00001 #include "data.h"
00002 #include "utils.h"
00003 #include "image.h"
00004 #include "cuda.h"
00005
00006 #include <stdio.h>
00007 #include <stdlib.h>
00008 #include <string.h>
00009
00010 pthread_mutex_t mutex = PTHREAD_MUTEX_INITIALIZER;
00011
00012 list *get_paths(char *filename)
00013 {
00014 char *path;
00015 FILE *file = fopen(filename, "r");
00016 if(!file) file_error(filename);
00017 list *lines = make_list();
00018 while((path=fgetl(file))){
00019 list_insert(lines, path);
00020 }
00021 fclose(file);
00022 return lines;
00023 }
00024
00025
00026
00027
00028
00029
00030
00031
00032
00033
00034
00035
00036
00037
00038
00039
00040
00041
00042 char **get_random_paths(char **paths, int n, int m)
00043 {
00044 char **random_paths = calloc(n, sizeof(char*));
00045 int i;
00046 pthread_mutex_lock(&mutex);
00047 for(i = 0; i < n; ++i){
00048 int index = rand()%m;
00049 random_paths[i] = paths[index];
00050
00051 }
00052 pthread_mutex_unlock(&mutex);
00053 return random_paths;
00054 }
00055
00056 char **find_replace_paths(char **paths, int n, char *find, char *replace)
00057 {
00058 char **replace_paths = calloc(n, sizeof(char*));
00059 int i;
00060 for(i = 0; i < n; ++i){
00061 char replaced[4096];
00062 find_replace(paths[i], find, replace, replaced);
00063 replace_paths[i] = copy_string(replaced);
00064 }
00065 return replace_paths;
00066 }
00067
00068 matrix load_image_paths_gray(char **paths, int n, int w, int h)
00069 {
00070 int i;
00071 matrix X;
00072 X.rows = n;
00073 X.vals = calloc(X.rows, sizeof(float*));
00074 X.cols = 0;
00075
00076 for(i = 0; i < n; ++i){
00077 image im = load_image(paths[i], w, h, 3);
00078
00079 image gray = grayscale_image(im);
00080 free_image(im);
00081 im = gray;
00082
00083 X.vals[i] = im.data;
00084 X.cols = im.h*im.w*im.c;
00085 }
00086 return X;
00087 }
00088
00089 matrix load_image_paths(char **paths, int n, int w, int h)
00090 {
00091 int i;
00092 matrix X;
00093 X.rows = n;
00094 X.vals = calloc(X.rows, sizeof(float*));
00095 X.cols = 0;
00096
00097 for(i = 0; i < n; ++i){
00098 image im = load_image_color(paths[i], w, h);
00099 X.vals[i] = im.data;
00100 X.cols = im.h*im.w*im.c;
00101 }
00102 return X;
00103 }
00104
00105 matrix load_image_augment_paths(char **paths, int n, int min, int max, int size, float angle, float aspect, float hue, float saturation, float exposure)
00106 {
00107 int i;
00108 matrix X;
00109 X.rows = n;
00110 X.vals = calloc(X.rows, sizeof(float*));
00111 X.cols = 0;
00112
00113 for(i = 0; i < n; ++i){
00114 image im = load_image_color(paths[i], 0, 0);
00115 image crop = random_augment_image(im, angle, aspect, min, max, size);
00116 int flip = rand()%2;
00117 if (flip) flip_image(crop);
00118 random_distort_image(crop, hue, saturation, exposure);
00119
00120
00121
00122
00123
00124
00125 free_image(im);
00126 X.vals[i] = crop.data;
00127 X.cols = crop.h*crop.w*crop.c;
00128 }
00129 return X;
00130 }
00131
00132
00133 box_label *read_boxes(char *filename, int *n)
00134 {
00135 box_label *boxes = calloc(1, sizeof(box_label));
00136 FILE *file = fopen(filename, "r");
00137 if(!file) file_error(filename);
00138 float x, y, h, w;
00139 int id;
00140 int count = 0;
00141 while(fscanf(file, "%d %f %f %f %f", &id, &x, &y, &w, &h) == 5){
00142 boxes = realloc(boxes, (count+1)*sizeof(box_label));
00143 boxes[count].id = id;
00144 boxes[count].x = x;
00145 boxes[count].y = y;
00146 boxes[count].h = h;
00147 boxes[count].w = w;
00148 boxes[count].left = x - w/2;
00149 boxes[count].right = x + w/2;
00150 boxes[count].top = y - h/2;
00151 boxes[count].bottom = y + h/2;
00152 ++count;
00153 }
00154 fclose(file);
00155 *n = count;
00156 return boxes;
00157 }
00158
00159 void randomize_boxes(box_label *b, int n)
00160 {
00161 int i;
00162 for(i = 0; i < n; ++i){
00163 box_label swap = b[i];
00164 int index = rand()%n;
00165 b[i] = b[index];
00166 b[index] = swap;
00167 }
00168 }
00169
00170 void correct_boxes(box_label *boxes, int n, float dx, float dy, float sx, float sy, int flip)
00171 {
00172 int i;
00173 for(i = 0; i < n; ++i){
00174 if(boxes[i].x == 0 && boxes[i].y == 0) {
