| | |
| | | } |
| | | |
| | | #ifdef OPENCV |
| | | void calc_anchors(char *datacfg, int num_of_clusters, int final_width, int final_height) |
| | | void calc_anchors(char *datacfg, int num_of_clusters, int final_width, int final_height, int show) |
| | | { |
| | | printf("\n num_of_clusters = %d, final_width = %d, final_height = %d \n", num_of_clusters, final_width, final_height); |
| | | |
| | |
| | | } |
| | | printf("\n all loaded. \n"); |
| | | |
| | | //int number_of_boxes = 10; |
| | | CvMat* points = cvCreateMat(number_of_boxes, 2, CV_32FC1); |
| | | CvMat* centers = cvCreateMat(num_of_clusters, 2, CV_32FC1); |
| | | CvMat* labels = cvCreateMat(number_of_boxes, 1, CV_32SC1); |
| | |
| | | } |
| | | |
| | | |
| | | const int attemps = 1000; |
| | | const int attemps = 10; |
| | | double compactness; |
| | | |
| | | enum { |
| | |
| | | printf("\n calculating k-means++ ..."); |
| | | // Should be used: distance(box, centroid) = 1 - IoU(box, centroid) |
| | | cvKMeans2(points, num_of_clusters, labels, |
| | | cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 1000, 0), attemps, |
| | | 0, KMEANS_RANDOM_CENTERS, |
| | | cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 10000, 0), attemps, |
| | | 0, KMEANS_PP_CENTERS, |
| | | centers, &compactness); |
| | | |
| | | printf("\n"); |
| | | printf("anchors = "); |
| | | for (i = 0; i < num_of_clusters; ++i) { |
| | | printf("%2.2f,%2.2f, ", centers->data.fl[i * 2], centers->data.fl[i * 2 + 1]); |
| | | } |
| | | //orig 2.0 anchors = 1.08,1.19, 3.42,4.41, 6.63,11.38, 9.42,5.11, 16.62,10.52 |
| | | //float orig_anch[] = { 1.08,1.19, 3.42,4.41, 6.63,11.38, 9.42,5.11, 16.62,10.52 }; |
| | | // worse than ours (even for 19x19 final size - for input size 608x608) |
| | | |
| | | //orig anchors = 1.3221,1.73145, 3.19275,4.00944, 5.05587,8.09892, 9.47112,4.84053, 11.2364,10.0071 |
| | | //float orig_anch[] = { 1.3221,1.73145, 3.19275,4.00944, 5.05587,8.09892, 9.47112,4.84053, 11.2364,10.0071 }; |
| | | // orig (IoU=59.90%) better than ours (59.75%) |
| | | |
| | | //gen_anchors.py = 1.19, 1.99, 2.79, 4.60, 4.53, 8.92, 8.06, 5.29, 10.32, 10.66 |
| | | //float orig_anch[] = { 1.19, 1.99, 2.79, 4.60, 4.53, 8.92, 8.06, 5.29, 10.32, 10.66 }; |
| | | |
| | | // ours: anchors = 9.3813,6.0095, 3.3999,5.3505, 10.9476,11.1992, 5.0161,9.8314, 1.5003,2.1595 |
| | | //float orig_anch[] = { 9.3813,6.0095, 3.3999,5.3505, 10.9476,11.1992, 5.0161,9.8314, 1.5003,2.1595 }; |
| | | //for (i = 0; i < num_of_clusters * 2; ++i) centers->data.fl[i] = orig_anch[i]; |
| | | |
| | | //for (i = 0; i < number_of_boxes; ++i) |
| | | // printf("%2.2f,%2.2f, ", points->data.fl[i * 2], points->data.fl[i * 2 + 1]); |
| | | |
| | | float avg_iou = 0; |
| | | for (i = 0; i < number_of_boxes; ++i) { |
| | | float box_w = points->data.fl[i * 2]; |
| | | float box_h = points->data.fl[i * 2 + 1]; |
| | | //int cluster_idx = labels->data.i[i]; |
| | | int cluster_idx = 0; |
| | | float min_dist = 1000000; |
| | | for (j = 0; j < num_of_clusters; ++j) { |
| | | float anchor_w = centers->data.fl[j * 2]; |
| | | float anchor_h = centers->data.fl[j * 2 + 1]; |
| | | float w_diff = anchor_w - box_w; |
| | | float h_diff = anchor_h - box_h; |
| | | float distance = sqrt(w_diff*w_diff + h_diff*h_diff); |
| | | if (distance < min_dist) min_dist = distance, cluster_idx = j; |
| | | } |
| | | |
| | | float anchor_w = centers->data.fl[cluster_idx * 2]; |
| | | float anchor_h = centers->data.fl[cluster_idx * 2 + 1]; |
| | | float min_w = (box_w < anchor_w) ? box_w : anchor_w; |
