| | |
| | | |
| | | void train_classifier(char *datacfg, char *cfgfile, char *weightfile, int clear) |
| | | { |
| | | int nthreads = 2; |
| | | int nthreads = 8; |
| | | int i; |
| | | |
| | | data_seed = time(0); |
| | |
| | | |
| | | args.min = net.min_crop; |
| | | args.max = net.max_crop; |
| | | args.angle = net.angle; |
| | | args.exposure = net.exposure; |
| | | args.saturation = net.saturation; |
| | | args.size = net.w; |
| | | |
| | | args.paths = paths; |
| | |
| | | printf("Loaded: %lf seconds\n", sec(clock()-time)); |
| | | time=clock(); |
| | | |
| | | /* |
| | | if(0){ |
| | | int u; |
| | | for(u = 0; u < net.batch; ++u){ |
| | | for(u = 0; u < imgs; ++u){ |
| | | image im = float_to_image(net.w, net.h, 3, train.X.vals[u]); |
| | | show_image(im, "loaded"); |
| | | cvWaitKey(0); |
| | | } |
| | | */ |
| | | } |
| | | |
| | | float loss = train_network(net, train); |
| | | if(avg_loss == -1) avg_loss = loss; |