |
| | | } |
| | | } |
| | | fclose(file); |
| | | } |
| | | printf("%d/%d\n", count, n); |
| | | return y; |
| | | } |
| | | |
| | | char **get_labels_custom(char *filename, int *size) |
| | | { |
| | | list *plist = get_paths(filename); |
| | | if(size) *size = plist->size; |
| | | char **labels = (char **)list_to_array(plist); |
| | | free_list(plist); |
| | | return labels; |
| | | } |
| | | |
| | | char **get_labels(char *filename) |
| | | { |
| | | return get_labels_custom(filename, NULL); |
| | | } |
| | | |
| | | 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_region(int n, char **paths, int m, int w, int h, int size, int classes, float jitter, float hue, float saturation, float exposure) |
| | | { |
| | | char **random_paths = get_random_paths(paths, n, m); |
| | | int i; |
| | | data d = {0}; |
| | | d.shallow = 0; |
| | | |
| | | d.X.rows = n; |
| | | d.X.vals = (float**)xcalloc(d.X.rows, sizeof(float*)); |
| | | d.X.cols = h*w*3; |
| | | |
| | | |
| | | int k = size*size*(5+classes); |
| | | d.y = make_matrix(n, k); |
| | | for(i = 0; i < n; ++i){ |
| | | image orig = load_image_color(random_paths[i], 0, 0); |
| | | |
| | | int oh = orig.h; |
| | | int ow = orig.w; |
| | | |
| | | int dw = (ow*jitter); |
| | | int dh = (oh*jitter); |
| | | |
| | | int pleft = rand_uniform(-dw, dw); |
| | | int pright = rand_uniform(-dw, dw); |
| | | int ptop = rand_uniform(-dh, dh); |
| | | int pbot = rand_uniform(-dh, dh); |
| | | |
| | | int swidth = ow - pleft - pright; |
| | | int sheight = oh - ptop - pbot; |
| | | |
| | | float sx = (float)swidth / ow; |
| | | float sy = (float)sheight / oh; |
| | | |
| | | int flip = random_gen()%2; |
| | | image cropped = crop_image(orig, pleft, ptop, swidth, sheight); |
| | | |
| | | float dx = ((float)pleft/ow)/sx; |
| | | float dy = ((float)ptop /oh)/sy; |
| | | |
| | | image sized = resize_image(cropped, w, h); |
| | | if(flip) flip_image(sized); |
| | | random_distort_image(sized, hue, saturation, exposure); |
| | | d.X.vals[i] = sized.data; |
| | | |
| | | fill_truth_region(random_paths[i], d.y.vals[i], classes, size, flip, dx, dy, 1./sx, 1./sy); |
| | | |
| | | free_image(orig); |
| | | free_image(cropped); |
| | | } |
| | | free(random_paths); |
| | | return d; |
| | | } |
| | | |
| | | data load_data_compare(int n, char **paths, int m, int classes, int w, int h) |
| | | { |
| | | if(m) paths = get_random_paths(paths, 2*n, m); |
| | | int i,j; |
| | | data d = {0}; |
| | | d.shallow = 0; |
| | | |
| | | d.X.rows = n; |
| | | d.X.vals = (float**)xcalloc(d.X.rows, sizeof(float*)); |
| | | d.X.cols = h*w*6; |
| | | |
| | | int k = 2*(classes); |
| | | d.y = make_matrix(n, k); |
| | | for(i = 0; i < n; ++i){ |
| | | image im1 = load_image_color(paths[i*2], w, h); |
| | | image im2 = load_image_color(paths[i*2+1], w, h); |
| | | |
| | | d.X.vals[i] = (float*)xcalloc(d.X.cols, sizeof(float)); |
| | | memcpy(d.X.vals[i], im1.data, h*w*3*sizeof(float)); |
| | | memcpy(d.X.vals[i] + h*w*3, im2.data, h*w*3*sizeof(float)); |
| | | |
| | | int id; |
| | | float iou; |
| | | |
| | | char imlabel1[4096]; |
| | | char imlabel2[4096]; |
| | | find_replace(paths[i*2], "imgs", "labels", imlabel1); |
| | | find_replace(imlabel1, "jpg", "txt", imlabel1); |
| | | FILE *fp1 = fopen(imlabel1, "r"); |
| | | |
| | | while(fscanf(fp1, "%d %f", &id, &iou) == 2){ |
| | | if (d.y.vals[i][2*id] < iou) d.y.vals[i][2*id] = iou; |
| | | } |
| | | |
| | | find_replace(paths[i*2+1], "imgs", "labels", imlabel2); |
| | | find_replace(imlabel2, "jpg", "txt", imlabel2); |
| | | FILE *fp2 = fopen(imlabel2, "r"); |
| | | |
| | | while(fscanf(fp2, "%d %f", &id, &iou) == 2){ |
| | | if (d.y.vals[i][2*id + 1] < iou) d.y.vals[i][2*id + 1] = iou; |
| | | } |
| | | |
| | | for (j = 0; j < classes; ++j){ |
| | | if (d.y.vals[i][2*j] > .5 && d.y.vals[i][2*j+1] < .5){ |
| | | d.y.vals[i][2*j] = 1; |
| | | d.y.vals[i][2*j+1] = 0; |
| | | } else if (d.y.vals[i][2*j] < .5 && d.y.vals[i][2*j+1] > .5){ |
| | | d.y.vals[i][2*j] = 0; |
| | | d.y.vals[i][2*j+1] = 1; |
| | | } else { |
| | | d.y.vals[i][2*j] = SECRET_NUM; |
| | | d.y.vals[i][2*j+1] = SECRET_NUM; |
| | | } |
| | | } |
| | | fclose(fp1); |
| | | fclose(fp2); |
| | | |
| | | free_image(im1); |
| | | free_image(im2); |
| | | } |
| | | if(m) free(paths); |
| | | return d; |
| | | } |
| | | |
| | | data load_data_swag(char **paths, int n, int classes, float jitter) |
| | | { |
| | | int index = random_gen()%n; |
| | | char *random_path = paths[index]; |
| | | |
| | | image orig = load_image_color(random_path, 0, 0); |
| | | int h = orig.h; |
| | | int w = orig.w; |
| | | |
| | | data d = {0}; |
| | | d.shallow = 0; |
| | | d.w = w; |
| | | d.h = h; |
| | | |
| | | d.X.rows = 1; |
| | | d.X.vals = (float**)xcalloc(d.X.rows, sizeof(float*)); |
| | | d.X.cols = h*w*3; |
| | | |
| | | int k = (4+classes)*30; |
| | | d.y = make_matrix(1, k); |
| | | |
| | | int dw = w*jitter; |
| | | int dh = h*jitter; |
| | | |
| | | int pleft = rand_uniform(-dw, dw); |
| | | int pright = rand_uniform(-dw, dw); |
| | | int ptop = rand_uniform(-dh, dh); |
| | | int pbot = rand_uniform(-dh, dh); |
| | | |
| | | int swidth = w - pleft - pright; |
| | | int sheight = h - ptop - pbot; |
| | | |
| | | float sx = (float)swidth / w; |
| | | float sy = (float)sheight / h; |
| | | |
| | | int flip = random_gen()%2; |
| | | image cropped = crop_image(orig, pleft, ptop, swidth, sheight); |
| | | |
| | | float dx = ((float)pleft/w)/sx; |
| | | float dy = ((float)ptop /h)/sy; |
| | | |
| | | image sized = resize_image(cropped, w, h); |
| | | if(flip) flip_image(sized); |
| | | d.X.vals[0] = sized.data; |
| | | |
| | | fill_truth_swag(random_path, d.y.vals[0], classes, flip, dx, dy, 1./sx, 1./sy); |
| | | |
| | | free_image(orig); |
| | | free_image(cropped); |
| | | |
| | | return d; |
| | | } |
| | | |
| | | void blend_truth(float *new_truth, int boxes, int truth_size, float *old_truth) |
| | | { |
| | | int count_new_truth = 0; |
| | | int t; |
| | | for (t = 0; t < boxes; ++t) { |
| | | float x = new_truth[t*truth_size]; |
| | | if (!x) break; |
| | | count_new_truth++; |
| | | |
| | | } |
| | | for (t = count_new_truth; t < boxes; ++t) { |
| | | float *new_truth_ptr = new_truth + t*truth_size; |
| | | float *old_truth_ptr = old_truth + (t - count_new_truth)*truth_size; |
| | | float x = old_truth_ptr[0]; |
| | | if (!x) break; |
| | | |
| | | new_truth_ptr[0] = old_truth_ptr[0]; |
| | | new_truth_ptr[1] = old_truth_ptr[1]; |
| | | new_truth_ptr[2] = old_truth_ptr[2]; |
| | | new_truth_ptr[3] = old_truth_ptr[3]; |
| | | new_truth_ptr[4] = old_truth_ptr[4]; |