00175 boxes[i].x = 999999;
00176 boxes[i].y = 999999;
00177 boxes[i].w = 999999;
00178 boxes[i].h = 999999;
00179 continue;
00180 }
00181 boxes[i].left = boxes[i].left * sx - dx;
00182 boxes[i].right = boxes[i].right * sx - dx;
00183 boxes[i].top = boxes[i].top * sy - dy;
00184 boxes[i].bottom = boxes[i].bottom* sy - dy;
00185
00186 if(flip){
00187 float swap = boxes[i].left;
00188 boxes[i].left = 1. - boxes[i].right;
00189 boxes[i].right = 1. - swap;
00190 }
00191
00192 boxes[i].left = constrain(0, 1, boxes[i].left);
00193 boxes[i].right = constrain(0, 1, boxes[i].right);
00194 boxes[i].top = constrain(0, 1, boxes[i].top);
00195 boxes[i].bottom = constrain(0, 1, boxes[i].bottom);
00196
00197 boxes[i].x = (boxes[i].left+boxes[i].right)/2;
00198 boxes[i].y = (boxes[i].top+boxes[i].bottom)/2;
00199 boxes[i].w = (boxes[i].right - boxes[i].left);
00200 boxes[i].h = (boxes[i].bottom - boxes[i].top);
00201
00202 boxes[i].w = constrain(0, 1, boxes[i].w);
00203 boxes[i].h = constrain(0, 1, boxes[i].h);
00204 }
00205 }
00206
00207 void fill_truth_swag(char *path, float *truth, int classes, int flip, float dx, float dy, float sx, float sy)
00208 {
00209 char labelpath[4096];
00210 find_replace(path, "images", "labels", labelpath);
00211 find_replace(labelpath, "JPEGImages", "labels", labelpath);
00212 find_replace(labelpath, ".jpg", ".txt", labelpath);
00213 find_replace(labelpath, ".JPG", ".txt", labelpath);
00214 find_replace(labelpath, ".JPEG", ".txt", labelpath);
00215
00216 int count = 0;
00217 box_label *boxes = read_boxes(labelpath, &count);
00218 randomize_boxes(boxes, count);
00219 correct_boxes(boxes, count, dx, dy, sx, sy, flip);
00220 float x,y,w,h;
00221 int id;
00222 int i;
00223
00224 for (i = 0; i < count && i < 30; ++i) {
00225 x = boxes[i].x;
00226 y = boxes[i].y;
00227 w = boxes[i].w;
00228 h = boxes[i].h;
00229 id = boxes[i].id;
00230
00231 if (w < .0 || h < .0) continue;
00232
00233 int index = (4+classes) * i;
00234
00235 truth[index++] = x;
00236 truth[index++] = y;
00237 truth[index++] = w;
00238 truth[index++] = h;
00239
00240 if (id < classes) truth[index+id] = 1;
00241 }
00242 free(boxes);
00243 }
00244
00245 void fill_truth_region(char *path, float *truth, int classes, int num_boxes, int flip, float dx, float dy, float sx, float sy)
00246 {
00247 char labelpath[4096];
00248 find_replace(path, "images", "labels", labelpath);
00249 find_replace(labelpath, "JPEGImages", "labels", labelpath);
00250
00251 find_replace(labelpath, ".jpg", ".txt", labelpath);
00252 find_replace(labelpath, ".png", ".txt", labelpath);
00253 find_replace(labelpath, ".JPG", ".txt", labelpath);
00254 find_replace(labelpath, ".JPEG", ".txt", labelpath);
00255 int count = 0;
00256 box_label *boxes = read_boxes(labelpath, &count);
00257 randomize_boxes(boxes, count);
00258 correct_boxes(boxes, count, dx, dy, sx, sy, flip);
00259 float x,y,w,h;
00260 int id;
00261 int i;
00262
00263 for (i = 0; i < count; ++i) {
00264 x = boxes[i].x;
00265 y = boxes[i].y;
00266 w = boxes[i].w;
00267 h = boxes[i].h;
00268 id = boxes[i].id;
00269
00270 if (w < .01 || h < .01) continue;
00271
00272 int col = (int)(x*num_boxes);
00273 int row = (int)(y*num_boxes);
00274
00275 x = x*num_boxes - col;
00276 y = y*num_boxes - row;
00277
00278 int index = (col+row*num_boxes)*(5+classes);
00279 if (truth[index]) continue;
00280 truth[index++] = 1;
00281
00282 if (id < classes) truth[index+id] = 1;
00283 index += classes;
00284
00285 truth[index++] = x;
00286 truth[index++] = y;
00287 truth[index++] = w;
00288 truth[index++] = h;
00289 }
00290 free(boxes);
00291 }
00292
00293 void fill_truth_detection(char *path, int num_boxes, float *truth, int classes, int flip, float dx, float dy, float sx, float sy)
00294 {
00295 char labelpath[4096];
00296 find_replace(path, "images", "labels", labelpath);
00297 find_replace(labelpath, "JPEGImages", "labels", labelpath);
00298
00299 find_replace(labelpath, "raw", "labels", labelpath);
00300 find_replace(labelpath, ".jpg", ".txt", labelpath);
00301 find_replace(labelpath, ".png", ".txt", labelpath);
