Question

使用以下参数调用Segmentation fault (core dumped)函数时出现draw_detections错误：

draw_detections(im, l.side*l.side*l.n, thresh, boxes, probs, voc_names, alphabet, 20);

这是我第一次使用Yolo，事实上，我不知道包含libs的{{1}}功能定义了哪个draw_detections。这是完整的事情：

#include "network.h"
#include "detection_layer.h"
#include "cost_layer.h"
#include "utils.h"
#include "parser.h"
#include "box.h"
#include "demo.h"

#ifdef OPENCV
#include "opencv2/highgui/highgui_c.h"
#endif

char *voc_names[] = {"face"};

void test_yolo(char *cfgfile, char *weightfile, char *filename, float thresh)
{
    printf("looking for faces");
    image **alphabet = load_alphabet();
    network net = parse_network_cfg(cfgfile);
    if(weightfile){
        load_weights(&net, weightfile);
    }
    detection_layer l = net.layers[net.n-1];
    set_batch_network(&net, 1);
    srand(2222222);
    clock_t time;
    char buff[256];
    char *input = buff;
    int j;
    float nms=.4;
    box *boxes = calloc(l.side*l.side*l.n, sizeof(box));
    float **probs = calloc(l.side*l.side*l.n, sizeof(float *));
    for(j = 0; j < l.side*l.side*l.n; ++j) probs[j] = calloc(l.classes, sizeof(float *));
    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);
        image sized = resize_image(im, net.w, net.h);
        float *X = sized.data;
        time=clock();
        network_predict(net, X);
        printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
        get_detection_boxes(l, 1, 1, thresh, probs, boxes, 0);
        if (nms) 
            do_nms_sort(boxes, probs, l.side*l.side*l.n, l.classes, nms);
        printf("check1\n"); //this statement is reached fine
        draw_detections(im, l.side*l.side*l.n, thresh, boxes, probs, voc_names, alphabet, 20);
        printf("check2\n"); //this statement is never reached
        save_image(im, "predictions");
        printf("just saved the img");
        show_image(im, "predictions");

        free_image(im);
        free_image(sized);
#ifdef OPENCV
        cvWaitKey(0);
        cvDestroyAllWindows();
#endif
        if (filename) break;
    }
}

void run_yolo(int argc, char **argv)
{
    printf("\n/nrunning Yolo....");
    char *prefix = find_char_arg(argc, argv, "-prefix", 0);
    float thresh = find_float_arg(argc, argv, "-thresh", .2);
    int cam_index = find_int_arg(argc, argv, "-c", 0);
    int frame_skip = find_int_arg(argc, argv, "-s", 0);
    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], "test")) test_yolo(cfg, weights, filename, thresh);

