mirror of https://github.com/pjreddie/darknet.git
117 lines
3.5 KiB
C
117 lines
3.5 KiB
C
#include "darknet.h"
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char *dice_labels[] = {"face1","face2","face3","face4","face5","face6"};
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void train_dice(char *cfgfile, char *weightfile)
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{
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srand(time(0));
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float avg_loss = -1;
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char *base = basecfg(cfgfile);
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char *backup_directory = "/home/pjreddie/backup/";
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printf("%s\n", base);
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network net = parse_network_cfg(cfgfile);
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if(weightfile){
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load_weights(&net, weightfile);
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}
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printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
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int imgs = 1024;
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int i = *net.seen/imgs;
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char **labels = dice_labels;
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list *plist = get_paths("data/dice/dice.train.list");
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char **paths = (char **)list_to_array(plist);
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printf("%d\n", plist->size);
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clock_t time;
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while(1){
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++i;
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time=clock();
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data train = load_data_old(paths, imgs, plist->size, labels, 6, net.w, net.h);
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printf("Loaded: %lf seconds\n", sec(clock()-time));
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time=clock();
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float loss = train_network(net, train);
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if(avg_loss == -1) avg_loss = loss;
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avg_loss = avg_loss*.9 + loss*.1;
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printf("%d: %f, %f avg, %lf seconds, %ld images\n", i, loss, avg_loss, sec(clock()-time), *net.seen);
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free_data(train);
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if((i % 100) == 0) net.learning_rate *= .1;
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if(i%100==0){
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char buff[256];
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sprintf(buff, "%s/%s_%d.weights",backup_directory,base, i);
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save_weights(net, buff);
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}
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}
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}
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void validate_dice(char *filename, char *weightfile)
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{
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network net = parse_network_cfg(filename);
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if(weightfile){
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load_weights(&net, weightfile);
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}
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srand(time(0));
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char **labels = dice_labels;
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list *plist = get_paths("data/dice/dice.val.list");
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char **paths = (char **)list_to_array(plist);
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int m = plist->size;
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free_list(plist);
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data val = load_data_old(paths, m, 0, labels, 6, net.w, net.h);
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float *acc = network_accuracies(net, val, 2);
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printf("Validation Accuracy: %f, %d images\n", acc[0], m);
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free_data(val);
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}
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void test_dice(char *cfgfile, char *weightfile, char *filename)
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{
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network net = parse_network_cfg(cfgfile);
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if(weightfile){
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load_weights(&net, weightfile);
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}
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set_batch_network(&net, 1);
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srand(2222222);
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int i = 0;
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char **names = dice_labels;
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char buff[256];
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char *input = buff;
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int indexes[6];
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while(1){
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if(filename){
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strncpy(input, filename, 256);
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}else{
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printf("Enter Image Path: ");
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fflush(stdout);
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input = fgets(input, 256, stdin);
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if(!input) return;
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strtok(input, "\n");
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}
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image im = load_image_color(input, net.w, net.h);
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float *X = im.data;
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float *predictions = network_predict(net, X);
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top_predictions(net, 6, indexes);
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for(i = 0; i < 6; ++i){
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int index = indexes[i];
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printf("%s: %f\n", names[index], predictions[index]);
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}
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free_image(im);
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if (filename) break;
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}
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}
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void run_dice(int argc, char **argv)
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{
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if(argc < 4){
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fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]);
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return;
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}
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char *cfg = argv[3];
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char *weights = (argc > 4) ? argv[4] : 0;
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char *filename = (argc > 5) ? argv[5]: 0;
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if(0==strcmp(argv[2], "test")) test_dice(cfg, weights, filename);
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else if(0==strcmp(argv[2], "train")) train_dice(cfg, weights);
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else if(0==strcmp(argv[2], "valid")) validate_dice(cfg, weights);
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}
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