00302 find_replace(labelpath, ".JPG", ".txt", labelpath);
00303 find_replace(labelpath, ".JPEG", ".txt", labelpath);
00304 int count = 0;
00305 box_label *boxes = read_boxes(labelpath, &count);
00306 randomize_boxes(boxes, count);
00307 correct_boxes(boxes, count, dx, dy, sx, sy, flip);
00308 if(count > num_boxes) count = num_boxes;
00309 float x,y,w,h;
00310 int id;
00311 int i;
00312
00313 for (i = 0; i < count; ++i) {
00314 x = boxes[i].x;
00315 y = boxes[i].y;
00316 w = boxes[i].w;
00317 h = boxes[i].h;
00318 id = boxes[i].id;
00319
00320 if ((w < .01 || h < .01)) continue;
00321
00322 truth[i*5+0] = x;
00323 truth[i*5+1] = y;
00324 truth[i*5+2] = w;
00325 truth[i*5+3] = h;
00326 truth[i*5+4] = id;
00327 }
00328 free(boxes);
00329 }
00330
00331 #define NUMCHARS 37
00332
00333 void print_letters(float *pred, int n)
00334 {
00335 int i;
00336 for(i = 0; i < n; ++i){
00337 int index = max_index(pred+i*NUMCHARS, NUMCHARS);
00338 printf("%c", int_to_alphanum(index));
00339 }
00340 printf("\n");
00341 }
00342
00343 void fill_truth_captcha(char *path, int n, float *truth)
00344 {
00345 char *begin = strrchr(path, '/');
00346 ++begin;
00347 int i;
00348 for(i = 0; i < strlen(begin) && i < n && begin[i] != '.'; ++i){
00349 int index = alphanum_to_int(begin[i]);
00350 if(index > 35) printf("Bad %c\n", begin[i]);
00351 truth[i*NUMCHARS+index] = 1;
00352 }
00353 for(;i < n; ++i){
00354 truth[i*NUMCHARS + NUMCHARS-1] = 1;
00355 }
00356 }
00357
00358 data load_data_captcha(char **paths, int n, int m, int k, int w, int h)
00359 {
00360 if(m) paths = get_random_paths(paths, n, m);
00361 data d = {0};
00362 d.shallow = 0;
00363 d.X = load_image_paths(paths, n, w, h);
00364 d.y = make_matrix(n, k*NUMCHARS);
00365 int i;
00366 for(i = 0; i < n; ++i){
00367 fill_truth_captcha(paths[i], k, d.y.vals[i]);
00368 }
00369 if(m) free(paths);
00370 return d;
00371 }
00372
00373 data load_data_captcha_encode(char **paths, int n, int m, int w, int h)
00374 {
00375 if(m) paths = get_random_paths(paths, n, m);
00376 data d = {0};
00377 d.shallow = 0;
00378 d.X = load_image_paths(paths, n, w, h);
00379 d.X.cols = 17100;
00380 d.y = d.X;
00381 if(m) free(paths);
00382 return d;
00383 }
00384
00385 void fill_truth(char *path, char **labels, int k, float *truth)
00386 {
00387 int i;
00388 memset(truth, 0, k*sizeof(float));
00389 int count = 0;
00390 for(i = 0; i < k; ++i){
00391 if(strstr(path, labels[i])){
00392 truth[i] = 1;
00393 ++count;
00394 }
00395 }
00396 if(count != 1) printf("Too many or too few labels: %d, %s\n", count, path);
00397 }
00398
00399 void fill_hierarchy(float *truth, int k, tree *hierarchy)
00400 {
00401 int j;
00402 for(j = 0; j < k; ++j){
00403 if(truth[j]){
00404 int parent = hierarchy->parent[j];
00405 while(parent >= 0){
00406 truth[parent] = 1;
00407 parent = hierarchy->parent[parent];
00408 }
00409 }
00410 }
00411 int i;
00412 int count = 0;
00413 for(j = 0; j < hierarchy->groups; ++j){
00414
00415 int mask = 1;
00416 for(i = 0; i < hierarchy->group_size[j]; ++i){
00417 if(truth[count + i]){
00418 mask = 0;
00419 break;
00420 }
00421 }
00422 if (mask) {
00423 for(i = 0; i < hierarchy->group_size[j]; ++i){
00424 truth[count + i] = SECRET_NUM;
00425 }
00426 }
00427 count += hierarchy->group_size[j];
00428 }
00429 }
00430
00431 matrix load_labels_paths(char **paths, int n, char **labels, int k, tree *hierarchy)
00432 {
00433 matrix y = make_matrix(n, k);
00434 int i;
00435 for(i = 0; i < n && labels; ++i){
00436 fill_truth(paths[i], labels, k, y.vals[i]);
00437 if(hierarchy){
00438 fill_hierarchy(y.vals[i], k, hierarchy);
00439 }
00440 }
00441 return y;
00442 }
00443
00444 matrix load_tags_paths(char **paths, int n, int k)
00445 {
00446 matrix y = make_matrix(n, k);
00447 int i;
00448 int count = 0;
00449 for(i = 0; i < n; ++i){
00450 char label[4096];
00451 find_replace(paths[i], "imgs", "labels", label);
00452 find_replace(label, "_iconl.jpeg", ".txt", label);
00453 FILE *file = fopen(label, "r");
00454 if(!file){
00455 find_replace(label, "labels", "labels2", label);
00456 file = fopen(label, "r");
00457 if(!file) continue;
00458 }