}

我正在使用以下命令运行它：

./darknet yolo test cfg/yolo-face.cfg yolo-face_final.weights data/faces.jpg

它加载权重并执行预测，但在到达draw_predictions()时崩溃。有什么想法吗？

编辑：这是我使用Valgrind

进行调试时获得的跟踪

   valgrind --leak-check=yes ./darknet yolo test cfg/yolo-face.cfg yolo-face_final.weights data/faces.jpg
==8582== Memcheck, a memory error detector
==8582== Copyright (C) 2002-2015, and GNU GPL'd, by Julian Seward et al.
==8582== Using Valgrind-3.11.0 and LibVEX; rerun with -h for copyright info
==8582== Command: ./darknet yolo test cfg/yolo-face.cfg yolo-face_final.weights data/faces.jpg
==8582== 
running Yolo....
layer     filters    size              input                output
    0 Crop Layer: 448 x 448 -> 448 x 448 x 3 image
shift: Using default '0.000000'
    1 conv     16  3 x 3 / 1   448 x 448 x   3   ->   448 x 448 x  16
    2 max          2 x 2 / 2   448 x 448 x  16   ->   224 x 224 x  16
    3 conv     32  3 x 3 / 1   224 x 224 x  16   ->   224 x 224 x  32
    4 max          2 x 2 / 2   224 x 224 x  32   ->   112 x 112 x  32
    5 conv     64  3 x 3 / 1   112 x 112 x  32   ->   112 x 112 x  64
    6 max          2 x 2 / 2   112 x 112 x  64   ->    56 x  56 x  64
    7 conv    128  3 x 3 / 1    56 x  56 x  64   ->    56 x  56 x 128
    8 max          2 x 2 / 2    56 x  56 x 128   ->    28 x  28 x 128
    9 conv    256  3 x 3 / 1    28 x  28 x 128   ->    28 x  28 x 256
   10 max          2 x 2 / 2    28 x  28 x 256   ->    14 x  14 x 256
   11 conv    512  3 x 3 / 1    14 x  14 x 256   ->    14 x  14 x 512
   12 max          2 x 2 / 2    14 x  14 x 512   ->     7 x   7 x 512
   13 conv   1024  3 x 3 / 1     7 x   7 x 512   ->     7 x   7 x1024
   14 conv   1024  3 x 3 / 1     7 x   7 x1024   ->     7 x   7 x1024
   15 conv   1024  3 x 3 / 1     7 x   7 x1024   ->     7 x   7 x1024
   16 connected                            50176  ->   256
   17 connected                             256  ->  4096
   18 dropout       p = 0.50               4096  ->  4096
   19 connected                            4096  ->  1331
   20 Detection Layer
forced: Using default '0'
Loading weights from yolo-face_final.weights...looking for facesDone!
data/faces.jpg: Predicted in 28.192593 seconds.
pre check
==8582== Invalid read of size 4
==8582==    at 0x407DA0: max_index (in /home/.../darknet/darknet)
==8582==    by 0x429492: draw_detections (in /home/.../darknet/darknet)
==8582==    by 0x456487: test_yolo (in /home/.../darknet/darknet)
==8582==    by 0x401F41: main (in /home/.../darknet/darknet)
==8582==  Address 0x7328f78 is 0 bytes after a block of size 8 alloc'd
==8582==    at 0x4C2FB55: calloc (in /usr/lib/valgrind/vgpreload_memcheck-amd64-linux.so)
==8582==    by 0x456300: test_yolo (in /home/.../darknet/darknet)
==8582==    by 0x401F41: main (in /home/.../darknet/darknet)
==8582== 
==8582== Invalid read of size 4
==8582==    at 0x42949B: draw_detections (in /home/.../darknet/darknet)
==8582==    by 0x456487: test_yolo (in /home/.../darknet/darknet)
==8582==    by 0x401F41: main (in /home/.../darknet/darknet)
==8582==  Address 0x7328fa0 is 32 bytes before a block of size 32 in arena "client"
==8582== 
face: 6%
face: 15%
face: 18%
face: 12%
face: 5%
face: 10%
face: 8%
face: 6%
face: 21%
face: 21%
face: 37%
face: 37%
face: 23%
face: 7%
face: 33%
face: 31%
face: 20%
face: 15%
face: 37%
face: 9%
face: 36%
face: 50%
face: 49%
face: 37%
face: 5%
face: 9%
face: 6%
face: 9%
face: 19%
face: 14%
face: 25%