| | | } |
| | | //printf("\n was %d bboxes, now %d bboxes \n", count_new_truth, t); |
| | | } |
| | | |
| | | |
| | | void blend_truth_mosaic(float *new_truth, int boxes, int truth_size, float *old_truth, int w, int h, float cut_x, float cut_y, int i_mixup, |
| | | int left_shift, int right_shift, int top_shift, int bot_shift, |
| | | int net_w, int net_h, int mosaic_bound) |
| | | { |
| | | const float lowest_w = 1.F / net_w; |
| | | const float lowest_h = 1.F / net_h; |
| | | |
| | | int count_new_truth = 0; |
| | | int t; |
| | | for (t = 0; t < boxes; ++t) { |
| | | float x = new_truth[t*truth_size]; |
| | | if (!x) break; |
| | | count_new_truth++; |
| | | |
| | | } |
| | | int new_t = count_new_truth; |
| | | for (t = count_new_truth; t < boxes; ++t) { |
| | | float *new_truth_ptr = new_truth + new_t*truth_size; |
| | | new_truth_ptr[0] = 0; |
| | | float *old_truth_ptr = old_truth + (t - count_new_truth)*truth_size; |
| | | float x = old_truth_ptr[0]; |
| | | if (!x) break; |
| | | |
| | | float xb = old_truth_ptr[0]; |
| | | float yb = old_truth_ptr[1]; |
| | | float wb = old_truth_ptr[2]; |
| | | float hb = old_truth_ptr[3]; |
| | | |
| | | |
| | | |
| | | // shift 4 images |
| | | if (i_mixup == 0) { |
| | | xb = xb - (float)(w - cut_x - right_shift) / w; |
| | | yb = yb - (float)(h - cut_y - bot_shift) / h; |
| | | } |
| | | if (i_mixup == 1) { |
| | | xb = xb + (float)(cut_x - left_shift) / w; |
| | | yb = yb - (float)(h - cut_y - bot_shift) / h; |
| | | } |
| | | if (i_mixup == 2) { |
| | | xb = xb - (float)(w - cut_x - right_shift) / w; |
| | | yb = yb + (float)(cut_y - top_shift) / h; |
| | | } |
| | | if (i_mixup == 3) { |
| | | xb = xb + (float)(cut_x - left_shift) / w; |
| | | yb = yb + (float)(cut_y - top_shift) / h; |
| | | } |
| | | |
| | | int left = (xb - wb / 2)*w; |
| | | int right = (xb + wb / 2)*w; |
| | | int top = (yb - hb / 2)*h; |
| | | int bot = (yb + hb / 2)*h; |
| | | |
| | | if(mosaic_bound) |
| | | { |
| | | // fix out of Mosaic-bound |
| | | float left_bound = 0, right_bound = 0, top_bound = 0, bot_bound = 0; |
| | | if (i_mixup == 0) { |
| | | left_bound = 0; |
| | | right_bound = cut_x; |
| | | top_bound = 0; |
| | | bot_bound = cut_y; |
| | | } |
| | | if (i_mixup == 1) { |
| | | left_bound = cut_x; |
| | | right_bound = w; |
| | | top_bound = 0; |
| | | bot_bound = cut_y; |
| | | } |
| | | if (i_mixup == 2) { |
| | | left_bound = 0; |
| | | right_bound = cut_x; |
| | | top_bound = cut_y; |
| | | bot_bound = h; |
| | | } |
| | | if (i_mixup == 3) { |
| | | left_bound = cut_x; |
| | | right_bound = w; |
| | | top_bound = cut_y; |
| | | bot_bound = h; |
| | | } |
| | | |
| | | |
| | | if (left < left_bound) { |
| | | //printf(" i_mixup = %d, left = %d, left_bound = %f \n", i_mixup, left, left_bound); |
| | | left = left_bound; |
| | | } |
| | | if (right > right_bound) { |
| | | //printf(" i_mixup = %d, right = %d, right_bound = %f \n", i_mixup, right, right_bound); |
| | | right = right_bound; |
| | | } |
| | | if (top < top_bound) top = top_bound; |
| | | if (bot > bot_bound) bot = bot_bound; |
| | | |
| | | |
| | | xb = ((float)(right + left) / 2) / w; |
| | | wb = ((float)(right - left)) / w; |
| | | yb = ((float)(bot + top) / 2) / h; |
| | | hb = ((float)(bot - top)) / h; |
| | | } |
| | | else |
| | | { |
| | | // fix out of bound |
| | | if (left < 0) { |
| | | float diff = (float)left / w; |
| | | xb = xb - diff / 2; |
| | | wb = wb + diff; |
| | | } |
| | | |
| | | if (right > w) { |
| | | float diff = (float)(right - w) / w; |
| | | xb = xb - diff / 2; |
| | | wb = wb - diff; |
| | | } |
| | | |
| | | if (top < 0) { |
| | | float diff = (float)top / h; |
| | | yb = yb - diff / 2; |
| | | hb = hb + diff; |
| | | } |
| | | |
| | | if (bot > h) { |
| | | float diff = (float)(bot - h) / h; |
| | | yb = yb - diff / 2; |
| | | hb = hb - diff; |
| | | } |
| | | |
| | | left = (xb - wb / 2)*w; |
| | | right = (xb + wb / 2)*w; |
| | | top = (yb - hb / 2)*h; |
| | | bot = (yb + hb / 2)*h; |
| | | } |
| | | |
| | | |
| | | // leave only within the image |
| | | if(left >= 0 && right <= w && top >= 0 && bot <= h && |
| | | wb > 0 && wb < 1 && hb > 0 && hb < 1 && |
| | | xb > 0 && xb < 1 && yb > 0 && yb < 1 && |
| | | wb > lowest_w && hb > lowest_h) |
| | | { |
| | | new_truth_ptr[0] = xb; |
| | | new_truth_ptr[1] = yb; |
| | | new_truth_ptr[2] = wb; |
| | | new_truth_ptr[3] = hb; |
| | | new_truth_ptr[4] = old_truth_ptr[4]; |
| | | new_t++; |
| | | } |
| | | } |
| | | //printf("\n was %d bboxes, now %d bboxes \n", count_new_truth, t); |
| | | } |
| | | |
| | | #ifdef OPENCV |
| | | |
| | | #include "http_stream.h" |
| | | |
| | | data load_data_detection(int n, char **paths, int m, int w, int h, int c, int boxes, int truth_size, int classes, int use_flip, int use_gaussian_noise, int use_blur, int use_mixup, |
| | | float jitter, float resize, float hue, float saturation, float exposure, int mini_batch, int track, int augment_speed, int letter_box, int mosaic_bound, int contrastive, int contrastive_jit_flip, int contrastive_color, int show_imgs) |
| | | { |
| | | const int random_index = random_gen(); |
| | | c = c ? c : 3; |
| | | |
| | | if (use_mixup == 2 || use_mixup == 4) { |
| | | printf("\n cutmix=1 - isn't supported for Detector (use cutmix=1 only for Classifier) \n"); |
| | | if (check_mistakes) getchar(); |
| | | if(use_mixup == 2) use_mixup = 0; |
| | | else use_mixup = 3; |
| | | } |
| | | if (use_mixup == 3 && letter_box) { |
| | | //printf("\n Combination: letter_box=1 & mosaic=1 - isn't supported, use only 1 of these parameters \n"); |
| | | //if (check_mistakes) getchar(); |
| | | //exit(0); |
| | | } |
| | | if (random_gen() % 2 == 0) use_mixup = 0; |
| | | int i; |
| | | |
| | | int *cut_x = NULL, *cut_y = NULL; |
| | | if (use_mixup == 3) { |
| | | cut_x = (int*)calloc(n, sizeof(int)); |
| | | cut_y = (int*)calloc(n, sizeof(int)); |
| | | const float min_offset = 0.2; // 20% |
| | | for (i = 0; i < n; ++i) { |
| | | cut_x[i] = rand_int(w*min_offset, w*(1 - min_offset)); |
| | | cut_y[i] = rand_int(h*min_offset, h*(1 - min_offset)); |
| | | } |
| | | } |
| | | |
| | | data d = {0}; |
| | | d.shallow = 0; |
| | | |
| | | d.X.rows = n; |
| | | d.X.vals = (float**)xcalloc(d.X.rows, sizeof(float*)); |
| | | d.X.cols = h*w*c; |
| | | |
| | | float r1 = 0, r2 = 0, r3 = 0, r4 = 0, r_scale = 0; |
| | | float resize_r1 = 0, resize_r2 = 0; |
| | | float dhue = 0, dsat = 0, dexp = 0, flip = 0, blur = 0; |
| | | int augmentation_calculated = 0, gaussian_noise = 0; |
| | | |
| | | d.y = make_matrix(n, truth_size*boxes); |
| | | int i_mixup = 0; |