00459 ++count;
00460 int tag;
00461 while(fscanf(file, "%d", &tag) == 1){
00462 if(tag < k){
00463 y.vals[i][tag] = 1;
00464 }
00465 }
00466 fclose(file);
00467 }
00468 printf("%d/%d\n", count, n);
00469 return y;
00470 }
00471
00472 char **get_labels(char *filename)
00473 {
00474 list *plist = get_paths(filename);
00475 char **labels = (char **)list_to_array(plist);
00476 free_list(plist);
00477 return labels;
00478 }
00479
00480 void free_data(data d)
00481 {
00482 if(!d.shallow){
00483 free_matrix(d.X);
00484 free_matrix(d.y);
00485 }else{
00486 free(d.X.vals);
00487 free(d.y.vals);
00488 }
00489 }
00490
00491 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)
00492 {
00493 char **random_paths = get_random_paths(paths, n, m);
00494 int i;
00495 data d = {0};
00496 d.shallow = 0;
00497
00498 d.X.rows = n;
00499 d.X.vals = calloc(d.X.rows, sizeof(float*));
00500 d.X.cols = h*w*3;
00501
00502
00503 int k = size*size*(5+classes);
00504 d.y = make_matrix(n, k);
00505 for(i = 0; i < n; ++i){
00506 image orig = load_image_color(random_paths[i], 0, 0);
00507
00508 int oh = orig.h;
00509 int ow = orig.w;
00510
00511 int dw = (ow*jitter);
00512 int dh = (oh*jitter);
00513
00514 int pleft = rand_uniform(-dw, dw);
00515 int pright = rand_uniform(-dw, dw);
00516 int ptop = rand_uniform(-dh, dh);
00517 int pbot = rand_uniform(-dh, dh);
00518
00519 int swidth = ow - pleft - pright;
00520 int sheight = oh - ptop - pbot;
00521
00522 float sx = (float)swidth / ow;
00523 float sy = (float)sheight / oh;
00524
00525 int flip = rand()%2;
00526 image cropped = crop_image(orig, pleft, ptop, swidth, sheight);
00527
00528 float dx = ((float)pleft/ow)/sx;
00529 float dy = ((float)ptop /oh)/sy;
00530
00531 image sized = resize_image(cropped, w, h);
00532 if(flip) flip_image(sized);
00533 random_distort_image(sized, hue, saturation, exposure);
00534 d.X.vals[i] = sized.data;
00535
00536 fill_truth_region(random_paths[i], d.y.vals[i], classes, size, flip, dx, dy, 1./sx, 1./sy);
00537
00538 free_image(orig);
00539 free_image(cropped);
00540 }
00541 free(random_paths);
00542 return d;
00543 }
00544
00545 data load_data_compare(int n, char **paths, int m, int classes, int w, int h)
00546 {
00547 if(m) paths = get_random_paths(paths, 2*n, m);
00548 int i,j;
00549 data d = {0};
00550 d.shallow = 0;
00551
00552 d.X.rows = n;
00553 d.X.vals = calloc(d.X.rows, sizeof(float*));
00554 d.X.cols = h*w*6;
00555
00556 int k = 2*(classes);
00557 d.y = make_matrix(n, k);
00558 for(i = 0; i < n; ++i){
00559 image im1 = load_image_color(paths[i*2], w, h);
00560 image im2 = load_image_color(paths[i*2+1], w, h);
00561
00562 d.X.vals[i] = calloc(d.X.cols, sizeof(float));
00563 memcpy(d.X.vals[i], im1.data, h*w*3*sizeof(float));
00564 memcpy(d.X.vals[i] + h*w*3, im2.data, h*w*3*sizeof(float));
00565
00566 int id;
00567 float iou;
00568
00569 char imlabel1[4096];
00570 char imlabel2[4096];
00571 find_replace(paths[i*2], "imgs", "labels", imlabel1);
00572 find_replace(imlabel1, "jpg", "txt", imlabel1);
00573 FILE *fp1 = fopen(imlabel1, "r");
00574
00575 while(fscanf(fp1, "%d %f", &id, &iou) == 2){
00576 if (d.y.vals[i][2*id] < iou) d.y.vals[i][2*id] = iou;
00577 }
00578
00579 find_replace(paths[i*2+1], "imgs", "labels", imlabel2);
00580 find_replace(imlabel2, "jpg", "txt", imlabel2);
00581 FILE *fp2 = fopen(imlabel2, "r");
00582
00583 while(fscanf(fp2, "%d %f", &id, &iou) == 2){
00584 if (d.y.vals[i][2*id + 1] < iou) d.y.vals[i][2*id + 1] = iou;
00585 }
00586
00587 for (j = 0; j < classes; ++j){
00588 if (d.y.vals[i][2*j] > .5 && d.y.vals[i][2*j+1] < .5){
00589 d.y.vals[i][2*j] = 1;
00590 d.y.vals[i][2*j+1] = 0;
00591 } else if (d.y.vals[i][2*j] < .5 && d.y.vals[i][2*j+1] > .5){
00592 d.y.vals[i][2*j] = 0;
00593 d.y.vals[i][2*j+1] = 1;
00594 } else {
00595 d.y.vals[i][2*j] = SECRET_NUM;
00596 d.y.vals[i][2*j+1] = SECRET_NUM;
00597 }
00598 }
00599 fclose(fp1);
00600 fclose(fp2);
00601
00602 free_image(im1);
00603 free_image(im2);
00604 }
00605 if(m) free(paths);
00606 return d;
00607 }
00608
00609 data load_data_swag(char **paths, int n, int classes, float jitter)