face: 11%
face: 6%
face: 36%
face: 13%
face: 17%
face: 8%
face: 8%
face: 6%
After check
Not compiled with OpenCV, saving to predictions.png instead
just saved the img==8582== 
==8582== HEAP SUMMARY:
==8582==     in use at exit: 550,317,244 bytes in 1,116 blocks
==8582==   total heap usage: 98,171 allocs, 97,055 frees, 579,801,694 bytes allocated
==8582== 
==8582== 4 bytes in 1 blocks are definitely lost in loss record 2 of 37
==8582==    at 0x4C2FB55: calloc (in /usr/lib/valgrind/vgpreload_memcheck-amd64-linux.so)
==8582==    by 0x43E34D: make_network (in /home/.../darknet/darknet)
==8582==    by 0x444ABE: parse_network_cfg (in /home/.../darknet/darknet)
==8582==    by 0x456224: test_yolo (in /home/.../darknet/darknet)
==8582==    by 0x401F41: main (in /home/.../darknet/darknet)
==8582== 
==8582== 4 bytes in 1 blocks are definitely lost in loss record 3 of 37
==8582==    at 0x4C2FB55: calloc (in /usr/lib/valgrind/vgpreload_memcheck-amd64-linux.so)
==8582==    by 0x43E35F: make_network (in /home/.../darknet/darknet)
==8582==    by 0x444ABE: parse_network_cfg (in /home/.../darknet/darknet)
==8582==    by 0x456224: test_yolo (in /home/.../darknet/darknet)
==8582==    by 0x401F41: main (in /home/.../darknet/darknet)
==8582== 
==8582== 24 bytes in 1 blocks are definitely lost in loss record 4 of 37
==8582==    at 0x4C2FB55: calloc (in /usr/lib/valgrind/vgpreload_memcheck-amd64-linux.so)
==8582==    by 0x4447C3: parse_net_options (in /home/.../darknet/darknet)
==8582==    by 0x444B12: parse_network_cfg (in /home/.../darknet/darknet)
==8582==    by 0x456224: test_yolo (in /home/.../darknet/darknet)
==8582==    by 0x401F41: main (in /home/.../darknet/darknet)
==8582== 
==8582== 24 bytes in 1 blocks are definitely lost in loss record 5 of 37
==8582==    at 0x4C2FB55: calloc (in /usr/lib/valgrind/vgpreload_memcheck-amd64-linux.so)
==8582==    by 0x4447D5: parse_net_options (in /home/.../darknet/darknet)
==8582==    by 0x444B12: parse_network_cfg (in /home/.../darknet/darknet)
==8582==    by 0x456224: test_yolo (in /home/.../darknet/darknet)
==8582==    by 0x401F41: main (in /home/.../darknet/darknet)
==8582== 
==8582== 3,872 bytes in 1 blocks are definitely lost in loss record 7 of 37
==8582==    at 0x4C2FB55: calloc (in /usr/lib/valgrind/vgpreload_memcheck-amd64-linux.so)
==8582==    by 0x4562C1: test_yolo (in /home/.../darknet/darknet)
==8582==    by 0x401F41: main (in /home/.../darknet/darknet)
==8582== 
==8582== 3,872 (1,936 direct, 1,936 indirect) bytes in 1 blocks are definitely lost in loss record 8 of 37
==8582==    at 0x4C2FB55: calloc (in /usr/lib/valgrind/vgpreload_memcheck-amd64-linux.so)
==8582==    by 0x4562D1: test_yolo (in /home/.../darknet/darknet)
==8582==    by 0x401F41: main (in /home/.../darknet/darknet)
==8582== 
==8582== 5,808 bytes in 1 blocks are definitely lost in loss record 9 of 37
==8582==    at 0x4C2FB55: calloc (in /usr/lib/valgrind/vgpreload_memcheck-amd64-linux.so)
==8582==    by 0x445416: parse_network_cfg (in /home/.../darknet/darknet)
==8582==    by 0x456224: test_yolo (in /home/.../darknet/darknet)
==8582==    by 0x401F41: main (in /home/.../darknet/darknet)
==8582== 
==8582== 32,856 bytes in 1 blocks are possibly lost in loss record 18 of 37
==8582==    at 0x4C2FB55: calloc (in /usr/lib/valgrind/vgpreload_memcheck-amd64-linux.so)
==8582==    by 0x42DC33: load_image_stb (in /home/.../darknet/darknet)
