Hacks to get nightmare to not break gridsizing

Joseph Redmon

2015-08-11 d0b9326a352ed2fbc3ae66fdef40b4533a2f211d

 src/detection.c

@@ -51,6 +51,8 @@

void train_detection(char *cfgfile, char *weightfile)
{
    char *train_images = "/home/pjreddie/data/voc/test/train.txt";
    char *backup_directory = "/home/pjreddie/backup/";
    srand(time(0));
    data_seed = time(0);
    char *base = basecfg(cfgfile);
@@ -71,13 +73,13 @@
    int side = sqrt(get_detection_layer_locations(layer));

    char **paths;
    list *plist = get_paths("/home/pjreddie/data/voc/test/train.txt");
    list *plist = get_paths(train_images);
    int N = plist->size;

    paths = (char **)list_to_array(plist);
    pthread_t load_thread = load_data_detection_thread(imgs, paths, plist->size, classes, net.w, net.h, side, side, background, &buffer);
    clock_t time;
    while(i*imgs < N*120){
    while(i*imgs < N*130){
        i += 1;
        time=clock();
        pthread_join(load_thread, 0);
@@ -93,29 +95,36 @@

        printf("%d: %f, %f avg, %lf seconds, %d images\n", i, loss, avg_loss, sec(clock()-time), i*imgs);
        if((i-1)*imgs <= N && i*imgs > N){
            fprintf(stderr, "Starting second stage...\n");
            fprintf(stderr, "First stage done\n");
            net.learning_rate *= 10;
            char buff[256];
            sprintf(buff, "/home/pjreddie/imagenet_backup/%s_first_stage.weights", base);
            sprintf(buff, "%s/%s_first_stage.weights", backup_directory, base);
            save_weights(net, buff);
        }
        if((i-1)*imgs <= 80*N && i*imgs > N*80){
            fprintf(stderr, "Second stage done.\n");
            net.learning_rate *= .1;
            char buff[256];
            sprintf(buff, "/home/pjreddie/imagenet_backup/%s_second_stage.weights", base);
            sprintf(buff, "%s/%s_second_stage.weights", backup_directory, base);
            save_weights(net, buff);
            return;
        }
        if((i-1)*imgs <= 120*N && i*imgs > N*120){
            fprintf(stderr, "Third stage done.\n");
            char buff[256];
            sprintf(buff, "%s/%s_third_stage.weights", backup_directory, base);
            net.layers[net.n-1].rescore = 1;
            save_weights(net, buff);
        }
        if(i%1000==0){
            char buff[256];
            sprintf(buff, "/home/pjreddie/imagenet_backup/%s_%d.weights",base, i);
            sprintf(buff, "%s/%s_%d.weights", backup_directory, base, i);
            save_weights(net, buff);
        }
        free_data(train);
    }
    char buff[256];
    sprintf(buff, "/home/pjreddie/imagenet_backup/%s_final.weights",base);
    sprintf(buff, "%s/%s_final.weights", backup_directory, base);
    save_weights(net, buff);
}

@@ -141,26 +150,6 @@
    }
}

void do_nms(box *boxes, float **probs, int num_boxes, int classes, float thresh)
{
    int i, j, k;
    for(i = 0; i < num_boxes*num_boxes; ++i){
        int any = 0;
        for(k = 0; k < classes; ++k) any = any || (probs[i][k] > 0);
        if(!any) {
            continue;
        }
        for(j = i+1; j < num_boxes*num_boxes; ++j){
            if (box_iou(boxes[i], boxes[j]) > thresh){
                for(k = 0; k < classes; ++k){
                    if (probs[i][k] < probs[j][k]) probs[i][k] = 0;
                    else probs[j][k] = 0;
                }
            }
        }
    }
}

void print_detections(FILE **fps, char *id, box *boxes, float **probs, int num_boxes, int classes, int w, int h)
{
    int i, j;
@@ -194,7 +183,7 @@
    srand(time(0));

    char *base = "results/comp4_det_test_";
    list *plist = get_paths("data/voc.2012test.list");
    list *plist = get_paths("/home/pjreddie/data/voc/test/2007_test.txt");
    char **paths = (char **)list_to_array(plist);

    int classes = layer.classes;