00610 {
00611 int index = rand()%n;
00612 char *random_path = paths[index];
00613
00614 image orig = load_image_color(random_path, 0, 0);
00615 int h = orig.h;
00616 int w = orig.w;
00617
00618 data d = {0};
00619 d.shallow = 0;
00620 d.w = w;
00621 d.h = h;
00622
00623 d.X.rows = 1;
00624 d.X.vals = calloc(d.X.rows, sizeof(float*));
00625 d.X.cols = h*w*3;
00626
00627 int k = (4+classes)*30;
00628 d.y = make_matrix(1, k);
00629
00630 int dw = w*jitter;
00631 int dh = h*jitter;
00632
00633 int pleft = rand_uniform(-dw, dw);
00634 int pright = rand_uniform(-dw, dw);
00635 int ptop = rand_uniform(-dh, dh);
00636 int pbot = rand_uniform(-dh, dh);
00637
00638 int swidth = w - pleft - pright;
00639 int sheight = h - ptop - pbot;
00640
00641 float sx = (float)swidth / w;
00642 float sy = (float)sheight / h;
00643
00644 int flip = rand()%2;
00645 image cropped = crop_image(orig, pleft, ptop, swidth, sheight);
00646
00647 float dx = ((float)pleft/w)/sx;
00648 float dy = ((float)ptop /h)/sy;
00649
00650 image sized = resize_image(cropped, w, h);
00651 if(flip) flip_image(sized);
00652 d.X.vals[0] = sized.data;
00653
00654 fill_truth_swag(random_path, d.y.vals[0], classes, flip, dx, dy, 1./sx, 1./sy);
00655
00656 free_image(orig);
00657 free_image(cropped);
00658
00659 return d;
00660 }
00661
00662 data load_data_detection(int n, char **paths, int m, int w, int h, int boxes, int classes, float jitter, float hue, float saturation, float exposure)
00663 {
00664 char **random_paths = get_random_paths(paths, n, m);
00665 int i;
00666 data d = {0};
00667 d.shallow = 0;
00668
00669 d.X.rows = n;
00670 d.X.vals = calloc(d.X.rows, sizeof(float*));
00671 d.X.cols = h*w*3;
00672
00673 d.y = make_matrix(n, 5*boxes);
00674 for(i = 0; i < n; ++i){
00675 image orig = load_image_color(random_paths[i], 0, 0);
00676
00677 int oh = orig.h;
00678 int ow = orig.w;
00679
00680 int dw = (ow*jitter);
00681 int dh = (oh*jitter);
00682
00683 int pleft = rand_uniform(-dw, dw);
00684 int pright = rand_uniform(-dw, dw);
00685 int ptop = rand_uniform(-dh, dh);
00686 int pbot = rand_uniform(-dh, dh);
00687
00688 int swidth = ow - pleft - pright;
00689 int sheight = oh - ptop - pbot;
00690
00691 float sx = (float)swidth / ow;
00692 float sy = (float)sheight / oh;
00693
00694 int flip = rand()%2;
00695 image cropped = crop_image(orig, pleft, ptop, swidth, sheight);
00696
00697 float dx = ((float)pleft/ow)/sx;
00698 float dy = ((float)ptop /oh)/sy;
00699
00700 image sized = resize_image(cropped, w, h);
00701 if(flip) flip_image(sized);
00702 random_distort_image(sized, hue, saturation, exposure);
00703 d.X.vals[i] = sized.data;
00704
00705 fill_truth_detection(random_paths[i], boxes, d.y.vals[i], classes, flip, dx, dy, 1./sx, 1./sy);
00706
00707 free_image(orig);
00708 free_image(cropped);
00709 }
00710 free(random_paths);
00711 return d;
00712 }
00713
00714
00715 void *load_thread(void *ptr)
00716 {
00717
00718 load_args a = *(struct load_args*)ptr;
00719 if(a.exposure == 0) a.exposure = 1;
00720 if(a.saturation == 0) a.saturation = 1;
00721 if(a.aspect == 0) a.aspect = 1;
00722
00723 if (a.type == OLD_CLASSIFICATION_DATA){
00724 *a.d = load_data_old(a.paths, a.n, a.m, a.labels, a.classes, a.w, a.h);
00725 } else if (a.type == CLASSIFICATION_DATA){
00726 *a.d = load_data_augment(a.paths, a.n, a.m, a.labels, a.classes, a.hierarchy, a.min, a.max, a.size, a.angle, a.aspect, a.hue, a.saturation, a.exposure);
00727 } else if (a.type == SUPER_DATA){
00728 *a.d = load_data_super(a.paths, a.n, a.m, a.w, a.h, a.scale);
00729 } else if (a.type == WRITING_DATA){
00730 *a.d = load_data_writing(a.paths, a.n, a.m, a.w, a.h, a.out_w, a.out_h);
00731 } else if (a.type == REGION_DATA){
00732 *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);
00733 } else if (a.type == DETECTION_DATA){
00734 *a.d = load_data_detection(a.n, a.paths, a.m, a.w, a.h, a.num_boxes, a.classes, a.jitter, a.hue, a.saturation, a.exposure);
00735 } else if (a.type == SWAG_DATA){
00736 *a.d = load_data_swag(a.paths, a.n, a.classes, a.jitter);
00737 } else if (a.type == COMPARE_DATA){
