@crossbot I will murder you in your sleep ⚔️

2023-08-10 21:13:14 +03:00 · 2017-05-31 21:06:35 -07:00
parent 579e588c84
commit 1ef829e585
74 changed files with 404 additions and 393 deletions
--- a/examples/writing.c
+++ b/examples/writing.c
@@ -0,0 +1,146 @@
+#include "darknet/network.h"
+#include "darknet/utils.h"
+#include "darknet/parser.h"
+
+void train_writing(char *cfgfile, char *weightfile)
+{
+    char *backup_directory = "/home/pjreddie/backup/";
+    srand(time(0));
+    float avg_loss = -1;
+    char *base = basecfg(cfgfile);
+    printf("%s\n", base);
+    network net = parse_network_cfg(cfgfile);
+    if(weightfile){
+        load_weights(&net, weightfile);
+    }
+    printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
+    int imgs = net.batch*net.subdivisions;
+    list *plist = get_paths("figures.list");
+    char **paths = (char **)list_to_array(plist);
+    clock_t time;
+    int N = plist->size;
+    printf("N: %d\n", N);
+    image out = get_network_image(net);
+
+    data train, buffer;
+
+    load_args args = {0};
+    args.w = net.w;
+    args.h = net.h;
+    args.out_w = out.w;
+    args.out_h = out.h;
+    args.paths = paths;
+    args.n = imgs;
+    args.m = N;
+    args.d = &buffer;
+    args.type = WRITING_DATA;
+
+    pthread_t load_thread = load_data_in_thread(args);
+    int epoch = (*net.seen)/N;
+    while(get_current_batch(net) < net.max_batches || net.max_batches == 0){
+        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);
+
+        /*
+           image pred = float_to_image(64, 64, 1, out);
+           print_image(pred);
+         */
+
+        /*
+           image im = float_to_image(256, 256, 3, train.X.vals[0]);
+           image lab = float_to_image(64, 64, 1, train.y.vals[0]);
+           image pred = float_to_image(64, 64, 1, out);
+           show_image(im, "image");
+           show_image(lab, "label");
+           print_image(lab);
+           show_image(pred, "pred");
+           cvWaitKey(0);
+         */
+
+        if(avg_loss == -1) avg_loss = loss;
+        avg_loss = avg_loss*.9 + loss*.1;
+        printf("%d, %.3f: %f, %f avg, %f rate, %lf seconds, %d images\n", get_current_batch(net), (float)(*net.seen)/N, loss, avg_loss, get_current_rate(net), sec(clock()-time), *net.seen);
+        free_data(train);
+        if(get_current_batch(net)%100 == 0){
+            char buff[256];
+            sprintf(buff, "%s/%s_batch_%d.weights", backup_directory, base, get_current_batch(net));
+            save_weights(net, buff);
+        }
+        if(*net.seen/N > epoch){
+            epoch = *net.seen/N;
+            char buff[256];
+            sprintf(buff, "%s/%s_%d.weights",backup_directory,base, epoch);
+            save_weights(net, buff);
+        }
+    }
+}
+
+void test_writing(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 %d\n", im.h, im.w, im.c);
+        float *X = im.data;
+        time=clock();
+        network_predict(net, X);
+        printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
+        image pred = get_network_image(net);
+
+        image upsampled = resize_image(pred, im.w, im.h);
+        image thresh = threshold_image(upsampled, .5);
+        pred = thresh;
+
+        show_image(pred, "prediction");
+        show_image(im, "orig");
+#ifdef OPENCV
+        cvWaitKey(0);
+        cvDestroyAllWindows();
+#endif
+
+        free_image(upsampled);
+        free_image(thresh);
+        free_image(im);
+        if (filename) break;
+    }
+}
+
+void run_writing(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;
+    if(0==strcmp(argv[2], "train")) train_writing(cfg, weights);
+    else if(0==strcmp(argv[2], "test")) test_writing(cfg, weights, filename);
+}
+