| | |
| | | while(1){ |
| | | i += 1; |
| | | time=clock(); |
| | | data train = load_data_random(imgs*net.batch, paths, m, labels, 2, 256, 256); |
| | | data train = load_data(paths, imgs*net.batch, m, labels, 2, 256, 256); |
| | | normalize_data_rows(train); |
| | | printf("Loaded: %lf seconds\n", sec(clock()-time)); |
| | | time=clock(); |
| | |
| | | printf("%d\n", plist->size); |
| | | clock_t time; |
| | | data train, buffer; |
| | | pthread_t load_thread = load_data_random_thread(imgs*net.batch, paths, plist->size, labels, 1000, 224, 224, &buffer); |
| | | pthread_t load_thread = load_data_thread(paths, imgs*net.batch, plist->size, labels, 1000, 224, 224, &buffer); |
| | | while(1){ |
| | | i += 1; |
| | | |
| | |
| | | pthread_join(load_thread, 0); |
| | | train = buffer; |
| | | normalize_data_rows(train); |
| | | load_thread = load_data_random_thread(imgs*net.batch, paths, plist->size, labels, 1000, 224, 224, &buffer); |
| | | load_thread = load_data_thread(paths, imgs*net.batch, plist->size, labels, 1000, 224, 224, &buffer); |
| | | printf("Loaded: %lf seconds\n", sec(clock()-time)); |
| | | time=clock(); |
| | | |
| | |
| | | float avg_loss = 1; |
| | | //network net = parse_network_cfg("/home/pjreddie/imagenet_backup/alexnet_1270.cfg"); |
| | | srand(time(0)); |
| | | network net = parse_network_cfg("cfg/net.cfg"); |
| | | network net = parse_network_cfg("cfg/net.part"); |
| | | printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay); |
| | | int imgs = 1000/net.batch+1; |
| | | //imgs=1; |
| | | int i = 0; |
| | | int i = 9540; |
| | | char **labels = get_labels("/home/pjreddie/data/imagenet/cls.labels.list"); |
| | | list *plist = get_paths("/data/imagenet/cls.train.list"); |
| | | char **paths = (char **)list_to_array(plist); |
| | |
| | | pthread_t load_thread; |
| | | data train; |
| | | data buffer; |
| | | load_thread = load_data_random_thread(imgs*net.batch, paths, plist->size, labels, 1000, 224, 224, &buffer); |
| | | load_thread = load_data_thread(paths, imgs*net.batch, plist->size, labels, 1000, 224, 224, &buffer); |
| | | while(1){ |
| | | i += 1; |
| | | time=clock(); |
| | | pthread_join(load_thread, 0); |
| | | train = buffer; |
| | | normalize_data_rows(train); |
| | | load_thread = load_data_random_thread(imgs*net.batch, paths, plist->size, labels, 1000, 224, 224, &buffer); |
| | | load_thread = load_data_thread(paths, imgs*net.batch, plist->size, labels, 1000, 224, 224, &buffer); |
| | | printf("Loaded: %lf seconds\n", sec(clock()-time)); |
| | | time=clock(); |
| | | #ifdef GPU |
| | |
| | | free_data(train); |
| | | if(i%10==0){ |
| | | char buff[256]; |
| | | sprintf(buff, "/home/pjreddie/imagenet_backup/alexnet_%d.cfg", i); |
| | | sprintf(buff, "/home/pjreddie/imagenet_backup/net_%d.cfg", i); |
| | | save_network(net, buff); |
| | | } |
| | | } |
| | |
| | | |
| | | void validate_imagenet(char *filename) |
| | | { |
| | | int i; |
| | | int i = 0; |
| | | network net = parse_network_cfg(filename); |
| | | srand(time(0)); |
| | | |
| | |
| | | float avg_acc = 0; |
| | | float avg_top5 = 0; |
| | | int splits = 50; |
| | | |
| | | for(i = 0; i < splits; ++i){ |
| | | time=clock(); |
| | | char **part = paths+(i*m/splits); |
| | | int num = (i+1)*m/splits - i*m/splits; |
| | | data val = load_data(part, num, labels, 1000, 224, 224); |
| | | |
| | | data val, buffer; |
| | | pthread_t load_thread = load_data_thread(paths, num, 0, labels, 1000, 224, 224, &buffer); |
| | | for(i = 1; i <= splits; ++i){ |
| | | time=clock(); |
| | | |
| | | pthread_join(load_thread, 0); |
| | | val = buffer; |
| | | normalize_data_rows(val); |
| | | |
| | | num = (i+1)*m/splits - i*m/splits; |
| | | char **part = paths+(i*m/splits); |
| | | if(i != splits) load_thread = load_data_thread(part, num, 0, labels, 1000, 224, 224, &buffer); |
| | | printf("Loaded: %d images in %lf seconds\n", val.X.rows, sec(clock()-time)); |
| | | |
| | | time=clock(); |
| | | #ifdef GPU |
| | | float *acc = network_accuracies_gpu(net, val); |
| | | avg_acc += acc[0]; |
| | | avg_top5 += acc[1]; |
| | | printf("%d: top1: %f, top5: %f, %lf seconds, %d images\n", i, avg_acc/(i+1), avg_top5/(i+1), sec(clock()-time), val.X.rows); |
| | | printf("%d: top1: %f, top5: %f, %lf seconds, %d images\n", i, avg_acc/i, avg_top5/i, sec(clock()-time), val.X.rows); |
| | | #endif |
| | | free_data(val); |
| | | } |
| | |
| | | int count = 0; |
| | | |
| | | srand(222222); |
| | | network net = parse_network_cfg("cfg/alexnet.test"); |
| | | network net = parse_network_cfg("cfg/net.cfg"); |
| | | printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay); |
| | | int imgs = 1000/net.batch+1; |
| | | imgs = 1; |
| | | |
| | | while(++count <= 5){ |
| | | time=clock(); |
| | | data train = load_data_random(imgs*net.batch, paths, plist->size, labels, 1000, 256, 256); |
| | | data train = load_data(paths, imgs*net.batch, plist->size, labels, 1000, 224,224); |
| | | //translate_data_rows(train, -144); |
| | | normalize_data_rows(train); |
| | | printf("Loaded: %lf seconds\n", sec(clock()-time)); |
| | |
| | | #ifdef GPU |
| | | count = 0; |
| | | srand(222222); |
| | | net = parse_network_cfg("cfg/alexnet.test"); |
| | | net = parse_network_cfg("cfg/net.cfg"); |
| | | while(++count <= 5){ |
| | | time=clock(); |
| | | data train = load_data_random(imgs*net.batch, paths, plist->size, labels, 1000, 256, 256); |
| | | data train = load_data(paths, imgs*net.batch, plist->size, labels, 1000, 224, 224); |
| | | //translate_data_rows(train, -144); |
| | | normalize_data_rows(train); |
| | | printf("Loaded: %lf seconds\n", sec(clock()-time)); |