00738 *a.d = load_data_compare(a.n, a.paths, a.m, a.classes, a.w, a.h);
00739 } else if (a.type == IMAGE_DATA){
00740 *(a.im) = load_image_color(a.path, 0, 0);
00741 *(a.resized) = resize_image(*(a.im), a.w, a.h);
00742 } else if (a.type == TAG_DATA){
00743 *a.d = load_data_tag(a.paths, a.n, a.m, a.classes, a.min, a.max, a.size, a.angle, a.aspect, a.hue, a.saturation, a.exposure);
00744 }
00745 free(ptr);
00746 return 0;
00747 }
00748
00749 pthread_t load_data_in_thread(load_args args)
00750 {
00751 pthread_t thread;
00752 struct load_args *ptr = calloc(1, sizeof(struct load_args));
00753 *ptr = args;
00754 if(pthread_create(&thread, 0, load_thread, ptr)) error("Thread creation failed");
00755 return thread;
00756 }
00757
00758 void *load_threads(void *ptr)
00759 {
00760 int i;
00761 load_args args = *(load_args *)ptr;
00762 if (args.threads == 0) args.threads = 1;
00763 data *out = args.d;
00764 int total = args.n;
00765 free(ptr);
00766 data *buffers = calloc(args.threads, sizeof(data));
00767 pthread_t *threads = calloc(args.threads, sizeof(pthread_t));
00768 for(i = 0; i < args.threads; ++i){
00769 args.d = buffers + i;
00770 args.n = (i+1) * total/args.threads - i * total/args.threads;
00771 threads[i] = load_data_in_thread(args);
00772 }
00773 for(i = 0; i < args.threads; ++i){
00774 pthread_join(threads[i], 0);
00775 }
00776 *out = concat_datas(buffers, args.threads);
00777 out->shallow = 0;
00778 for(i = 0; i < args.threads; ++i){
00779 buffers[i].shallow = 1;
00780 free_data(buffers[i]);
00781 }
00782 free(buffers);
00783 free(threads);
00784 return 0;
00785 }
00786
00787 pthread_t load_data(load_args args)
00788 {
00789 pthread_t thread;
00790 struct load_args *ptr = calloc(1, sizeof(struct load_args));
00791 *ptr = args;
00792 if(pthread_create(&thread, 0, load_threads, ptr)) error("Thread creation failed");
00793 return thread;
00794 }
00795
00796 data load_data_writing(char **paths, int n, int m, int w, int h, int out_w, int out_h)
00797 {
00798 if(m) paths = get_random_paths(paths, n, m);
00799 char **replace_paths = find_replace_paths(paths, n, ".png", "-label.png");
00800 data d = {0};
00801 d.shallow = 0;
00802 d.X = load_image_paths(paths, n, w, h);
00803 d.y = load_image_paths_gray(replace_paths, n, out_w, out_h);
00804 if(m) free(paths);
00805 int i;
00806 for(i = 0; i < n; ++i) free(replace_paths[i]);
00807 free(replace_paths);
00808 return d;
00809 }
00810
00811 data load_data_old(char **paths, int n, int m, char **labels, int k, int w, int h)
00812 {
00813 if(m) paths = get_random_paths(paths, n, m);
00814 data d = {0};
00815 d.shallow = 0;
00816 d.X = load_image_paths(paths, n, w, h);
00817 d.y = load_labels_paths(paths, n, labels, k, 0);
00818 if(m) free(paths);
00819 return d;
00820 }
00821
00822
00823
00824
00825
00826
00827
00828
00829
00830
00831
00832
00833
00834
00835
00836 data load_data_super(char **paths, int n, int m, int w, int h, int scale)
00837 {
00838 if(m) paths = get_random_paths(paths, n, m);
00839 data d = {0};
00840 d.shallow = 0;
00841
00842 int i;
00843 d.X.rows = n;
00844 d.X.vals = calloc(n, sizeof(float*));
00845 d.X.cols = w*h*3;
00846
00847 d.y.rows = n;
00848 d.y.vals = calloc(n, sizeof(float*));
00849 d.y.cols = w*scale * h*scale * 3;
00850
00851 for(i = 0; i < n; ++i){
00852 image im = load_image_color(paths[i], 0, 0);
00853 image crop = random_crop_image(im, w*scale, h*scale);
00854 int flip = rand()%2;
00855 if (flip) flip_image(crop);
00856 image resize = resize_image(crop, w, h);
00857 d.X.vals[i] = resize.data;
00858 d.y.vals[i] = crop.data;
00859 free_image(im);
00860 }
00861
00862 if(m) free(paths);
00863 return d;
00864 }
00865
00866 data load_data_augment(char **paths, int n, int m, char **labels, int k, tree *hierarchy, int min, int max, int size, float angle, float aspect, float hue, float saturation, float exposure)
00867 {
00868 if(m) paths = get_random_paths(paths, n, m);
00869 data d = {0};
00870 d.shallow = 0;
00871 d.X = load_image_augment_paths(paths, n, min, max, size, angle, aspect, hue, saturation, exposure);
00872 d.y = load_labels_paths(paths, n, labels, k, hierarchy);
