| | |
| | | free(boxes); |
| | | } |
| | | |
| | | void fill_truth_detection(char *path, float *truth, int classes, int num_boxes, int flip, int background, float dx, float dy, float sx, float sy) |
| | | void fill_truth_detection(char *path, float *truth, int classes, int flip, float dx, float dy, float sx, float sy) |
| | | { |
| | | char *labelpath = find_replace(path, "JPEGImages", "labels"); |
| | | char *labelpath = find_replace(path, "images", "labels"); |
| | | labelpath = find_replace(labelpath, "JPEGImages", "labels"); |
| | | |
| | | labelpath = find_replace(labelpath, ".jpg", ".txt"); |
| | | labelpath = find_replace(labelpath, ".JPG", ".txt"); |
| | | labelpath = find_replace(labelpath, ".JPEG", ".txt"); |
| | | int count = 0; |
| | | box_label *boxes = read_boxes(labelpath, &count); |
| | | randomize_boxes(boxes, count); |
| | | correct_boxes(boxes, count, dx, dy, sx, sy, flip); |
| | | if(count > 17) count = 17; |
| | | float x,y,w,h; |
| | | float left, top, right, bot; |
| | | int id; |
| | | int i; |
| | | if(background){ |
| | | for(i = 0; i < num_boxes*num_boxes*(4+classes+background); i += 4+classes+background){ |
| | | truth[i] = 1; |
| | | } |
| | | } |
| | | for(i = 0; i < count; ++i){ |
| | | left = boxes[i].left * sx - dx; |
| | | right = boxes[i].right * sx - dx; |
| | | top = boxes[i].top * sy - dy; |
| | | bot = boxes[i].bottom* sy - dy; |
| | | |
| | | 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(flip){ |
| | | float swap = left; |
| | | left = 1. - right; |
| | | right = 1. - swap; |
| | | } |
| | | |
| | | left = constrain(0, 1, left); |
| | | right = constrain(0, 1, right); |
| | | top = constrain(0, 1, top); |
| | | bot = constrain(0, 1, bot); |
| | | |
| | | x = (left+right)/2; |
| | | y = (top+bot)/2; |
| | | w = (right - left); |
| | | h = (bot - top); |
| | | |
| | | if (x <= 0 || x >= 1 || y <= 0 || y >= 1) continue; |
| | | |
| | | int col = (int)(x*num_boxes); |
| | | int row = (int)(y*num_boxes); |
| | | |
| | | x = x*num_boxes - col; |
| | | y = y*num_boxes - row; |
| | | |
| | | /* |
| | | float maxwidth = distance_from_edge(i, num_boxes); |
| | | float maxheight = distance_from_edge(j, num_boxes); |
| | | w = w/maxwidth; |
| | | h = h/maxheight; |
| | | */ |
| | | |
| | | w = constrain(0, 1, w); |
| | | h = constrain(0, 1, h); |
| | | if (w < .01 || h < .01) continue; |
| | | if(1){ |
| | | w = pow(w, 1./2.); |
| | | h = pow(h, 1./2.); |
| | | } |
| | | |
| | | int index = (col+row*num_boxes)*(4+classes+background); |
| | | if(truth[index+classes+background+2]) continue; |
| | | if(background) truth[index++] = 0; |
| | | truth[index+id] = 1; |
| | | index += classes; |
| | | truth[index++] = x; |
| | | truth[index++] = y; |
| | | truth[index++] = w; |
| | | truth[index++] = h; |
| | | truth[i*5] = id; |
| | | truth[i*5+2] = x; |
| | | truth[i*5+3] = y; |
| | | truth[i*5+4] = w; |
| | | truth[i*5+5] = h; |
| | | } |
| | | free(boxes); |
| | | } |
| | |
| | | d.X.vals = calloc(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){ |
| | |
| | | return d; |
| | | } |
| | | |
| | | data load_data_detection(int n, char **paths, int m, int classes, int w, int h, int num_boxes, int background) |
| | | data load_data_detection(int n, int boxes, char **paths, int m, int w, int h, int classes, float jitter) |
| | | { |
| | | char **random_paths = get_random_paths(paths, n, m); |
| | | int i; |
| | |
| | | d.X.vals = calloc(d.X.rows, sizeof(float*)); |
| | | d.X.cols = h*w*3; |
| | | |
| | | int k = num_boxes*num_boxes*(4+classes+background); |
| | | d.y = make_matrix(n, k); |
| | | d.y = make_matrix(n, 5*boxes); |
| | | 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/10; |
| | | int dh = oh/10; |
| | | int dw = (ow*jitter); |
| | | int dh = (oh*jitter); |
| | | |
| | | int pleft = rand_uniform(-dw, dw); |
| | | int pright = rand_uniform(-dw, dw); |
| | |
| | | float sx = (float)swidth / ow; |
| | | float sy = (float)sheight / oh; |
| | | |
| | | /* |
| | | float angle = rand_uniform()*.1 - .05; |
| | | image rot = rotate_image(orig, angle); |
| | | free_image(orig); |
| | | orig = rot; |
| | | */ |
| | | |
| | | int flip = rand_r(&data_seed)%2; |
| | | image cropped = crop_image(orig, pleft, ptop, swidth, sheight); |
| | | |
| | |
| | | if(flip) flip_image(sized); |
| | | d.X.vals[i] = sized.data; |
| | | |
| | | fill_truth_detection(random_paths[i], d.y.vals[i], classes, num_boxes, flip, background, dx, dy, 1./sx, 1./sy); |
| | | fill_truth_detection(random_paths[i], d.y.vals[i], classes, flip, dx, dy, 1./sx, 1./sy); |
| | | |
| | | free_image(orig); |
| | | free_image(cropped); |
| | |
| | | return d; |
| | | } |
| | | |
| | | |
| | | void *load_thread(void *ptr) |
| | | { |
| | | |
| | |
| | | } else if (a.type == STUDY_DATA){ |
| | | *a.d = load_data_study(a.paths, a.n, a.m, a.labels, a.classes, a.min, a.max, a.size); |
| | | } else if (a.type == DETECTION_DATA){ |
| | | *a.d = load_data_detection(a.n, a.paths, a.m, a.classes, a.w, a.h, a.num_boxes, a.background); |
| | | *a.d = load_data_detection(a.n, a.num_boxes, a.paths, a.m, a.classes, a.w, a.h, a.background); |
| | | } 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){ |