sides of box instead of coords
| | |
| | | int w; |
| | | int nh; |
| | | int nw; |
| | | int num_boxes; |
| | | int jitter; |
| | | int classes; |
| | | int background; |
| | |
| | | } |
| | | } |
| | | |
| | | void fill_truth_detection(char *path, float *truth, int classes, int height, int width, int num_height, int num_width, int dy, int dx, int jitter, int flip, int background) |
| | | 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) |
| | | { |
| | | int box_height = height/num_height; |
| | | int box_width = width/num_width; |
| | | char *labelpath = find_replace(path, "VOC2012/JPEGImages", "labels"); |
| | | labelpath = find_replace(labelpath, ".jpg", ".txt"); |
| | | int count = 0; |
| | | box *boxes = read_boxes(labelpath, &count); |
| | | randomize_boxes(boxes, count); |
| | | float x, y, h, w; |
| | | float l,r,t,b; |
| | | int id; |
| | | int i; |
| | | if(background){ |
| | | for(i = 0; i < num_height*num_width*(4+classes+background); i += 4+classes+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){ |
| | | x = boxes[i].x; |
| | | y = boxes[i].y; |
| | | w = boxes[i].w; |
| | | h = boxes[i].h; |
| | | l = boxes[i].left; |
| | | r = boxes[i].right; |
| | | t = boxes[i].top; |
| | | b = boxes[i].bottom; |
| | | id = boxes[i].id; |
| | | if(flip) x = 1-x; |
| | | x *= width + jitter; |
| | | y *= height + jitter; |
| | | x -= dx; |
| | | y -= dy; |
| | | int i = x/box_width; |
| | | int j = y/box_height; |
| | | |
| | | if(i < 0) i = 0; |
| | | if(i >= num_width) i = num_width-1; |
| | | if(j < 0) j = 0; |
| | | if(j >= num_height) j = num_height-1; |
| | | if(flip){ |
| | | float left = l; |
| | | float right = r; |
| | | r = 1-left; |
| | | l = 1-right; |
| | | } |
| | | |
| | | float dw = constrain(0,1, (x - i*box_width)/box_width ); |
| | | float dh = constrain(0,1, (y - j*box_height)/box_height ); |
| | | float th = constrain(0,1, h*(height+jitter)/height ); |
| | | float tw = constrain(0,1, w*(width+jitter)/width ); |
| | | l = l*sx-dx; |
| | | r = r*sx-dx; |
| | | t = t*sy-dy; |
| | | b = b*sy-dy; |
| | | |
| | | int index = (i+j*num_width)*(4+classes+background); |
| | | float x = (l+r)/2.; |
| | | float y = (t+b)/2.; |
| | | |
| | | if (x < 0 || x >= 1 || y < 0 || y >= 1) continue; |
| | | |
| | | int i = (int)(x*num_boxes); |
| | | int j = (int)(y*num_boxes); |
| | | |
| | | l = constrain(0, 1, l); |
| | | r = constrain(0, 1, r); |
| | | t = constrain(0, 1, t); |
| | | b = constrain(0, 1, b); |
| | | |
| | | int index = (i+j*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++] = dh; |
| | | truth[index++] = dw; |
| | | truth[index++] = th; |
| | | truth[index++] = tw; |
| | | truth[index++] = l; |
| | | truth[index++] = r; |
| | | truth[index++] = t; |
| | | truth[index++] = b; |
| | | } |
| | | free(boxes); |
| | | } |
| | |
| | | } |
| | | } |
| | | |
| | | data load_data_detection_jitter_random(int n, char **paths, int m, int classes, int h, int w, int nh, int nw, int jitter, int background) |
| | | data load_data_detection_jitter_random(int n, char **paths, int m, int classes, int h, int w, int num_boxes, int jitter, int background) |
| | | { |
| | | char **random_paths = get_random_paths(paths, n, m); |
| | | int i; |
| | | data d; |
| | | d.shallow = 0; |
| | | d.X = load_image_paths(random_paths, n, h, w); |
| | | int k = nh*nw*(4+classes+background); |
| | | int k = num_boxes*num_boxes*(4+classes+background); |
| | | d.y = make_matrix(n, k); |
| | | for(i = 0; i < n; ++i){ |
| | | int dx = rand()%jitter; |
| | | int dy = rand()%jitter; |
| | | int px = rand()%jitter; |
| | | px = 0; |
| | | int py = rand()%jitter; |