00873 if(m) free(paths);
00874 return d;
00875 }
00876
00877 data load_data_tag(char **paths, int n, int m, int k, int min, int max, int size, float angle, float aspect, float hue, float saturation, float exposure)
00878 {
00879 if(m) paths = get_random_paths(paths, n, m);
00880 data d = {0};
00881 d.w = size;
00882 d.h = size;
00883 d.shallow = 0;
00884 d.X = load_image_augment_paths(paths, n, min, max, size, angle, aspect, hue, saturation, exposure);
00885 d.y = load_tags_paths(paths, n, k);
00886 if(m) free(paths);
00887 return d;
00888 }
00889
00890 matrix concat_matrix(matrix m1, matrix m2)
00891 {
00892 int i, count = 0;
00893 matrix m;
00894 m.cols = m1.cols;
00895 m.rows = m1.rows+m2.rows;
00896 m.vals = calloc(m1.rows + m2.rows, sizeof(float*));
00897 for(i = 0; i < m1.rows; ++i){
00898 m.vals[count++] = m1.vals[i];
00899 }
00900 for(i = 0; i < m2.rows; ++i){
00901 m.vals[count++] = m2.vals[i];
00902 }
00903 return m;
00904 }
00905
00906 data concat_data(data d1, data d2)
00907 {
00908 data d = {0};
00909 d.shallow = 1;
00910 d.X = concat_matrix(d1.X, d2.X);
00911 d.y = concat_matrix(d1.y, d2.y);
00912 return d;
00913 }
00914
00915 data concat_datas(data *d, int n)
00916 {
00917 int i;
00918 data out = {0};
00919 for(i = 0; i < n; ++i){
00920 data new = concat_data(d[i], out);
00921 free_data(out);
00922 out = new;
00923 }
00924 return out;
00925 }
00926
00927 data load_categorical_data_csv(char *filename, int target, int k)
00928 {
00929 data d = {0};
00930 d.shallow = 0;
00931 matrix X = csv_to_matrix(filename);
00932 float *truth_1d = pop_column(&X, target);
00933 float **truth = one_hot_encode(truth_1d, X.rows, k);
00934 matrix y;
00935 y.rows = X.rows;
00936 y.cols = k;
00937 y.vals = truth;
00938 d.X = X;
00939 d.y = y;
00940 free(truth_1d);
00941 return d;
00942 }
00943
00944 data load_cifar10_data(char *filename)
00945 {
00946 data d = {0};
00947 d.shallow = 0;
00948 long i,j;
00949 matrix X = make_matrix(10000, 3072);
00950 matrix y = make_matrix(10000, 10);
00951 d.X = X;
00952 d.y = y;
00953
00954 FILE *fp = fopen(filename, "rb");
00955 if(!fp) file_error(filename);
00956 for(i = 0; i < 10000; ++i){
00957 unsigned char bytes[3073];
00958 fread(bytes, 1, 3073, fp);
00959 int class = bytes[0];
00960 y.vals[i][class] = 1;
00961 for(j = 0; j < X.cols; ++j){
00962 X.vals[i][j] = (double)bytes[j+1];
00963 }
00964 }
00965
00966 scale_data_rows(d, 1./255);
00967
00968 fclose(fp);
00969 return d;
00970 }
00971
00972 void get_random_batch(data d, int n, float *X, float *y)
00973 {
00974 int j;
00975 for(j = 0; j < n; ++j){
00976 int index = rand()%d.X.rows;
00977 memcpy(X+j*d.X.cols, d.X.vals[index], d.X.cols*sizeof(float));
00978 memcpy(y+j*d.y.cols, d.y.vals[index], d.y.cols*sizeof(float));
00979 }
00980 }
00981
00982 void get_next_batch(data d, int n, int offset, float *X, float *y)
00983 {
00984 int j;
00985 for(j = 0; j < n; ++j){
00986 int index = offset + j;
00987 memcpy(X+j*d.X.cols, d.X.vals[index], d.X.cols*sizeof(float));
00988 memcpy(y+j*d.y.cols, d.y.vals[index], d.y.cols*sizeof(float));
00989 }
00990 }
00991
00992 void smooth_data(data d)
00993 {
00994 int i, j;
00995 float scale = 1. / d.y.cols;
00996 float eps = .1;
00997 for(i = 0; i < d.y.rows; ++i){
00998 for(j = 0; j < d.y.cols; ++j){
00999 d.y.vals[i][j] = eps * scale + (1-eps) * d.y.vals[i][j];
01000 }
01001 }
01002 }
01003
01004 data load_all_cifar10()
01005 {
01006 data d = {0};
01007 d.shallow = 0;
01008 int i,j,b;
01009 matrix X = make_matrix(50000, 3072);
01010 matrix y = make_matrix(50000, 10);
01011 d.X = X;
01012 d.y = y;
01013
01014
01015 for(b = 0; b < 5; ++b){
01016 char buff[256];
01017 sprintf(buff, "data/cifar/cifar-10-batches-bin/data_batch_%d.bin", b+1);
01018 FILE *fp = fopen(buff, "rb");
01019 if(!fp) file_error(buff);
01020 for(i = 0; i < 10000; ++i){
01021 unsigned char bytes[3073];
01022 fread(bytes, 1, 3073, fp);
01023 int class = bytes[0];
01024 y.vals[i+b*10000][class] = 1;
01025 for(j = 0; j < X.cols; ++j){
01026 X.vals[i+b*10000][j] = (double)bytes[j+1];
01027 }
01028 }
01029 fclose(fp);
01030 }
01031
01032
