| 3 | #include <assert.h> |
| 4 | |
| 5 | void train_segmenter(char *datacfg, char *cfgfile, char *weightfile, int *gpus, int ngpus, int clear, int display) |
| 6 | { |
| 7 | int i; |
| 8 | |
| 9 | float avg_loss = -1; |
| 10 | char *base = basecfg(cfgfile); |
| 11 | printf("%s\n", base); |
| 12 | printf("%d\n", ngpus); |
| 13 | network **nets = calloc(ngpus, sizeof(network*)); |
| 14 | |
| 15 | srand(time(0)); |
| 16 | int seed = rand(); |
| 17 | for(i = 0; i < ngpus; ++i){ |
| 18 | srand(seed); |
| 19 | #ifdef GPU |
| 20 | cuda_set_device(gpus[i]); |
| 21 | #endif |
| 22 | nets[i] = load_network(cfgfile, weightfile, clear); |
| 23 | nets[i]->learning_rate *= ngpus; |
| 24 | } |
| 25 | srand(time(0)); |
| 26 | network *net = nets[0]; |
| 27 | image pred = get_network_image(net); |
| 28 | |
| 29 | int div = net->w/pred.w; |
| 30 | assert(pred.w * div == net->w); |
| 31 | assert(pred.h * div == net->h); |
| 32 | |
| 33 | int imgs = net->batch * net->subdivisions * ngpus; |
| 34 | |
| 35 | printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net->learning_rate, net->momentum, net->decay); |
| 36 | list *options = read_data_cfg(datacfg); |
| 37 | |
| 38 | char *backup_directory = option_find_str(options, "backup", "/backup/"); |
| 39 | char *train_list = option_find_str(options, "train", "data/train.list"); |
| 40 | |
| 41 | list *plist = get_paths(train_list); |
| 42 | char **paths = (char **)list_to_array(plist); |
| 43 | printf("%d\n", plist->size); |
| 44 | int N = plist->size; |
| 45 | clock_t time; |
| 46 | |
| 47 | load_args args = {0}; |
| 48 | args.w = net->w; |
| 49 | args.h = net->h; |
| 50 | args.threads = 32; |
| 51 | args.scale = div; |
| 52 | |
| 53 | args.min = net->min_crop; |
| 54 | args.max = net->max_crop; |
| 55 | args.angle = net->angle; |
| 56 | args.aspect = net->aspect; |
| 57 | args.exposure = net->exposure; |
| 58 | args.saturation = net->saturation; |
| 59 | args.hue = net->hue; |
| 60 | args.size = net->w; |
| 61 | args.classes = 80; |
| 62 |
no test coverage detected