| | |
| | | int imgs = 1000/net.batch+1; |
| | | srand(time(0)); |
| | | int i = 0; |
| | | char **labels = get_labels("/home/pjreddie/data/imagenet/cls.labels.list"); |
| | | list *plist = get_paths("/data/imagenet/cls.train.list"); |
| | | list *plist = get_paths("/home/pjreddie/data/imagenet/horse.txt"); |
| | | char **paths = (char **)list_to_array(plist); |
| | | printf("%d\n", plist->size); |
| | | clock_t time; |
| | | while(1){ |
| | | i += 1; |
| | | time=clock(); |
| | | data train = load_data_random(imgs*net.batch, paths, plist->size, labels, 1000, 256, 256); |
| | | data train = load_data_detection_random(imgs*net.batch, paths, plist->size, 256, 256, 8, 8, 256); |
| | | //translate_data_rows(train, -144); |
| | | normalize_data_rows(train); |
| | | printf("Loaded: %lf seconds\n", sec(clock()-time)); |
| | |
| | | { |
| | | float avg_loss = 1; |
| | | //network net = parse_network_cfg("/home/pjreddie/imagenet_backup/alexnet_1270.cfg"); |
| | | network net = parse_network_cfg("cfg/alexnet.cfg"); |
| | | network net = parse_network_cfg("cfg/trained_alexnet.cfg"); |
| | | printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay); |
| | | int imgs = 1000/net.batch+1; |
| | | srand(time(0)); |
| | |
| | | } |
| | | } |
| | | |
| | | void test_detection() |
| | | { |
| | | network net = parse_network_cfg("cfg/detnet_test.cfg"); |
| | | //imgs=1; |
| | | srand(2222222); |
| | | int i = 0; |
| | | clock_t time; |
| | | char filename[256]; |
| | | int indexes[10]; |
| | | while(1){ |
| | | fgets(filename, 256, stdin); |
| | | image im = load_image_color(filename, 256, 256); |
| | | z_normalize_image(im); |
| | | printf("%d %d %d\n", im.h, im.w, im.c); |
| | | float *X = im.data; |
| | | time=clock(); |
| | | float *predictions = network_predict(net, X); |
| | | top_predictions(net, 10, indexes); |
| | | printf("%s: Predicted in %f seconds.\n", filename, sec(clock()-time)); |
| | | free_image(im); |
| | | } |
| | | } |
| | | |
| | | void test_imagenet() |
| | | { |
| | | network net = parse_network_cfg("cfg/imagenet_test.cfg"); |
| | |
| | | return 0; |
| | | } |
| | | if(0==strcmp(argv[1], "train")) train_imagenet(); |
| | | else if(0==strcmp(argv[1], "detection")) train_detection_net(); |
| | | else if(0==strcmp(argv[1], "asirra")) train_asirra(); |
| | | else if(0==strcmp(argv[1], "nist")) train_nist(); |
| | | else if(0==strcmp(argv[1], "test_correct")) test_gpu_net(); |
| | |
| | | #ifdef GPU |
| | | else if(0==strcmp(argv[1], "test_gpu")) test_gpu_blas(); |
| | | #endif |
| | | test_parser(); |
| | | fprintf(stderr, "Success!\n"); |
| | | return 0; |
| | | } |