tag.c
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00001 #include "network.h"
00002 #include "utils.h"
00003 #include "parser.h"
00004 
00005 #ifdef OPENCV
00006 #include "opencv2/highgui/highgui_c.h"
00007 #endif
00008 
00009 void train_tag(char *cfgfile, char *weightfile, int clear)
00010 {
00011     srand(time(0));
00012     float avg_loss = -1;
00013     char *base = basecfg(cfgfile);
00014     char *backup_directory = "/home/pjreddie/backup/";
00015     printf("%s\n", base);
00016     network net = parse_network_cfg(cfgfile);
00017     if(weightfile){
00018         load_weights(&net, weightfile);
00019     }
00020     if(clear) *net.seen = 0;
00021     printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
00022     int imgs = 1024;
00023     list *plist = get_paths("/home/pjreddie/tag/train.list");
00024     char **paths = (char **)list_to_array(plist);
00025     printf("%d\n", plist->size);
00026     int N = plist->size;
00027     clock_t time;
00028     pthread_t load_thread;
00029     data train;
00030     data buffer;
00031 
00032     load_args args = {0};
00033     args.w = net.w;
00034     args.h = net.h;
00035 
00036     args.min = net.w;
00037     args.max = net.max_crop;
00038     args.size = net.w;
00039 
00040     args.paths = paths;
00041     args.classes = net.outputs;
00042     args.n = imgs;
00043     args.m = N;
00044     args.d = &buffer;
00045     args.type = TAG_DATA;
00046 
00047     args.angle = net.angle;
00048     args.exposure = net.exposure;
00049     args.saturation = net.saturation;
00050     args.hue = net.hue;
00051 
00052     fprintf(stderr, "%d classes\n", net.outputs);
00053 
00054     load_thread = load_data_in_thread(args);
00055     int epoch = (*net.seen)/N;
00056     while(get_current_batch(net) < net.max_batches || net.max_batches == 0){
00057         time=clock();
00058         pthread_join(load_thread, 0);
00059         train = buffer;
00060 
00061         load_thread = load_data_in_thread(args);
00062         printf("Loaded: %lf seconds\n", sec(clock()-time));
00063         time=clock();
00064         float loss = train_network(net, train);
00065         if(avg_loss == -1) avg_loss = loss;
00066         avg_loss = avg_loss*.9 + loss*.1;
00067         printf("%d, %.3f: %f, %f avg, %f rate, %lf seconds, %d images\n", get_current_batch(net), (float)(*net.seen)/N, loss, avg_loss, get_current_rate(net), sec(clock()-time), *net.seen);
00068         free_data(train);
00069         if(*net.seen/N > epoch){
00070             epoch = *net.seen/N;
00071             char buff[256];
00072             sprintf(buff, "%s/%s_%d.weights",backup_directory,base, epoch);
00073             save_weights(net, buff);
00074         }
00075         if(get_current_batch(net)%100 == 0){
00076             char buff[256];
00077             sprintf(buff, "%s/%s.backup",backup_directory,base);
00078             save_weights(net, buff);
00079         }
00080     }
00081     char buff[256];
00082     sprintf(buff, "%s/%s.weights", backup_directory, base);
00083     save_weights(net, buff);
00084 
00085     pthread_join(load_thread, 0);
00086     free_data(buffer);
00087     free_network(net);
00088     free_ptrs((void**)paths, plist->size);
00089     free_list(plist);
00090     free(base);
00091 }
00092 
00093 void test_tag(char *cfgfile, char *weightfile, char *filename)
00094 {
00095     network net = parse_network_cfg(cfgfile);
00096     if(weightfile){
00097         load_weights(&net, weightfile);
00098     }
00099     set_batch_network(&net, 1);
00100     srand(2222222);
00101     int i = 0;
00102     char **names = get_labels("data/tags.txt");
00103     clock_t time;
00104     int indexes[10];
00105     char buff[256];
00106     char *input = buff;
00107     int size = net.w;
00108     while(1){
00109         if(filename){
00110             strncpy(input, filename, 256);
00111         }else{
00112             printf("Enter Image Path: ");
00113             fflush(stdout);
00114             input = fgets(input, 256, stdin);
00115             if(!input) return;
00116             strtok(input, "\n");
00117         }
00118         image im = load_image_color(input, 0, 0);
00119         image r = resize_min(im, size);
00120         resize_network(&net, r.w, r.h);
00121         printf("%d %d\n", r.w, r.h);
00122 
00123         float *X = r.data;
00124         time=clock();
00125         float *predictions = network_predict(net, X);
00126         top_predictions(net, 10, indexes);
00127         printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
00128         for(i = 0; i < 10; ++i){
00129             int index = indexes[i];
00130             printf("%.1f%%: %s\n", predictions[index]*100, names[index]);
00131         }
00132         if(r.data != im.data) free_image(r);
00133         free_image(im);
00134         if (filename) break;
00135     }
00136 }
00137 
00138 
00139 void run_tag(int argc, char **argv)
00140 {
00141     if(argc < 4){
00142         fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]);
00143         return;
00144     }
00145 
00146     int clear = find_arg(argc, argv, "-clear");
00147     char *cfg = argv[3];
00148     char *weights = (argc > 4) ? argv[4] : 0;
00149     char *filename = (argc > 5) ? argv[5] : 0;
00150     if(0==strcmp(argv[2], "train")) train_tag(cfg, weights, clear);
00151     else if(0==strcmp(argv[2], "test")) test_tag(cfg, weights, filename);
00152 }
00153 


rail_object_detector
Author(s):
autogenerated on Sat Jun 8 2019 20:26:31