| | | py = 0; |
| | | float sy = (float) h / (h-jitter); |
| | | float sx = (float) w / (w-jitter); |
| | | float dy = (float) py / (h-jitter); |
| | | float dx = (float) px / (w-jitter); |
| | | |
| | | int flip = rand()%2; |
| | | fill_truth_detection(random_paths[i], d.y.vals[i], classes, h-jitter, w-jitter, nh, nw, dy, dx, jitter, flip, background); |
| | | fill_truth_detection(random_paths[i], d.y.vals[i], classes, num_boxes, flip, background, dx, dy, sx, sy); |
| | | image a = float_to_image(h, w, 3, d.X.vals[i]); |
| | | if(flip) flip_image(a); |
| | | jitter_image(a,h-jitter,w-jitter,dy,dx); |
| | | jitter_image(a, h-jitter, w-jitter, py, px); |
| | | } |
| | | d.X.cols = (h-jitter)*(w-jitter)*3; |
| | | free(random_paths); |
| | |
| | | { |
| | | printf("Loading data: %d\n", rand()); |
| | | struct load_args a = *(struct load_args*)ptr; |
| | | *a.d = load_data_detection_jitter_random(a.n, a.paths, a.m, a.classes, a.h, a.w, a.nh, a.nw, a.jitter, a.background); |
| | | *a.d = load_data_detection_jitter_random(a.n, a.paths, a.m, a.classes, a.h, a.w, a.num_boxes, a.jitter, a.background); |
| | | translate_data_rows(*a.d, -128); |
| | | scale_data_rows(*a.d, 1./128); |
| | | free(ptr); |
| | |
| | | args->w = w; |
| | | args->nh = nh; |
| | | args->nw = nw; |
| | | args->num_boxes = nw; |
| | | args->classes = classes; |
| | | args->jitter = jitter; |
| | | args->background = background; |
| | |
| | | pthread_t load_data_thread(char **paths, int n, int m, char **labels, int k, int h, int w, data *d); |
| | | |
| | | pthread_t load_data_detection_thread(int n, char **paths, int m, int classes, int h, int w, int nh, int nw, int jitter, int background, data *d); |
| | | data load_data_detection_jitter_random(int n, char **paths, int m, int classes, int h, int w, int nh, int nw, int jitter, int background); |
| | | data load_data_detection_jitter_random(int n, char **paths, int m, int classes, int h, int w, int num_boxes, int jitter, int background); |
| | | |
| | | data load_data_image_pathfile(char *filename, char **labels, int k, int h, int w); |
| | | data load_cifar10_data(char *filename); |
| | |
| | | float blue = get_color(2,class,classes); |
| | | |
| | | j += classes; |
| | | int d = im.w/side; |
| | | int y = r*d+box[j]*d; |
| | | int x = c*d+box[j+1]*d; |
| | | int h = box[j+2]*im.h; |
| | | int w = box[j+3]*im.w; |
| | | draw_box(im, x-w/2, y-h/2, x+w/2, y+h/2,red,green,blue); |
| | | int left = box[j] *im.w; |
| | | int right = box[j+1]*im.w; |
| | | int top = box[j+2]*im.h; |
| | | int bot = box[j+3]*im.h; |
| | | draw_box(im, left, top, right, bot, red, green, blue); |
| | | } |
| | | } |
| | | } |
| | |
| | | float scale = 1.; |
| | | if(nuisance) scale = 1.-pred.vals[j][k]; |
| | | for(class = 0; class < classes; ++class){ |
| | | int index = (k)/(classes+4+background+nuisance); |
| | | int r = index/7; |
| | | int c = index%7; |
| | | int ci = k+classes+background+nuisance; |
| | | float y = (r + pred.vals[j][ci + 0])/7.; |
| | | float x = (c + pred.vals[j][ci + 1])/7.; |
| | | float h = pred.vals[j][ci + 2]; |
| | | float w = pred.vals[j][ci + 3]; |
| | | printf("%d %d %f %f %f %f %f\n", (i-1)*m/splits + j, class, scale*pred.vals[j][k+class+background+nuisance], y, x, h, w); |
| | | float left = pred.vals[j][ci + 0]; |
| | | float right = pred.vals[j][ci + 1]; |
| | | float top = pred.vals[j][ci + 2]; |
| | | float bot = pred.vals[j][ci + 3]; |
| | | printf("%d %d %f %f %f %f %f\n", (i-1)*m/splits + j, class, scale*pred.vals[j][k+class+background+nuisance], left, right, top, bot); |
| | | } |
| | | } |
| | | } |