| | | for (i_mixup = 0; i_mixup <= use_mixup; i_mixup++) { |
| | | if (i_mixup) augmentation_calculated = 0; // recalculate augmentation for the 2nd sequence if(track==1) |
| | | |
| | | char **random_paths; |
| | | if (track) random_paths = get_sequential_paths(paths, n, m, mini_batch, augment_speed, contrastive); |
| | | else random_paths = get_random_paths_custom(paths, n, m, contrastive); |
| | | |
| | | for (i = 0; i < n; ++i) { |
| | | float *truth = (float*)xcalloc(truth_size * boxes, sizeof(float)); |
| | | const char *filename = random_paths[i]; |
| | | |
| | | int flag = (c >= 3); |
| | | mat_cv *src; |
| | | src = load_image_mat_cv(filename, flag); |
| | | if (src == NULL) { |
| | | printf("\n Error in load_data_detection() - OpenCV \n"); |
| | | fflush(stdout); |
| | | if (check_mistakes) { |
| | | getchar(); |
| | | } |
| | | continue; |
| | | } |
| | | |
| | | int oh = get_height_mat(src); |
| | | int ow = get_width_mat(src); |
| | | |
| | | int dw = (ow*jitter); |
| | | int dh = (oh*jitter); |
| | | |
| | | float resize_down = resize, resize_up = resize; |
| | | if (resize_down > 1.0) resize_down = 1 / resize_down; |
| | | int min_rdw = ow*(1 - (1 / resize_down)) / 2; // < 0 |
| | | int min_rdh = oh*(1 - (1 / resize_down)) / 2; // < 0 |
| | | |
| | | if (resize_up < 1.0) resize_up = 1 / resize_up; |
| | | int max_rdw = ow*(1 - (1 / resize_up)) / 2; // > 0 |
| | | int max_rdh = oh*(1 - (1 / resize_up)) / 2; // > 0 |
| | | //printf(" down = %f, up = %f \n", (1 - (1 / resize_down)) / 2, (1 - (1 / resize_up)) / 2); |
| | | |
| | | if (!augmentation_calculated || !track) |
| | | { |
| | | augmentation_calculated = 1; |
| | | resize_r1 = random_float(); |
| | | resize_r2 = random_float(); |
| | | |
| | | if (!contrastive || contrastive_jit_flip || i % 2 == 0) |
| | | { |
| | | r1 = random_float(); |
| | | r2 = random_float(); |
| | | r3 = random_float(); |
| | | r4 = random_float(); |
| | | |
| | | flip = use_flip ? random_gen() % 2 : 0; |
| | | } |
| | | |
| | | r_scale = random_float(); |
| | | |
| | | if (!contrastive || contrastive_color || i % 2 == 0) |
| | | { |
| | | dhue = rand_uniform_strong(-hue, hue); |
| | | dsat = rand_scale(saturation); |
| | | dexp = rand_scale(exposure); |
| | | } |
| | | |
| | | if (use_blur) { |
| | | int tmp_blur = rand_int(0, 2); // 0 - disable, 1 - blur background, 2 - blur the whole image |
| | | if (tmp_blur == 0) blur = 0; |
| | | else if (tmp_blur == 1) blur = 1; |
| | | else blur = use_blur; |
| | | } |
| | | |
| | | if (use_gaussian_noise && rand_int(0, 1) == 1) gaussian_noise = use_gaussian_noise; |
| | | else gaussian_noise = 0; |
| | | } |
| | | |
| | | int pleft = rand_precalc_random(-dw, dw, r1); |
| | | int pright = rand_precalc_random(-dw, dw, r2); |
| | | int ptop = rand_precalc_random(-dh, dh, r3); |
| | | int pbot = rand_precalc_random(-dh, dh, r4); |
| | | |
| | | if (resize < 1) { |
| | | // downsize only |
| | | pleft += rand_precalc_random(min_rdw, 0, resize_r1); |
| | | pright += rand_precalc_random(min_rdw, 0, resize_r2); |
| | | ptop += rand_precalc_random(min_rdh, 0, resize_r1); |
| | | pbot += rand_precalc_random(min_rdh, 0, resize_r2); |
| | | } |
| | | else { |
| | | pleft += rand_precalc_random(min_rdw, max_rdw, resize_r1); |
| | | pright += rand_precalc_random(min_rdw, max_rdw, resize_r2); |
| | | ptop += rand_precalc_random(min_rdh, max_rdh, resize_r1); |
| | | pbot += rand_precalc_random(min_rdh, max_rdh, resize_r2); |
| | | } |
| | | |
| | | //printf("\n pleft = %d, pright = %d, ptop = %d, pbot = %d, ow = %d, oh = %d \n", pleft, pright, ptop, pbot, ow, oh); |
| | | |
| | | //float scale = rand_precalc_random(.25, 2, r_scale); // unused currently |
| | | //printf(" letter_box = %d \n", letter_box); |
| | | |
| | | if (letter_box) |
| | | { |
| | | float img_ar = (float)ow / (float)oh; |
| | | float net_ar = (float)w / (float)h; |
| | | float result_ar = img_ar / net_ar; |
| | | //printf(" ow = %d, oh = %d, w = %d, h = %d, img_ar = %f, net_ar = %f, result_ar = %f \n", ow, oh, w, h, img_ar, net_ar, result_ar); |
| | | if (result_ar > 1) // sheight - should be increased |
| | | { |
| | | float oh_tmp = ow / net_ar; |
| | | float delta_h = (oh_tmp - oh)/2; |
| | | ptop = ptop - delta_h; |
| | | pbot = pbot - delta_h; |
| | | //printf(" result_ar = %f, oh_tmp = %f, delta_h = %d, ptop = %f, pbot = %f \n", result_ar, oh_tmp, delta_h, ptop, pbot); |
| | | } |
| | | else // swidth - should be increased |
| | | { |
| | | float ow_tmp = oh * net_ar; |
| | | float delta_w = (ow_tmp - ow)/2; |
| | | pleft = pleft - delta_w; |
| | | pright = pright - delta_w; |
| | | //printf(" result_ar = %f, ow_tmp = %f, delta_w = %d, pleft = %f, pright = %f \n", result_ar, ow_tmp, delta_w, pleft, pright); |
| | | } |
| | | |
| | | //printf("\n pleft = %d, pright = %d, ptop = %d, pbot = %d, ow = %d, oh = %d \n", pleft, pright, ptop, pbot, ow, oh); |
| | | } |
| | | |
| | | // move each 2nd image to the corner - so that most of it was visible |
| | | if (use_mixup == 3 && random_gen() % 2 == 0) { |
| | | if (flip) { |
| | | if (i_mixup == 0) pleft += pright, pright = 0, pbot += ptop, ptop = 0; |
| | | if (i_mixup == 1) pright += pleft, pleft = 0, pbot += ptop, ptop = 0; |
| | | if (i_mixup == 2) pleft += pright, pright = 0, ptop += pbot, pbot = 0; |
| | | if (i_mixup == 3) pright += pleft, pleft = 0, ptop += pbot, pbot = 0; |
| | | } |
| | | else { |
| | | if (i_mixup == 0) pright += pleft, pleft = 0, pbot += ptop, ptop = 0; |
| | | if (i_mixup == 1) pleft += pright, pright = 0, pbot += ptop, ptop = 0; |
| | | if (i_mixup == 2) pright += pleft, pleft = 0, ptop += pbot, pbot = 0; |
| | | if (i_mixup == 3) pleft += pright, pright = 0, ptop += pbot, pbot = 0; |
| | | } |
| | | } |
| | | |
| | | int swidth = ow - pleft - pright; |
| | | int sheight = oh - ptop - pbot; |
| | | |
| | | float sx = (float)swidth / ow; |
| | | float sy = (float)sheight / oh; |
| | | |
| | | float dx = ((float)pleft / ow) / sx; |
| | | float dy = ((float)ptop / oh) / sy; |
| | | |
| | | |
| | | int min_w_h = fill_truth_detection(filename, boxes, truth_size, truth, classes, flip, dx, dy, 1. / sx, 1. / sy, w, h); |
| | | //for (int z = 0; z < boxes; ++z) if(truth[z*truth_size] > 0) printf(" track_id = %f \n", truth[z*truth_size + 5]); |
| | | //printf(" truth_size = %d \n", truth_size); |
| | | |
| | | if ((min_w_h / 8) < blur && blur > 1) blur = min_w_h / 8; // disable blur if one of the objects is too small |
| | | |
| | | image ai = image_data_augmentation(src, w, h, pleft, ptop, swidth, sheight, flip, dhue, dsat, dexp, |
| | | gaussian_noise, blur, boxes, truth_size, truth); |