==8582==    by 0x42DE1A: load_alphabet (in /home/.../darknet/darknet)
==8582==    by 0x456209: test_yolo (in /home/.../darknet/darknet)
==8582==    by 0x401F41: main (in /home/.../darknet/darknet)
==8582== 
==8582== 3,211,264 bytes in 1 blocks are possibly lost in loss record 21 of 37
==8582==    at 0x4C2FB55: calloc (in /usr/lib/valgrind/vgpreload_memcheck-amd64-linux.so)
==8582==    by 0x434D98: make_maxpool_layer (in /home/.../darknet/darknet)
==8582==    by 0x4462BC: parse_network_cfg (in /home/.../darknet/darknet)
==8582==    by 0x456224: test_yolo (in /home/.../darknet/darknet)
==8582==    by 0x401F41: main (in /home/.../darknet/darknet)
==8582== 
==8582== 4,816,896 bytes in 1 blocks are definitely lost in loss record 23 of 37
==8582==    at 0x4C2FB55: calloc (in /usr/lib/valgrind/vgpreload_memcheck-amd64-linux.so)
==8582==    by 0x445401: parse_network_cfg (in /home/.../darknet/darknet)
==8582==    by 0x456224: test_yolo (in /home/.../darknet/darknet)
==8582==    by 0x401F41: main (in /home/.../darknet/darknet)
==8582== 
==8582== 13,917,024 (192 direct, 13,916,832 indirect) bytes in 1 blocks are definitely lost in loss record 28 of 37
==8582==    at 0x4C2FB55: calloc (in /usr/lib/valgrind/vgpreload_memcheck-amd64-linux.so)
==8582==    by 0x42DDB5: load_alphabet (in /home/.../darknet/darknet)
==8582==    by 0x456209: test_yolo (in /home/.../darknet/darknet)
==8582==    by 0x401F41: main (in /home/.../darknet/darknet)
==8582== 
==8582== 25,690,112 bytes in 1 blocks are possibly lost in loss record 29 of 37
==8582==    at 0x4C2FB55: calloc (in /usr/lib/valgrind/vgpreload_memcheck-amd64-linux.so)
==8582==    by 0x40AB15: make_convolutional_layer (in /home/.../darknet/darknet)
==8582==    by 0x442203: parse_convolutional (in /home/.../darknet/darknet)
==8582==    by 0x4456A6: parse_network_cfg (in /home/.../darknet/darknet)
==8582==    by 0x456224: test_yolo (in /home/.../darknet/darknet)
==8582==    by 0x401F41: main (in /home/.../darknet/darknet)
==8582== 
==8582== 28,901,376 bytes in 1 blocks are definitely lost in loss record 31 of 37
==8582==    at 0x4C2FB55: calloc (in /usr/lib/valgrind/vgpreload_memcheck-amd64-linux.so)
==8582==    by 0x445435: parse_network_cfg (in /home/.../darknet/darknet)
==8582==    by 0x456224: test_yolo (in /home/.../darknet/darknet)
==8582==    by 0x401F41: main (in /home/.../darknet/darknet)
==8582== 
==8582== 473,734,108 (18,144 direct, 473,715,964 indirect) bytes in 1 blocks are definitely lost in loss record 37 of 37
==8582==    at 0x4C2FB55: calloc (in /usr/lib/valgrind/vgpreload_memcheck-amd64-linux.so)
==8582==    by 0x43E33B: make_network (in /home/.../darknet/darknet)
==8582==    by 0x444ABE: parse_network_cfg (in /home/.../darknet/darknet)
==8582==    by 0x456224: test_yolo (in /home/.../darknet/darknet)
==8582==    by 0x401F41: main (in /home/.../darknet/darknet)
==8582== 
==8582== LEAK SUMMARY:
==8582==    definitely lost: 33,748,280 bytes in 11 blocks
==8582==    indirectly lost: 487,634,732 bytes in 1,102 blocks
==8582==      possibly lost: 28,934,232 bytes in 3 blocks
==8582==    still reachable: 0 bytes in 0 blocks
==8582==         suppressed: 0 bytes in 0 blocks
==8582== 
==8582== For counts of detected and suppressed errors, rerun with: -v
==8582== ERROR SUMMARY: 4573 errors from 16 contexts (suppressed: 0 from 0)

哦，它给了我太多关于错误框边界的预测。减少相邻框数量的缺失参数是什么（因此我只得到相应的框）？

Answer 1

也调整nms值。 nms值是非最大值的阈值

Darknet Yolo：调用draw_detections函数

1 个答案: