@crossbot I will murder you in your sleep ⚔️

examples/super.c

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+#include "darknet/network.h"
+#include "darknet/cost_layer.h"
+#include "darknet/utils.h"
+#include "darknet/parser.h"
+
+void train_super(char *cfgfile, char *weightfile, int clear)
+{
+    char *train_images = "/data/imagenet/imagenet1k.train.list";
+    char *backup_directory = "/home/pjreddie/backup/";
+    srand(time(0));
+    char *base = basecfg(cfgfile);
+    printf("%s\n", base);
+    float avg_loss = -1;
+    network net = parse_network_cfg(cfgfile);
+    if(weightfile){
+        load_weights(&net, weightfile);
+    }
+    if(clear) *net.seen = 0;
+    printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
+    int imgs = net.batch*net.subdivisions;
+    int i = *net.seen/imgs;
+    data train, buffer;
+
+
+    list *plist = get_paths(train_images);
+    //int N = plist->size;
+    char **paths = (char **)list_to_array(plist);
+
+    load_args args = {0};
+    args.w = net.w;
+    args.h = net.h;
+    args.scale = 4;
+    args.paths = paths;
+    args.n = imgs;
+    args.m = plist->size;
+    args.d = &buffer;
+    args.type = SUPER_DATA;
+
+    pthread_t load_thread = load_data_in_thread(args);
+    clock_t time;
+    //while(i*imgs < N*120){
+    while(get_current_batch(net) < net.max_batches){
+        i += 1;
+        time=clock();
+        pthread_join(load_thread, 0);
+        train = buffer;
+        load_thread = load_data_in_thread(args);
+
+        printf("Loaded: %lf seconds\n", sec(clock()-time));
+
+        time=clock();
+        float loss = train_network(net, train);
+        if (avg_loss < 0) avg_loss = loss;
+        avg_loss = avg_loss*.9 + loss*.1;
+
+        printf("%d: %f, %f avg, %f rate, %lf seconds, %d images\n", i, loss, avg_loss, get_current_rate(net), sec(clock()-time), i*imgs);
+        if(i%1000==0){
+            char buff[256];
+            sprintf(buff, "%s/%s_%d.weights", backup_directory, base, i);
+            save_weights(net, buff);
+        }
+        if(i%100==0){
+            char buff[256];
+            sprintf(buff, "%s/%s.backup", backup_directory, base);
+            save_weights(net, buff);
+        }
+        free_data(train);
+    }
+    char buff[256];
+    sprintf(buff, "%s/%s_final.weights", backup_directory, base);
+    save_weights(net, buff);
+}
+
+void test_super(char *cfgfile, char *weightfile, char *filename)
+{
+    network net = parse_network_cfg(cfgfile);
+    if(weightfile){
+        load_weights(&net, weightfile);
+    }
+    set_batch_network(&net, 1);
+    srand(2222222);
+
+    clock_t time;
+    char buff[256];
+    char *input = buff;
+    while(1){
+        if(filename){
+            strncpy(input, filename, 256);
+        }else{
+            printf("Enter Image Path: ");
+            fflush(stdout);
+            input = fgets(input, 256, stdin);
+            if(!input) return;
+            strtok(input, "\n");
+        }
+        image im = load_image_color(input, 0, 0);
+        resize_network(&net, im.w, im.h);
+        printf("%d %d\n", im.w, im.h);
+
+        float *X = im.data;
+        time=clock();
+        network_predict(net, X);
+        image out = get_network_image(net);
+        printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
+        save_image(out, "out");
+
+        free_image(im);
+        if (filename) break;
+    }
+}
+
+
+void run_super(int argc, char **argv)
+{
+    if(argc < 4){
+        fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]);
+        return;
+    }
+
+    char *cfg = argv[3];
+    char *weights = (argc > 4) ? argv[4] : 0;
+    char *filename = (argc > 5) ? argv[5] : 0;
+    int clear = find_arg(argc, argv, "-clear");
+    if(0==strcmp(argv[2], "train")) train_super(cfg, weights, clear);
+    else if(0==strcmp(argv[2], "test")) test_super(cfg, weights, filename);
+    /*
+    else if(0==strcmp(argv[2], "valid")) validate_super(cfg, weights);
+    */
+}