| | | |
| | | if (use_mixup == 0) { |
| | | d.X.vals[i] = ai.data; |
| | | memcpy(d.y.vals[i], truth, truth_size * boxes * sizeof(float)); |
| | | } |
| | | else if (use_mixup == 1) { |
| | | if (i_mixup == 0) { |
| | | d.X.vals[i] = ai.data; |
| | | memcpy(d.y.vals[i], truth, truth_size * boxes * sizeof(float)); |
| | | } |
| | | else if (i_mixup == 1) { |
| | | image old_img = make_empty_image(w, h, c); |
| | | old_img.data = d.X.vals[i]; |
| | | //show_image(ai, "new"); |
| | | //show_image(old_img, "old"); |
| | | //wait_until_press_key_cv(); |
| | | blend_images_cv(ai, 0.5, old_img, 0.5); |
| | | blend_truth(d.y.vals[i], boxes, truth_size, truth); |
| | | free_image(old_img); |
| | | d.X.vals[i] = ai.data; |
| | | } |
| | | } |
| | | else if (use_mixup == 3) { |
| | | if (i_mixup == 0) { |
| | | image tmp_img = make_image(w, h, c); |
| | | d.X.vals[i] = tmp_img.data; |
| | | } |
| | | |
| | | if (flip) { |
| | | int tmp = pleft; |
| | | pleft = pright; |
| | | pright = tmp; |
| | | } |
| | | |
| | | const int left_shift = min_val_cmp(cut_x[i], max_val_cmp(0, (-pleft*w / ow))); |
| | | const int top_shift = min_val_cmp(cut_y[i], max_val_cmp(0, (-ptop*h / oh))); |
| | | |
| | | const int right_shift = min_val_cmp((w - cut_x[i]), max_val_cmp(0, (-pright*w / ow))); |
| | | const int bot_shift = min_val_cmp(h - cut_y[i], max_val_cmp(0, (-pbot*h / oh))); |
| | | |
| | | |
| | | int k, x, y; |
| | | for (k = 0; k < c; ++k) { |
| | | for (y = 0; y < h; ++y) { |
| | | int j = y*w + k*w*h; |
| | | if (i_mixup == 0 && y < cut_y[i]) { |
| | | int j_src = (w - cut_x[i] - right_shift) + (y + h - cut_y[i] - bot_shift)*w + k*w*h; |
| | | memcpy(&d.X.vals[i][j + 0], &ai.data[j_src], cut_x[i] * sizeof(float)); |
| | | } |
| | | if (i_mixup == 1 && y < cut_y[i]) { |
| | | int j_src = left_shift + (y + h - cut_y[i] - bot_shift)*w + k*w*h; |
| | | memcpy(&d.X.vals[i][j + cut_x[i]], &ai.data[j_src], (w-cut_x[i]) * sizeof(float)); |
| | | } |
| | | if (i_mixup == 2 && y >= cut_y[i]) { |
| | | int j_src = (w - cut_x[i] - right_shift) + (top_shift + y - cut_y[i])*w + k*w*h; |
| | | memcpy(&d.X.vals[i][j + 0], &ai.data[j_src], cut_x[i] * sizeof(float)); |
| | | } |
| | | if (i_mixup == 3 && y >= cut_y[i]) { |
| | | int j_src = left_shift + (top_shift + y - cut_y[i])*w + k*w*h; |
| | | memcpy(&d.X.vals[i][j + cut_x[i]], &ai.data[j_src], (w - cut_x[i]) * sizeof(float)); |
| | | } |
| | | } |
| | | } |
| | | |
| | | blend_truth_mosaic(d.y.vals[i], boxes, truth_size, truth, w, h, cut_x[i], cut_y[i], i_mixup, left_shift, right_shift, top_shift, bot_shift, w, h, mosaic_bound); |
| | | |
| | | free_image(ai); |
| | | ai.data = d.X.vals[i]; |
| | | } |
| | | |
| | | |
| | | if (show_imgs && i_mixup == use_mixup) // delete i_mixup |
| | | { |
| | | image tmp_ai = copy_image(ai); |
| | | char buff[1000]; |
| | | //sprintf(buff, "aug_%d_%d_%s_%d", random_index, i, basecfg((char*)filename), random_gen()); |
| | | sprintf(buff, "aug_%d_%d_%d", random_index, i, random_gen()); |
| | | int t; |
| | | for (t = 0; t < boxes; ++t) { |
| | | box b = float_to_box_stride(d.y.vals[i] + t*truth_size, 1); |
| | | if (!b.x) break; |
| | | int left = (b.x - b.w / 2.)*ai.w; |
| | | int right = (b.x + b.w / 2.)*ai.w; |
| | | int top = (b.y - b.h / 2.)*ai.h; |
| | | int bot = (b.y + b.h / 2.)*ai.h; |
| | | draw_box_width(tmp_ai, left, top, right, bot, 1, 150, 100, 50); // 3 channels RGB |
| | | } |
| | | |
| | | save_image(tmp_ai, buff); |
| | | if (show_imgs == 1) { |
| | | //char buff_src[1000]; |
| | | //sprintf(buff_src, "src_%d_%d_%s_%d", random_index, i, basecfg((char*)filename), random_gen()); |
| | | //show_image_mat(src, buff_src); |
| | | show_image(tmp_ai, buff); |
| | | wait_until_press_key_cv(); |
| | | } |
| | | printf("\nYou use flag -show_imgs, so will be saved aug_...jpg images. Click on window and press ESC button \n"); |
| | | free_image(tmp_ai); |
| | | } |
| | | |
| | | release_mat(&src); |
| | | free(truth); |
| | | } |
| | | if (random_paths) free(random_paths); |
| | | } |
| | | |
| | | |
| | | return d; |
| | | } |
| | | #else // OPENCV |
| | | void blend_images(image new_img, float alpha, image old_img, float beta) |
| | | { |
| | | int data_size = new_img.w * new_img.h * new_img.c; |
| | | int i; |
| | | #pragma omp parallel for |
| | | for (i = 0; i < data_size; ++i) |
| | | new_img.data[i] = new_img.data[i] * alpha + old_img.data[i] * beta; |
| | | } |
| | | |
| | | data load_data_detection(int n, char **paths, int m, int w, int h, int c, int boxes, int truth_size, int classes, int use_flip, int gaussian_noise, int use_blur, int use_mixup, |
| | | float jitter, float resize, float hue, float saturation, float exposure, int mini_batch, int track, int augment_speed, int letter_box, int mosaic_bound, int contrastive, int contrastive_jit_flip, int contrastive_color, int show_imgs) |
| | | { |
| | | const int random_index = random_gen(); |
| | | c = c ? c : 3; |
| | | char **random_paths; |
| | | char **mixup_random_paths = NULL; |
| | | if(track) random_paths = get_sequential_paths(paths, n, m, mini_batch, augment_speed, contrastive); |
| | | else random_paths = get_random_paths_custom(paths, n, m, contrastive); |
| | | |
| | | //assert(use_mixup < 2); |
| | | if (use_mixup == 2) { |
| | | printf("\n cutmix=1 - isn't supported for Detector \n"); |
| | | exit(0); |
| | | } |
| | | if (use_mixup == 3 || use_mixup == 4) { |
| | | printf("\n mosaic=1 - compile Darknet with OpenCV for using mosaic=1 \n"); |
| | | exit(0); |
| | | } |
| | | int mixup = use_mixup ? random_gen() % 2 : 0; |
| | | //printf("\n mixup = %d \n", mixup); |
| | | if (mixup) { |
| | | if (track) mixup_random_paths = get_sequential_paths(paths, n, m, mini_batch, augment_speed, contrastive); |
| | | else mixup_random_paths = get_random_paths(paths, n, m); |
| | | } |
| | | |
| | | int i; |
| | | data d = { 0 }; |
| | | d.shallow = 0; |
| | | |
| | | d.X.rows = n; |
| | | d.X.vals = (float**)xcalloc(d.X.rows, sizeof(float*)); |
| | | d.X.cols = h*w*c; |
| | | |
| | | float r1 = 0, r2 = 0, r3 = 0, r4 = 0, r_scale; |
| | | float resize_r1 = 0, resize_r2 = 0; |
| | | float dhue = 0, dsat = 0, dexp = 0, flip = 0; |
| | | int augmentation_calculated = 0; |
| | | |
| | | d.y = make_matrix(n, truth_size * boxes); |
| | | int i_mixup = 0; |
| | | for (i_mixup = 0; i_mixup <= mixup; i_mixup++) { |
| | | if (i_mixup) augmentation_calculated = 0; |
| | | for (i = 0; i < n; ++i) { |
| | | float *truth = (float*)xcalloc(truth_size * boxes, sizeof(float)); |
| | | char *filename = (i_mixup) ? mixup_random_paths[i] : random_paths[i]; |
