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| | | #ifdef _DEBUG |
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| | | #include <stdlib.h> |
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| | | #include <crtdbg.h> |
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| | | #endif |
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| | | |
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| | | #include "network.h" |
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| | | #include "region_layer.h" |
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| | | #include "cost_layer.h" |
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| | |
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| | | truth_dif = read_boxes(labelpath_dif, &num_labels_dif); |
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| | | } |
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| | | |
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| | | const int checkpoint_detections_count = detections_count; |
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| | | |
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| | | for (i = 0; i < nboxes; ++i) { |
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| | | |
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| | | int class_id; |
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| | |
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| | | |
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| | | // calc avg IoU, true-positives, false-positives for required Threshold |
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| | | if (prob > thresh_calc_avg_iou) { |
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| | | if (truth_index > -1) { |
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| | | int z, found = 0; |
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| | | for (z = checkpoint_detections_count; z < detections_count-1; ++z) |
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| | | if (detections[z].unique_truth_index == truth_index) { |
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| | | found = 1; break; |
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| | | } |
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| | | |
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| | | if(truth_index > -1 && found == 0) { |
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| | | avg_iou += max_iou; |
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| | | ++tp_for_thresh; |
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| | | } |
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| | |
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| | | } |
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| | | } |
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| | | |
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| | | avg_iou = avg_iou / (tp_for_thresh + fp_for_thresh); |
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| | | if((tp_for_thresh + fp_for_thresh) > 0) |
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| | | avg_iou = avg_iou / (tp_for_thresh + fp_for_thresh); |
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| | | |
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| | | |
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| | | // SORT(detections) |
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| | |
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| | | while(1){ |
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| | | if(filename){ |
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| | | strncpy(input, filename, 256); |
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| | | if (input[strlen(input) - 1] == 0x0d) input[strlen(input) - 1] = 0; |
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| | | if(strlen(input) > 0) |
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| | | if (input[strlen(input) - 1] == 0x0d) input[strlen(input) - 1] = 0; |
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| | | } else { |
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| | | printf("Enter Image Path: "); |
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| | | fflush(stdout); |
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| | |
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| | | } |
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| | | image im = load_image_color(input,0,0); |
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| | | int letterbox = 0; |
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| | | image sized = resize_image(im, net.w, net.h); |
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| | | //image sized = letterbox_image(im, net.w, net.h); letterbox = 1; |
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| | | //image sized = resize_image(im, net.w, net.h); |
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| | | image sized = letterbox_image(im, net.w, net.h); letterbox = 1; |
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| | | layer l = net.layers[net.n-1]; |
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| | | |
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| | | //box *boxes = calloc(l.w*l.h*l.n, sizeof(box)); |
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| | |
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| | | |
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| | | float *X = sized.data; |
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| | | time= what_time_is_it_now(); |
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| | | //network_predict(net, X); |
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| | | network_predict_image(&net, im); letterbox = 1; |
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| | | network_predict(net, X); |
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| | | //network_predict_image(&net, im); letterbox = 1; |
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| | | printf("%s: Predicted in %f seconds.\n", input, (what_time_is_it_now()-time)); |
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| | | //get_region_boxes(l, 1, 1, thresh, probs, boxes, 0, 0); |
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| | | // if (nms) do_nms_sort_v2(boxes, probs, l.w*l.h*l.n, l.classes, nms); |
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| | |
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| | | #endif |
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| | | if (filename) break; |
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| | | } |
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| | | |
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| | | // free memory |
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| | | free_ptrs(names, net.layers[net.n - 1].classes); |
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| | | free_list(options); |
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| | | |
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| | | int i; |
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| | | const int nsize = 8; |
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| | | for (j = 0; j < nsize; ++j) { |
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| | | for (i = 32; i < 127; ++i) { |
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| | | free_image(alphabet[j][i]); |
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| | | } |
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| | | free(alphabet[j]); |
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| | | } |
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| | | free(alphabet); |
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| | | |
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| | | free_network(net); |
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| | | } |
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| | | |
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| | | void run_detector(int argc, char **argv) |
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| | |
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| | | char *cfg = argv[4]; |
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| | | char *weights = (argc > 5) ? argv[5] : 0; |
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| | | if(weights) |
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| | | if (weights[strlen(weights) - 1] == 0x0d) weights[strlen(weights) - 1] = 0; |
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| | | if(strlen(weights) > 0) |
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| | | if (weights[strlen(weights) - 1] == 0x0d) weights[strlen(weights) - 1] = 0; |
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| | | char *filename = (argc > 6) ? argv[6]: 0; |
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| | | if(0==strcmp(argv[2], "test")) test_detector(datacfg, cfg, weights, filename, thresh, hier_thresh, dont_show); |
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| | | else if(0==strcmp(argv[2], "train")) train_detector(datacfg, cfg, weights, gpus, ngpus, clear, dont_show); |
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| | |
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| | | char *name_list = option_find_str(options, "names", "data/names.list"); |
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| | | char **names = get_labels(name_list); |
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| | | if(filename) |
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| | | if (filename[strlen(filename) - 1] == 0x0d) filename[strlen(filename) - 1] = 0; |
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| | | if(strlen(filename) > 0) |
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| | | if (filename[strlen(filename) - 1] == 0x0d) filename[strlen(filename) - 1] = 0; |
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| | | demo(cfg, weights, thresh, hier_thresh, cam_index, filename, names, classes, frame_skip, prefix, out_filename, |
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| | | http_stream_port, dont_show); |
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| | | } |
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