| | | float min_h = (box_h < anchor_h) ? box_h : anchor_h; |
| | | float box_intersect = min_w*min_h; |
| | | float box_union = box_w*box_h + anchor_w*anchor_h - box_intersect; |
| | | float iou = box_intersect / box_union; |
| | | if (iou > 1 || iou < 0) { |
| | | printf(" i = %d, box_w = %d, box_h = %d, anchor_w = %d, anchor_h = %d, iou = %f \n", |
| | | i, box_w, box_h, anchor_w, anchor_h, iou); |
| | | } |
| | | else avg_iou += iou; |
| | | } |
| | | avg_iou = 100 * avg_iou / number_of_boxes; |
| | | printf("\n avg IoU = %2.2f %% \n", avg_iou); |
| | | |
| | | char buff[1024]; |
| | | FILE* fw = fopen("anchors.txt", "wb"); |
| | | printf("\nSaving anchors to the file: anchors.txt \n"); |
| | | printf("anchors = "); |
| | | for (i = 0; i < num_of_clusters; ++i) { |
| | | sprintf(buff, "%2.4f,%2.4f", centers->data.fl[i * 2], centers->data.fl[i * 2 + 1]); |
| | | printf("%s, ", buff); |
| | | fwrite(buff, sizeof(char), strlen(buff), fw); |
| | | if (i + 1 < num_of_clusters) fwrite(", ", sizeof(char), 2, fw);; |
| | | } |
| | | printf("\n"); |
| | | fclose(fw); |
| | | |
| | | if (show) { |
| | | size_t img_size = 700; |
| | | IplImage* img = cvCreateImage(cvSize(img_size, img_size), 8, 3); |
| | | cvZero(img); |
| | | for (j = 0; j < num_of_clusters; ++j) { |
| | | CvPoint pt1, pt2; |
| | | pt1.x = pt1.y = 0; |
| | | pt2.x = centers->data.fl[j * 2] * img_size / final_width; |
| | | pt2.y = centers->data.fl[j * 2 + 1] * img_size / final_height; |
| | | cvRectangle(img, pt1, pt2, CV_RGB(255, 255, 255), 1, 8, 0); |
| | | } |
| | | |
| | | for (i = 0; i < number_of_boxes; ++i) { |
| | | CvPoint pt; |
| | | pt.x = points->data.fl[i * 2] * img_size / final_width; |
| | | pt.y = points->data.fl[i * 2 + 1] * img_size / final_height; |
| | | int cluster_idx = labels->data.i[i]; |
| | | int red_id = (cluster_idx * (uint64_t)123 + 55) % 255; |
| | | int green_id = (cluster_idx * (uint64_t)321 + 33) % 255; |
| | | int blue_id = (cluster_idx * (uint64_t)11 + 99) % 255; |
| | | cvCircle(img, pt, 1, CV_RGB(red_id, green_id, blue_id), CV_FILLED, 8, 0); |
| | | //if(pt.x > img_size || pt.y > img_size) printf("\n pt.x = %d, pt.y = %d \n", pt.x, pt.y); |
| | | } |
| | | cvShowImage("clusters", img); |
| | | cvWaitKey(0); |
| | | cvReleaseImage(&img); |
| | | cvDestroyAllWindows(); |
| | | } |
| | | |
| | | free(rel_width_height_array); |
| | | cvReleaseMat(&points); |
| | | cvReleaseMat(¢ers); |
| | |
| | | void run_detector(int argc, char **argv) |
| | | { |
| | | int dont_show = find_arg(argc, argv, "-dont_show"); |
| | | int show = find_arg(argc, argv, "-show"); |
| | | int http_stream_port = find_int_arg(argc, argv, "-http_port", -1); |
| | | char *out_filename = find_char_arg(argc, argv, "-out_filename", 0); |
| | | char *prefix = find_char_arg(argc, argv, "-prefix", 0); |
| | |
| | | else if(0==strcmp(argv[2], "valid")) validate_detector(datacfg, cfg, weights); |
| | | else if(0==strcmp(argv[2], "recall")) validate_detector_recall(datacfg, cfg, weights); |
| | | else if(0==strcmp(argv[2], "map")) validate_detector_map(datacfg, cfg, weights, thresh); |
| | | else if(0==strcmp(argv[2], "calc_anchors")) calc_anchors(datacfg, num_of_clusters, final_width, final_heigh); |
| | | else if(0==strcmp(argv[2], "calc_anchors")) calc_anchors(datacfg, num_of_clusters, final_width, final_heigh, show); |
| | | else if(0==strcmp(argv[2], "demo")) { |
| | | list *options = read_data_cfg(datacfg); |
| | | int classes = option_find_int(options, "classes", 20); |