| | | |
| | | image orig = load_image(filename, 0, 0, c); |
| | | |
| | | int oh = orig.h; |
| | | int ow = orig.w; |
| | | |
| | | int dw = (ow*jitter); |
| | | int dh = (oh*jitter); |
| | | |
| | | float resize_down = resize, resize_up = resize; |
| | | if (resize_down > 1.0) resize_down = 1 / resize_down; |
| | | int min_rdw = ow*(1 - (1 / resize_down)) / 2; |
| | | int min_rdh = oh*(1 - (1 / resize_down)) / 2; |
| | | |
| | | if (resize_up < 1.0) resize_up = 1 / resize_up; |
| | | int max_rdw = ow*(1 - (1 / resize_up)) / 2; |
| | | int max_rdh = oh*(1 - (1 / resize_up)) / 2; |
| | | |
| | | if (!augmentation_calculated || !track) |
| | | { |
| | | augmentation_calculated = 1; |
| | | resize_r1 = random_float(); |
| | | resize_r2 = random_float(); |
| | | |
| | | if (!contrastive || contrastive_jit_flip || i % 2 == 0) |
| | | { |
| | | r1 = random_float(); |
| | | r2 = random_float(); |
| | | r3 = random_float(); |
| | | r4 = random_float(); |
| | | |
| | | flip = use_flip ? random_gen() % 2 : 0; |
| | | } |
| | | |
| | | r_scale = random_float(); |
| | | |
| | | if (!contrastive || contrastive_color || i % 2 == 0) |
| | | { |
| | | dhue = rand_uniform_strong(-hue, hue); |
| | | dsat = rand_scale(saturation); |
| | | dexp = rand_scale(exposure); |
| | | } |
| | | } |
| | | |
| | | int pleft = rand_precalc_random(-dw, dw, r1); |
| | | int pright = rand_precalc_random(-dw, dw, r2); |
| | | int ptop = rand_precalc_random(-dh, dh, r3); |
| | | int pbot = rand_precalc_random(-dh, dh, r4); |
| | | |
| | | if (resize < 1) { |
| | | // downsize only |
| | | pleft += rand_precalc_random(min_rdw, 0, resize_r1); |
| | | pright += rand_precalc_random(min_rdw, 0, resize_r2); |
| | | ptop += rand_precalc_random(min_rdh, 0, resize_r1); |
| | | pbot += rand_precalc_random(min_rdh, 0, resize_r2); |
| | | } |
| | | else { |
| | | pleft += rand_precalc_random(min_rdw, max_rdw, resize_r1); |
| | | pright += rand_precalc_random(min_rdw, max_rdw, resize_r2); |
| | | ptop += rand_precalc_random(min_rdh, max_rdh, resize_r1); |
| | | pbot += rand_precalc_random(min_rdh, max_rdh, resize_r2); |
| | | } |
| | | |
| | | if (letter_box) |
| | | { |
| | | float img_ar = (float)ow / (float)oh; |
| | | float net_ar = (float)w / (float)h; |
| | | float result_ar = img_ar / net_ar; |
| | | //printf(" ow = %d, oh = %d, w = %d, h = %d, img_ar = %f, net_ar = %f, result_ar = %f \n", ow, oh, w, h, img_ar, net_ar, result_ar); |
| | | if (result_ar > 1) // sheight - should be increased |
| | | { |
| | | float oh_tmp = ow / net_ar; |
| | | float delta_h = (oh_tmp - oh) / 2; |
| | | ptop = ptop - delta_h; |
| | | pbot = pbot - delta_h; |
| | | //printf(" result_ar = %f, oh_tmp = %f, delta_h = %d, ptop = %f, pbot = %f \n", result_ar, oh_tmp, delta_h, ptop, pbot); |
| | | } |
| | | else // swidth - should be increased |
| | | { |
| | | float ow_tmp = oh * net_ar; |
| | | float delta_w = (ow_tmp - ow) / 2; |
| | | pleft = pleft - delta_w; |
| | | pright = pright - delta_w; |
| | | //printf(" result_ar = %f, ow_tmp = %f, delta_w = %d, pleft = %f, pright = %f \n", result_ar, ow_tmp, delta_w, pleft, pright); |
| | | } |
| | | } |
| | | |
| | | int swidth = ow - pleft - pright; |
| | | int sheight = oh - ptop - pbot; |
| | | |
| | | float sx = (float)swidth / ow; |
| | | float sy = (float)sheight / oh; |
| | | |
| | | image cropped = crop_image(orig, pleft, ptop, swidth, sheight); |
| | | |
| | | float dx = ((float)pleft / ow) / sx; |
| | | float dy = ((float)ptop / oh) / sy; |
| | | |
| | | image sized = resize_image(cropped, w, h); |
| | | if (flip) flip_image(sized); |
| | | distort_image(sized, dhue, dsat, dexp); |
| | | //random_distort_image(sized, hue, saturation, exposure); |
| | | |
| | | fill_truth_detection(filename, boxes, truth_size, truth, classes, flip, dx, dy, 1. / sx, 1. / sy, w, h); |
| | | |
| | | if (i_mixup) { |
| | | image old_img = sized; |
| | | old_img.data = d.X.vals[i]; |
| | | //show_image(sized, "new"); |
| | | //show_image(old_img, "old"); |
| | | //wait_until_press_key_cv(); |
| | | blend_images(sized, 0.5, old_img, 0.5); |
| | | blend_truth(truth, boxes, truth_size, d.y.vals[i]); |
| | | free_image(old_img); |
| | | } |
| | | |
| | | d.X.vals[i] = sized.data; |
| | | memcpy(d.y.vals[i], truth, truth_size * boxes * sizeof(float)); |
| | | |
| | | if (show_imgs)// && i_mixup) |
| | | { |
| | | char buff[1000]; |
| | | sprintf(buff, "aug_%d_%d_%s_%d", random_index, i, basecfg(filename), random_gen()); |
| | | |
| | | int t; |
| | | for (t = 0; t < boxes; ++t) { |
| | | box b = float_to_box_stride(d.y.vals[i] + t*truth_size, 1); |
| | | if (!b.x) break; |
| | | int left = (b.x - b.w / 2.)*sized.w; |
| | | int right = (b.x + b.w / 2.)*sized.w; |
| | | int top = (b.y - b.h / 2.)*sized.h; |
| | | int bot = (b.y + b.h / 2.)*sized.h; |
| | | draw_box_width(sized, left, top, right, bot, 1, 150, 100, 50); // 3 channels RGB |
| | | } |
| | | |
| | | save_image(sized, buff); |
| | | if (show_imgs == 1) { |
| | | show_image(sized, buff); |
| | | wait_until_press_key_cv(); |
| | | } |
| | | printf("\nYou use flag -show_imgs, so will be saved aug_...jpg images. Press Enter: \n"); |
| | | //getchar(); |
| | | } |
| | | |
| | | free_image(orig); |
| | | free_image(cropped); |
| | | free(truth); |
| | | } |
| | | } |
| | | free(random_paths); |
| | | if (mixup_random_paths) free(mixup_random_paths); |
| | | return d; |
| | | } |
| | | #endif // OPENCV |
| | | |
| | | void *load_thread(void *ptr) |
| | | { |
| | | //srand(time(0)); |
| | | //printf("Loading data: %d\n", random_gen()); |
| | | load_args a = *(struct load_args*)ptr; |
| | | if(a.exposure == 0) a.exposure = 1; |
| | | if(a.saturation == 0) a.saturation = 1; |
| | | if(a.aspect == 0) a.aspect = 1; |
| | | |
| | | if (a.type == OLD_CLASSIFICATION_DATA){ |
| | | *a.d = load_data_old(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.hierarchy, a.flip, a.min, a.max, a.w, a.h, a.angle, a.aspect, a.hue, a.saturation, a.exposure, a.mixup, a.blur, a.show_imgs, a.label_smooth_eps, a.dontuse_opencv, a.contrastive); |
| | | } else if (a.type == SUPER_DATA){ |
| | | *a.d = load_data_super(a.paths, a.n, a.m, a.w, a.h, a.scale); |
| | | } else if (a.type == WRITING_DATA){ |
| | | *a.d = load_data_writing(a.paths, a.n, a.m, a.w, a.h, a.out_w, a.out_h); |
| | | } else if (a.type == REGION_DATA){ |
| | | *a.d = load_data_region(a.n, a.paths, a.m, a.w, a.h, a.num_boxes, a.classes, a.jitter, a.hue, a.saturation, a.exposure); |
| | | } else if (a.type == DETECTION_DATA){ |
| | | *a.d = load_data_detection(a.n, a.paths, a.m, a.w, a.h, a.c, a.num_boxes, a.truth_size, a.classes, a.flip, a.gaussian_noise, a.blur, a.mixup, a.jitter, a.resize, |
