| | |
| | | #ifdef _DEBUG |
| | | #include <stdlib.h> |
| | | #include <crtdbg.h> |
| | | #endif |
| | | |
| | | #include "network.h" |
| | | #include "region_layer.h" |
| | | #include "cost_layer.h" |
| | |
| | | truth_dif = read_boxes(labelpath_dif, &num_labels_dif); |
| | | } |
| | | |
| | | const int checkpoint_detections_count = detections_count; |
| | | |
| | | for (i = 0; i < nboxes; ++i) { |
| | | |
| | | int class_id; |
| | |
| | | |
| | | // calc avg IoU, true-positives, false-positives for required Threshold |
| | | if (prob > thresh_calc_avg_iou) { |
| | | if (truth_index > -1) { |
| | | int z, found = 0; |
| | | for (z = checkpoint_detections_count; z < detections_count-1; ++z) |
| | | if (detections[z].unique_truth_index == truth_index) { |
| | | found = 1; break; |
| | | } |
| | | |
| | | if(truth_index > -1 && found == 0) { |
| | | avg_iou += max_iou; |
| | | ++tp_for_thresh; |
| | | } |
| | |
| | | } |
| | | } |
| | | |
| | | avg_iou = avg_iou / (tp_for_thresh + fp_for_thresh); |
| | | if((tp_for_thresh + fp_for_thresh) > 0) |
| | | avg_iou = avg_iou / (tp_for_thresh + fp_for_thresh); |
| | | |
| | | |
| | | // SORT(detections) |
| | |
| | | } |
| | | image im = load_image_color(input,0,0); |
| | | int letterbox = 0; |
| | | image sized = resize_image(im, net.w, net.h); |
| | | //image sized = letterbox_image(im, net.w, net.h); letterbox = 1; |
| | | //image sized = resize_image(im, net.w, net.h); |
| | | image sized = letterbox_image(im, net.w, net.h); letterbox = 1; |
| | | layer l = net.layers[net.n-1]; |
| | | |
| | | //box *boxes = calloc(l.w*l.h*l.n, sizeof(box)); |
| | |
| | | |
| | | float *X = sized.data; |
| | | time= what_time_is_it_now(); |
| | | //network_predict(net, X); |
| | | network_predict_image(&net, im); letterbox = 1; |
| | | network_predict(net, X); |
| | | //network_predict_image(&net, im); letterbox = 1; |
| | | printf("%s: Predicted in %f seconds.\n", input, (what_time_is_it_now()-time)); |
| | | //get_region_boxes(l, 1, 1, thresh, probs, boxes, 0, 0); |
| | | // if (nms) do_nms_sort_v2(boxes, probs, l.w*l.h*l.n, l.classes, nms); |
| | |
| | | #endif |
| | | if (filename) break; |
| | | } |
| | | |
| | | // free memory |
| | | free_ptrs(names, net.layers[net.n - 1].classes); |
| | | free_list(options); |
| | | |
| | | int i; |
| | | const int nsize = 8; |
| | | for (j = 0; j < nsize; ++j) { |
| | | for (i = 32; i < 127; ++i) { |
| | | free_image(alphabet[j][i]); |
| | | } |
| | | free(alphabet[j]); |
| | | } |
| | | free(alphabet); |
| | | |
| | | free_network(net); |
| | | } |
| | | |
| | | void run_detector(int argc, char **argv) |