01033 scale_data_rows(d, 1./255);
01034 smooth_data(d);
01035 return d;
01036 }
01037
01038 data load_go(char *filename)
01039 {
01040 FILE *fp = fopen(filename, "rb");
01041 matrix X = make_matrix(3363059, 361);
01042 matrix y = make_matrix(3363059, 361);
01043 int row, col;
01044
01045 if(!fp) file_error(filename);
01046 char *label;
01047 int count = 0;
01048 while((label = fgetl(fp))){
01049 int i;
01050 if(count == X.rows){
01051 X = resize_matrix(X, count*2);
01052 y = resize_matrix(y, count*2);
01053 }
01054 sscanf(label, "%d %d", &row, &col);
01055 char *board = fgetl(fp);
01056
01057 int index = row*19 + col;
01058 y.vals[count][index] = 1;
01059
01060 for(i = 0; i < 19*19; ++i){
01061 float val = 0;
01062 if(board[i] == '1') val = 1;
01063 else if(board[i] == '2') val = -1;
01064 X.vals[count][i] = val;
01065 }
01066 ++count;
01067 free(label);
01068 free(board);
01069 }
01070 X = resize_matrix(X, count);
01071 y = resize_matrix(y, count);
01072
01073 data d = {0};
01074 d.shallow = 0;
01075 d.X = X;
01076 d.y = y;
01077
01078
01079 fclose(fp);
01080
01081 return d;
01082 }
01083
01084
01085 void randomize_data(data d)
01086 {
01087 int i;
01088 for(i = d.X.rows-1; i > 0; --i){
01089 int index = rand()%i;
01090 float *swap = d.X.vals[index];
01091 d.X.vals[index] = d.X.vals[i];
01092 d.X.vals[i] = swap;
01093
01094 swap = d.y.vals[index];
01095 d.y.vals[index] = d.y.vals[i];
01096 d.y.vals[i] = swap;
01097 }
01098 }
01099
01100 void scale_data_rows(data d, float s)
01101 {
01102 int i;
01103 for(i = 0; i < d.X.rows; ++i){
01104 scale_array(d.X.vals[i], d.X.cols, s);
01105 }
01106 }
01107
01108 void translate_data_rows(data d, float s)
01109 {
01110 int i;
01111 for(i = 0; i < d.X.rows; ++i){
01112 translate_array(d.X.vals[i], d.X.cols, s);
01113 }
01114 }
01115
01116 void normalize_data_rows(data d)
01117 {
01118 int i;
01119 for(i = 0; i < d.X.rows; ++i){
01120 normalize_array(d.X.vals[i], d.X.cols);
01121 }
01122 }
01123
01124 data get_data_part(data d, int part, int total)
01125 {
01126 data p = {0};
01127 p.shallow = 1;
01128 p.X.rows = d.X.rows * (part + 1) / total - d.X.rows * part / total;
01129 p.y.rows = d.y.rows * (part + 1) / total - d.y.rows * part / total;
01130 p.X.cols = d.X.cols;
01131 p.y.cols = d.y.cols;
01132 p.X.vals = d.X.vals + d.X.rows * part / total;
01133 p.y.vals = d.y.vals + d.y.rows * part / total;
01134 return p;
01135 }
01136
01137 data get_random_data(data d, int num)
01138 {
01139 data r = {0};
01140 r.shallow = 1;
01141
01142 r.X.rows = num;
01143 r.y.rows = num;
01144
01145 r.X.cols = d.X.cols;
01146 r.y.cols = d.y.cols;
01147
01148 r.X.vals = calloc(num, sizeof(float *));
01149 r.y.vals = calloc(num, sizeof(float *));
01150
01151 int i;
01152 for(i = 0; i < num; ++i){
01153 int index = rand()%d.X.rows;
01154 r.X.vals[i] = d.X.vals[index];
01155 r.y.vals[i] = d.y.vals[index];
01156 }
01157 return r;
01158 }
01159
01160 data *split_data(data d, int part, int total)
01161 {
01162 data *split = calloc(2, sizeof(data));
01163 int i;
01164 int start = part*d.X.rows/total;
01165 int end = (part+1)*d.X.rows/total;
01166 data train;
01167 data test;
01168 train.shallow = test.shallow = 1;
01169
01170 test.X.rows = test.y.rows = end-start;
01171 train.X.rows = train.y.rows = d.X.rows - (end-start);
01172 train.X.cols = test.X.cols = d.X.cols;
01173 train.y.cols = test.y.cols = d.y.cols;
01174
01175 train.X.vals = calloc(train.X.rows, sizeof(float*));
01176 test.X.vals = calloc(test.X.rows, sizeof(float*));
01177 train.y.vals = calloc(train.y.rows, sizeof(float*));
01178 test.y.vals = calloc(test.y.rows, sizeof(float*));
01179
01180 for(i = 0; i < start; ++i){
01181 train.X.vals[i] = d.X.vals[i];
01182 train.y.vals[i] = d.y.vals[i];
01183 }
01184 for(i = start; i < end; ++i){
01185 test.X.vals[i-start] = d.X.vals[i];
01186 test.y.vals[i-start] = d.y.vals[i];
01187 }
01188 for(i = end; i < d.X.rows; ++i){
01189 train.X.vals[i-(end-start)] = d.X.vals[i];
01190 train.y.vals[i-(end-start)] = d.y.vals[i];
01191 }
01192 split[0] = train;
01193 split[1] = test;
01194 return split;
01195 }
01196