| | | a.hue, a.saturation, a.exposure, a.mini_batch, a.track, a.augment_speed, a.letter_box, a.mosaic_bound, a.contrastive, a.contrastive_jit_flip, a.contrastive_color, a.show_imgs); |
| | | } else if (a.type == SWAG_DATA){ |
| | | *a.d = load_data_swag(a.paths, a.n, a.classes, a.jitter); |
| | | } else if (a.type == COMPARE_DATA){ |
| | | *a.d = load_data_compare(a.n, a.paths, a.m, a.classes, a.w, a.h); |
| | | } else if (a.type == IMAGE_DATA){ |
| | | *(a.im) = load_image(a.path, 0, 0, a.c); |
| | | *(a.resized) = resize_image(*(a.im), a.w, a.h); |
| | | }else if (a.type == LETTERBOX_DATA) { |
| | | *(a.im) = load_image(a.path, 0, 0, a.c); |
| | | *(a.resized) = letterbox_image(*(a.im), a.w, a.h); |
| | | } else if (a.type == TAG_DATA){ |
| | | *a.d = load_data_tag(a.paths, a.n, a.m, a.classes, a.flip, a.min, a.max, a.w, a.h, a.angle, a.aspect, a.hue, a.saturation, a.exposure); |
| | | } |
| | | free(ptr); |
| | | return 0; |
| | | } |
| | | |
| | | pthread_t load_data_in_thread(load_args args) |
| | | { |
| | | pthread_t thread; |
| | | struct load_args* ptr = (load_args*)xcalloc(1, sizeof(struct load_args)); |
| | | *ptr = args; |
| | | if(pthread_create(&thread, 0, load_thread, ptr)) error("Thread creation failed"); |
| | | return thread; |
| | | } |
| | | |
| | | static const int thread_wait_ms = 5; |
| | | static volatile int flag_exit; |
| | | static volatile int * run_load_data = NULL; |
| | | static load_args * args_swap = NULL; |
| | | static pthread_t* threads = NULL; |
| | | |
| | | pthread_mutex_t mtx_load_data = PTHREAD_MUTEX_INITIALIZER; |
| | | |
| | | void *run_thread_loop(void *ptr) |
| | | { |
| | | const int i = *(int *)ptr; |
| | | |
| | | while (!custom_atomic_load_int(&flag_exit)) { |
| | | while (!custom_atomic_load_int(&run_load_data[i])) { |
| | | if (custom_atomic_load_int(&flag_exit)) { |
| | | free(ptr); |
| | | return 0; |
| | | } |
| | | this_thread_sleep_for(thread_wait_ms); |
| | | } |
| | | |
| | | pthread_mutex_lock(&mtx_load_data); |
| | | load_args *args_local = (load_args *)xcalloc(1, sizeof(load_args)); |
| | | *args_local = args_swap[i]; |
| | | pthread_mutex_unlock(&mtx_load_data); |
| | | |
| | | load_thread(args_local); |
| | | |
| | | custom_atomic_store_int(&run_load_data[i], 0); |
| | | } |
| | | free(ptr); |
| | | return 0; |
| | | } |
| | | |
| | | void *load_threads(void *ptr) |
| | | { |
| | | //srand(time(0)); |
| | | int i; |
| | | load_args args = *(load_args *)ptr; |
| | | if (args.threads == 0) args.threads = 1; |
| | | data *out = args.d; |
| | | int total = args.n; |
| | | free(ptr); |
| | | data* buffers = (data*)xcalloc(args.threads, sizeof(data)); |
| | | if (!threads) { |
| | | threads = (pthread_t*)xcalloc(args.threads, sizeof(pthread_t)); |
| | | run_load_data = (volatile int *)xcalloc(args.threads, sizeof(int)); |
| | | args_swap = (load_args *)xcalloc(args.threads, sizeof(load_args)); |
| | | fprintf(stderr, " Create %d permanent cpu-threads \n", args.threads); |
| | | |
| | | for (i = 0; i < args.threads; ++i) { |
| | | int* ptr = (int*)xcalloc(1, sizeof(int)); |
| | | *ptr = i; |
| | | if (pthread_create(&threads[i], 0, run_thread_loop, ptr)) error("Thread creation failed"); |
| | | } |
| | | } |
| | | |
| | | for (i = 0; i < args.threads; ++i) { |
| | | args.d = buffers + i; |
| | | args.n = (i + 1) * total / args.threads - i * total / args.threads; |
| | | |
| | | pthread_mutex_lock(&mtx_load_data); |
| | | args_swap[i] = args; |
| | | pthread_mutex_unlock(&mtx_load_data); |
| | | |
| | | custom_atomic_store_int(&run_load_data[i], 1); // run thread |
| | | } |
| | | for (i = 0; i < args.threads; ++i) { |
| | | while (custom_atomic_load_int(&run_load_data[i])) this_thread_sleep_for(thread_wait_ms); // join |
| | | } |
| | | |
| | | /* |
| | | pthread_t* threads = (pthread_t*)xcalloc(args.threads, sizeof(pthread_t)); |
| | | for(i = 0; i < args.threads; ++i){ |
| | | args.d = buffers + i; |
| | | args.n = (i+1) * total/args.threads - i * total/args.threads; |
| | | threads[i] = load_data_in_thread(args); |
| | | } |
| | | for(i = 0; i < args.threads; ++i){ |
| | | pthread_join(threads[i], 0); |
| | | } |
| | | */ |
| | | |
| | | *out = concat_datas(buffers, args.threads); |
| | | out->shallow = 0; |
| | | for(i = 0; i < args.threads; ++i){ |
| | | buffers[i].shallow = 1; |
| | | free_data(buffers[i]); |
| | | } |
| | | free(buffers); |
| | | //free(threads); |
| | | return 0; |
| | | } |
| | | |
| | | void free_load_threads(void *ptr) |
| | | { |
| | | load_args args = *(load_args *)ptr; |
| | | if (args.threads == 0) args.threads = 1; |
| | | int i; |
| | | if (threads) { |
| | | custom_atomic_store_int(&flag_exit, 1); |
| | | for (i = 0; i < args.threads; ++i) { |
| | | pthread_join(threads[i], 0); |
| | | } |
| | | free((void*)run_load_data); |
| | | free(args_swap); |
| | | free(threads); |
| | | threads = NULL; |
| | | custom_atomic_store_int(&flag_exit, 0); |
| | | } |
| | | } |
| | | |
| | | pthread_t load_data(load_args args) |
| | | { |
| | | pthread_t thread; |
| | | struct load_args* ptr = (load_args*)xcalloc(1, sizeof(struct load_args)); |
| | | *ptr = args; |
| | | if(pthread_create(&thread, 0, load_threads, ptr)) error("Thread creation failed"); |
| | | return thread; |
| | | } |
| | | |
| | | data load_data_writing(char **paths, int n, int m, int w, int h, int out_w, int out_h) |
| | | { |
| | | if(m) paths = get_random_paths(paths, n, m); |
| | | char **replace_paths = find_replace_paths(paths, n, ".png", "-label.png"); |
| | | 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); |
| | | if(m) free(paths); |
| | | int i; |
| | | for(i = 0; i < n; ++i) free(replace_paths[i]); |
| | | free(replace_paths); |
| | | return d; |
| | | } |
| | | |
| | | data load_data_old(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 = {0}; |
| | | d.shallow = 0; |
| | | d.X = load_image_paths(paths, n, w, h); |
| | | d.y = load_labels_paths(paths, n, labels, k, 0, 0, 0); |
| | | if(m) free(paths); |
| | | return d; |
| | | } |
| | | |
| | | /* |
| | | data load_data_study(char **paths, int n, int m, char **labels, int k, int min, int max, int size, float angle, float aspect, float hue, float saturation, float exposure) |
| | | { |
| | | 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_augment_paths(paths, n, flip, min, max, size, angle, aspect, hue, saturation, exposure); |
| | | d.y = load_labels_paths(paths, n, labels, k); |
| | | if(m) free(paths); |
| | | return d; |
| | | } |
| | | */ |
| | | |
| | | data load_data_super(char **paths, int n, int m, int w, int h, int scale) |
| | | { |
| | | if(m) paths = get_random_paths(paths, n, m); |
| | | data d = {0}; |
| | | d.shallow = 0; |
| | | |
| | | int i; |
| | | d.X.rows = n; |
| | | d.X.vals = (float**)xcalloc(n, sizeof(float*)); |
| | | d.X.cols = w*h*3; |
| | | |
| | | d.y.rows = n; |
| | | d.y.vals = (float**)xcalloc(n, sizeof(float*)); |
| | | d.y.cols = w*scale * h*scale * 3; |
| | | |
| | | for(i = 0; i < n; ++i){ |
| | | image im = load_image_color(paths[i], 0, 0); |
| | | image crop = random_crop_image(im, w*scale, h*scale); |
| | | int flip = random_gen()%2; |
| | | if (flip) flip_image(crop); |
| | | image resize = resize_image(crop, w, h); |
| | | d.X.vals[i] = resize.data; |
| | | d.y.vals[i] = crop.data; |
| | | free_image(im); |
| | | } |
| | | |
| | | if(m) free(paths); |
| | | return d; |
| | | } |
| | | |
| | | data load_data_augment(char **paths, int n, int m, char **labels, int k, tree *hierarchy, int use_flip, int min, int max, int w, int h, float angle, |
| | | float aspect, float hue, float saturation, float exposure, int use_mixup, int use_blur, int show_imgs, float label_smooth_eps, int dontuse_opencv, int contrastive) |
| | | { |
| | | char **paths_stored = paths; |
| | | if(m) paths = get_random_paths(paths, n, m); |
| | | data d = {0}; |
| | | d.shallow = 0; |
| | | d.X = load_image_augment_paths(paths, n, use_flip, min, max, w, h, angle, aspect, hue, saturation, exposure, dontuse_opencv, contrastive); |
| | | d.y = load_labels_paths(paths, n, labels, k, hierarchy, label_smooth_eps, contrastive); |
| | | |
| | | if (use_mixup && rand_int(0, 1)) { |
| | | char **paths_mix = get_random_paths(paths_stored, n, m); |
| | | data d2 = { 0 }; |
| | | d2.shallow = 0; |
| | | d2.X = load_image_augment_paths(paths_mix, n, use_flip, min, max, w, h, angle, aspect, hue, saturation, exposure, dontuse_opencv, contrastive); |
| | | d2.y = load_labels_paths(paths_mix, n, labels, k, hierarchy, label_smooth_eps, contrastive); |
| | | free(paths_mix); |
| | | |
| | | data d3 = { 0 }; |
| | | d3.shallow = 0; |
| | | data d4 = { 0 }; |
| | | d4.shallow = 0; |
| | | if (use_mixup >= 3) { |
| | | char **paths_mix3 = get_random_paths(paths_stored, n, m); |
| | | d3.X = load_image_augment_paths(paths_mix3, n, use_flip, min, max, w, h, angle, aspect, hue, saturation, exposure, dontuse_opencv, contrastive); |
| | | d3.y = load_labels_paths(paths_mix3, n, labels, k, hierarchy, label_smooth_eps, contrastive); |
| | | free(paths_mix3); |
| | | |
| | | char **paths_mix4 = get_random_paths(paths_stored, n, m); |
| | | d4.X = load_image_augment_paths(paths_mix4, n, use_flip, min, max, w, h, angle, aspect, hue, saturation, exposure, dontuse_opencv, contrastive); |
| | | d4.y = load_labels_paths(paths_mix4, n, labels, k, hierarchy, label_smooth_eps, contrastive); |
| | | free(paths_mix4); |
| | | } |
| | | |
| | | |
| | | // mix |
| | | int i, j; |
| | | for (i = 0; i < d2.X.rows; ++i) { |
| | | |
| | | int mixup = use_mixup; |
| | | if (use_mixup == 4) mixup = rand_int(2, 3); // alternate CutMix and Mosaic |
| | | |
| | | // MixUp ----------------------------------- |
| | | if (mixup == 1) { |
| | | // mix images |
| | | for (j = 0; j < d2.X.cols; ++j) { |
| | | d.X.vals[i][j] = (d.X.vals[i][j] + d2.X.vals[i][j]) / 2.0f; |
| | | } |
| | | |
| | | // mix labels |
| | | for (j = 0; j < d2.y.cols; ++j) { |
| | | d.y.vals[i][j] = (d.y.vals[i][j] + d2.y.vals[i][j]) / 2.0f; |
| | | } |
| | | } |
| | | // CutMix ----------------------------------- |
| | | else if (mixup == 2) { |
| | | const float min = 0.3; // 0.3*0.3 = 9% |
| | | const float max = 0.8; // 0.8*0.8 = 64% |
| | | const int cut_w = rand_int(w*min, w*max); |
| | | const int cut_h = rand_int(h*min, h*max); |
| | | const int cut_x = rand_int(0, w - cut_w - 1); |
| | | const int cut_y = rand_int(0, h - cut_h - 1); |
| | | const int left = cut_x; |
| | | const int right = cut_x + cut_w; |
| | | const int top = cut_y; |
| | | const int bot = cut_y + cut_h; |
| | | |
| | | assert(cut_x >= 0 && cut_x <= w); |
| | | assert(cut_y >= 0 && cut_y <= h); |
| | | assert(cut_w >= 0 && cut_w <= w); |
| | | assert(cut_h >= 0 && cut_h <= h); |
| | | |
| | | assert(right >= 0 && right <= w); |
| | | assert(bot >= 0 && bot <= h); |
| | | |
| | | assert(top <= bot); |
| | | assert(left <= right); |
| | | |
| | | const float alpha = (float)(cut_w*cut_h) / (float)(w*h); |
| | | const float beta = 1 - alpha; |
| | | |
| | | int c, x, y; |
| | | for (c = 0; c < 3; ++c) { |
| | | for (y = top; y < bot; ++y) { |
| | | for (x = left; x < right; ++x) { |
| | | int j = x + y*w + c*w*h; |
| | | d.X.vals[i][j] = d2.X.vals[i][j]; |
| | | } |
| | | } |
| | | } |
| | | |
| | | //printf("\n alpha = %f, beta = %f \n", alpha, beta); |
| | | // mix labels |
| | | for (j = 0; j < d.y.cols; ++j) { |
| | | d.y.vals[i][j] = d.y.vals[i][j] * beta + d2.y.vals[i][j] * alpha; |
| | | } |
| | | } |
| | | // Mosaic ----------------------------------- |
| | | else if (mixup == 3) |
| | | { |
| | | const float min_offset = 0.2; // 20% |
| | | const int cut_x = rand_int(w*min_offset, w*(1 - min_offset)); |
| | | const int cut_y = rand_int(h*min_offset, h*(1 - min_offset)); |
| | | |
| | | float s1 = (float)(cut_x * cut_y) / (w*h); |
| | | float s2 = (float)((w - cut_x) * cut_y) / (w*h); |
| | | float s3 = (float)(cut_x * (h - cut_y)) / (w*h); |
| | | float s4 = (float)((w - cut_x) * (h - cut_y)) / (w*h); |
| | | |
| | | int c, x, y; |
| | | for (c = 0; c < 3; ++c) { |
| | | for (y = 0; y < h; ++y) { |
| | | for (x = 0; x < w; ++x) { |
| | | int j = x + y*w + c*w*h; |
| | | if (x < cut_x && y < cut_y) d.X.vals[i][j] = d.X.vals[i][j]; |
| | | if (x >= cut_x && y < cut_y) d.X.vals[i][j] = d2.X.vals[i][j]; |
| | | if (x < cut_x && y >= cut_y) d.X.vals[i][j] = d3.X.vals[i][j]; |
| | | if (x >= cut_x && y >= cut_y) d.X.vals[i][j] = d4.X.vals[i][j]; |
| | | } |
| | | } |
| | | } |
| | | |
| | | for (j = 0; j < d.y.cols; ++j) { |
| | | const float max_s = 1;// max_val_cmp(s1, max_val_cmp(s2, max_val_cmp(s3, s4))); |
| | | |
| | | d.y.vals[i][j] = d.y.vals[i][j] * s1 / max_s + d2.y.vals[i][j] * s2 / max_s + d3.y.vals[i][j] * s3 / max_s + d4.y.vals[i][j] * s4 / max_s; |
| | | } |
| | | } |
| | | } |
| | | |
| | | free_data(d2); |
| | | |
| | | if (use_mixup >= 3) { |
| | | free_data(d3); |
| | | free_data(d4); |
| | | } |
| | | } |
| | | |
| | | #ifdef OPENCV |
| | | if (use_blur) { |
| | | int i; |
| | | for (i = 0; i < d.X.rows; ++i) { |
| | | if (random_gen() % 4 == 0) { |
| | | image im = make_empty_image(w, h, 3); |
| | | im.data = d.X.vals[i]; |
| | | int ksize = use_blur; |
