| | |
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| | | #pragma comment(lib, "opencv_highgui" OPENCV_VERSION ".lib") |
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| | | #endif |
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| | | |
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| | | #endif |
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| | | IplImage* draw_train_chart(float max_img_loss, int max_batches, int number_of_lines, int img_size); |
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| | | void draw_train_loss(IplImage* img, int img_size, float avg_loss, float max_img_loss, int current_batch, int max_batches); |
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| | | #endif // OPENCV |
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| | | |
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| | | static int coco_ids[] = {1,2,3,4,5,6,7,8,9,10,11,13,14,15,16,17,18,19,20,21,22,23,24,25,27,28,31,32,33,34,35,36,37,38,39,40,41,42,43,44,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,67,70,72,73,74,75,76,77,78,79,80,81,82,84,85,86,87,88,89,90}; |
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| | | |
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| | | void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, int ngpus, int clear) |
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| | | void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, int ngpus, int clear, int dont_show) |
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| | | { |
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| | | list *options = read_data_cfg(datacfg); |
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| | | char *train_images = option_find_str(options, "train", "data/train.list"); |
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| | |
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| | | args.saturation = net.saturation; |
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| | | args.hue = net.hue; |
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| | | |
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| | | #ifdef OPENCV |
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| | | IplImage* img = NULL; |
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| | | float max_img_loss = 5; |
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| | | int number_of_lines = 100; |
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| | | int img_size = 1000; |
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| | | if (!dont_show) |
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| | | img = draw_train_chart(max_img_loss, net.max_batches, number_of_lines, img_size); |
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| | | #endif //OPENCV |
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| | | |
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| | | pthread_t load_thread = load_data(args); |
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| | | clock_t time; |
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| | | int count = 0; |
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| | |
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| | | |
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| | | i = get_current_batch(net); |
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| | | printf("%d: %f, %f avg, %f rate, %lf seconds, %d images\n", get_current_batch(net), loss, avg_loss, get_current_rate(net), sec(clock()-time), i*imgs); |
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| | | |
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| | | #ifdef OPENCV |
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| | | if(!dont_show) |
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| | | draw_train_loss(img, img_size, avg_loss, max_img_loss, i, net.max_batches); |
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| | | #endif // OPENCV |
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| | | |
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| | | //if (i % 1000 == 0 || (i < 1000 && i % 100 == 0)) { |
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| | | if (i % 100 == 0) { |
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| | | #ifdef GPU |
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| | |
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| | | char buff[256]; |
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| | | sprintf(buff, "%s/%s_final.weights", backup_directory, base); |
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| | | save_weights(net, buff); |
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| | | |
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| | | //cvReleaseImage(&img); |
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| | | //cvDestroyAllWindows(); |
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| | | } |
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| | | |
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| | | |
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| | |
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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, dont_show); |
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| | | else if(0==strcmp(argv[2], "train")) train_detector(datacfg, cfg, weights, gpus, ngpus, clear); |
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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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| | | else if(0==strcmp(argv[2], "valid")) validate_detector(datacfg, cfg, weights); |
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| | | else if(0==strcmp(argv[2], "recall")) validate_detector_recall(datacfg, cfg, weights); |
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| | | else if(0==strcmp(argv[2], "map")) validate_detector_map(datacfg, cfg, weights, thresh); |
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| | | else if(0==strcmp(argv[2], "calc_anchors")) calc_anchors(datacfg, num_of_clusters, final_width, final_heigh, show); |
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| | | else if(0==strcmp(argv[2], "calc_anchors")) calc_anchors(datacfg, num_of_clusters, final_width, final_heigh, show); |
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| | | else if(0==strcmp(argv[2], "demo")) { |
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| | | list *options = read_data_cfg(datacfg); |
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| | | int classes = option_find_int(options, "classes", 20); |
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