使用以下参数调用函数时Segmentation fault (core dumped)出现错误：draw_detections
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的哪个libs定义了draw_detections函数。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，但在达到draw_predictions(). 任何想法为什么？
编辑：这是我使用调试时得到的跟踪Valgrind
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，它给了我太多带有错误框边界的预测。减少相邻框数量的缺失参数是什么（这样我只能得到适当的框）？