| | | if (use_blur == 1) ksize = 15; |
| | | image blurred = blur_image(im, ksize); |
| | | free_image(im); |
| | | d.X.vals[i] = blurred.data; |
| | | //if (i == 0) { |
| | | // show_image(im, "Not blurred"); |
| | | // show_image(blurred, "blurred"); |
| | | // wait_until_press_key_cv(); |
| | | //} |
| | | } |
| | | } |
| | | } |
| | | #endif // OPENCV |
| | | |
| | | if (show_imgs) { |
| | | int i, j; |
| | | for (i = 0; i < d.X.rows; ++i) { |
| | | image im = make_empty_image(w, h, 3); |
| | | im.data = d.X.vals[i]; |
| | | char buff[1000]; |
| | | sprintf(buff, "aug_%d_%s_%d", i, basecfg((char*)paths[i]), random_gen()); |
| | | save_image(im, buff); |
| | | |
| | | char buff_string[1000]; |
| | | sprintf(buff_string, "\n Classes: "); |
| | | for (j = 0; j < d.y.cols; ++j) { |
| | | if (d.y.vals[i][j] > 0) { |
| | | char buff_tmp[100]; |
| | | sprintf(buff_tmp, " %d (%f), ", j, d.y.vals[i][j]); |
| | | strcat(buff_string, buff_tmp); |
| | | } |
| | | } |
| | | printf("%s \n", buff_string); |
| | | |
| | | if (show_imgs == 1) { |
| | | show_image(im, buff); |
| | | wait_until_press_key_cv(); |
| | | } |
| | | } |
| | | printf("\nYou use flag -show_imgs, so will be saved aug_...jpg images. Click on window and press ESC button \n"); |
| | | } |
| | | |
| | | if (m) free(paths); |
| | | |
| | | return d; |
| | | } |
| | | |
| | | data load_data_tag(char **paths, int n, int m, int k, int use_flip, int min, int max, int w, int h, float angle, float aspect, float hue, float saturation, float exposure) |
| | | { |
| | | if(m) paths = get_random_paths(paths, n, m); |
| | | data d = {0}; |
| | | d.w = w; |
| | | d.h = h; |
| | | d.shallow = 0; |
| | | d.X = load_image_augment_paths(paths, n, use_flip, min, max, w, h, angle, aspect, hue, saturation, exposure, 0, 0); |
| | | d.y = load_tags_paths(paths, n, k); |
| | | if(m) free(paths); |
| | | return d; |
| | | } |
| | | |
| | | 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 = (float**)xcalloc(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 = {0}; |
| | | d.shallow = 1; |
| | | d.X = concat_matrix(d1.X, d2.X); |
| | | d.y = concat_matrix(d1.y, d2.y); |
| | | return d; |
| | | } |
| | | |
| | | data concat_datas(data *d, int n) |
| | | { |
| | | int i; |
| | | data out = {0}; |
| | | for(i = 0; i < n; ++i){ |
| | | data newdata = concat_data(d[i], out); |
| | | free_data(out); |
| | | out = newdata; |
| | | } |
| | | return out; |
| | | } |
| | | |
| | | data load_categorical_data_csv(char *filename, int target, int k) |
| | | { |
| | | data d = {0}; |
| | | 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 = {0}; |
| | | 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_id = bytes[0]; |
| | | y.vals[i][class_id] = 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./255); |
| | | //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 = random_gen()%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)); |
| | | } |
| | | } |
| | | |
| | | void smooth_data(data d) |
| | | { |
| | | int i, j; |
| | | float scale = 1. / d.y.cols; |
| | | float eps = .1; |
| | | for(i = 0; i < d.y.rows; ++i){ |
| | | for(j = 0; j < d.y.cols; ++j){ |
| | | d.y.vals[i][j] = eps * scale + (1-eps) * d.y.vals[i][j]; |
| | | } |
| | | } |
| | | } |
| | | |
| | | data load_all_cifar10() |
| | | { |
| | | data d = {0}; |
| | | 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/cifar/cifar-10-batches-bin/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_id = bytes[0]; |
| | | y.vals[i+b*10000][class_id] = 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./255); |
| | | smooth_data(d); |
| | | return d; |
| | | } |
| | | |
| | | data load_go(char *filename) |
| | | { |
| | | FILE *fp = fopen(filename, "rb"); |
| | | matrix X = make_matrix(3363059, 361); |
| | | matrix y = make_matrix(3363059, 361); |
| | | int row, col; |
| | | |
| | | if(!fp) file_error(filename); |
| | | char *label; |
| | | int count = 0; |
| | | while((label = fgetl(fp))){ |
| | | int i; |
| | | if(count == X.rows){ |
| | | X = resize_matrix(X, count*2); |
| | | y = resize_matrix(y, count*2); |
| | | } |
| | | sscanf(label, "%d %d", &row, &col); |
| | | char *board = fgetl(fp); |
| | | |
| | | int index = row*19 + col; |
| | | y.vals[count][index] = 1; |
| | | |
| | | for(i = 0; i < 19*19; ++i){ |
| | | float val = 0; |
| | | if(board[i] == '1') val = 1; |
| | | else if(board[i] == '2') val = -1; |
| | | X.vals[count][i] = val; |
| | | } |
| | | ++count; |
| | | free(label); |
| | | free(board); |
| | | } |
| | | X = resize_matrix(X, count); |
| | | y = resize_matrix(y, count); |
| | | |
| | | data d = {0}; |
| | | d.shallow = 0; |
| | | d.X = X; |
| | | d.y = y; |
| | | |
| | | |
| | | fclose(fp); |
| | | |
| | | return d; |
| | | } |
| | | |
| | | |
| | | void randomize_data(data d) |
| | | { |
| | | int i; |
| | | for(i = d.X.rows-1; i > 0; --i){ |
| | | int index = random_gen()%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 get_data_part(data d, int part, int total) |
| | | { |
| | | data p = {0}; |
| | | p.shallow = 1; |
| | | p.X.rows = d.X.rows * (part + 1) / total - d.X.rows * part / total; |
| | | p.y.rows = d.y.rows * (part + 1) / total - d.y.rows * part / total; |
| | | p.X.cols = d.X.cols; |
| | | p.y.cols = d.y.cols; |
| | | p.X.vals = d.X.vals + d.X.rows * part / total; |
| | | p.y.vals = d.y.vals + d.y.rows * part / total; |
| | | return p; |
| | | } |
| | | |
| | | data get_random_data(data d, int num) |
| | | { |
| | | data r = {0}; |
| | | r.shallow = 1; |
| | | |
| | | r.X.rows = num; |
| | | r.y.rows = num; |
| | | |
| | | r.X.cols = d.X.cols; |
| | | r.y.cols = d.y.cols; |
| | | |
| | | r.X.vals = (float**)xcalloc(num, sizeof(float*)); |
| | | r.y.vals = (float**)xcalloc(num, sizeof(float*)); |
| | | |
| | | int i; |
| | | for(i = 0; i < num; ++i){ |
| | | int index = random_gen()%d.X.rows; |
| | | r.X.vals[i] = d.X.vals[index]; |
| | | r.y.vals[i] = d.y.vals[index]; |
| | | } |
| | | return r; |
| | | } |
| | | |
| | | data *split_data(data d, int part, int total) |
| | | { |
| | | data* split = (data*)xcalloc(2, sizeof(data)); |
| | | int i; |
| | | int start = part*d.X.rows/total; |
| | | int end = (part+1)*d.X.rows/total; |
| | | data train ={0}; |
| | | data test ={0}; |
| | | 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 = (float**)xcalloc(train.X.rows, sizeof(float*)); |
| | | test.X.vals = (float**)xcalloc(test.X.rows, sizeof(float*)); |
| | | train.y.vals = (float**)xcalloc(train.y.rows, sizeof(float*)); |
| | | test.y.vals = (float**)xcalloc(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; |
| | | } |