weixin_39797693
weixin_39797693
2020-11-24 23:01

Yolo v3 crashes after detections on first image

I have some issues when running your latest commit that brought Yolo v3 support (c4512345e95779848d918d501caae37accc9439e). darknet_ros crashes just after performing detections on the first image. I copy/pasted the log below using gdb.

Do you have any idea? The same commit works very well with Yolo v2.


roslaunch em_task_manager darknet_ros_yolo_v3_gdb.launch 
... logging to /root/.ros/log/20180426-000028_d4333b82-48e4-11e8-830c-003064445192/roslaunch-hsr-17375.log
Checking log directory for disk usage. This may take awhile.
Press Ctrl-C to interrupt
Done checking log file disk usage. Usage is <1GB.

started roslaunch server http://192.168.1.21:45799/

SUMMARY
========

PARAMETERS
 * /darknet_ros/actions/camera_reading/name: /darknet_ros/chec...
 * /darknet_ros/config_path: /root/catkin_ws/s...
 * /darknet_ros/image_view/enable_console_output: False
 * /darknet_ros/image_view/enable_opencv: False
 * /darknet_ros/image_view/wait_key_delay: 1
 * /darknet_ros/publishers/bounding_boxes/latch: False
 * /darknet_ros/publishers/bounding_boxes/queue_size: 1
 * /darknet_ros/publishers/bounding_boxes/topic: /darknet_ros/boun...
 * /darknet_ros/publishers/detection_image/latch: True
 * /darknet_ros/publishers/detection_image/queue_size: 1
 * /darknet_ros/publishers/detection_image/topic: /darknet_ros/dete...
 * /darknet_ros/publishers/object_detector/latch: False
 * /darknet_ros/publishers/object_detector/queue_size: 1
 * /darknet_ros/publishers/object_detector/topic: /darknet_ros/foun...
 * /darknet_ros/subscribers/camera_reading/queue_size: 1
 * /darknet_ros/subscribers/camera_reading/topic: /hsrb/head_rgbd_s...
 * /darknet_ros/weights_path: /root/catkin_ws/s...
 * /darknet_ros/yolo_model/config_file/name: yolov3.cfg
 * /darknet_ros/yolo_model/detection_classes/names: ['person', 'bicyc...
 * /darknet_ros/yolo_model/threshold/value: 0.3
 * /darknet_ros/yolo_model/weight_file/name: yolov3.weights
 * /rosdistro: kinetic
 * /rosversion: 1.12.13

NODES
  /
    darknet_ros (darknet_ros/darknet_ros)

ROS_MASTER_URI=http://hsrb.local:11311

process[darknet_ros-1]: started with pid [17384]
GNU gdb (Ubuntu 7.11.1-0ubuntu1~16.5) 7.11.1
Copyright (C) 2016 Free Software Foundation, Inc.
License GPLv3+: GNU GPL version 3 or later <http:>
This is free software: you are free to change and redistribute it.
There is NO WARRANTY, to the extent permitted by law.  Type "show copying"
and "show warranty" for details.
This GDB was configured as "x86_64-linux-gnu".
Type "show configuration" for configuration details.
For bug reporting instructions, please see:
<http:></http:>.
Find the GDB manual and other documentation resources online at:
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For help, type "help".
Type "apropos word" to search for commands related to "word"...
Reading symbols from /root/catkin_ws/devel/lib/darknet_ros/darknet_ros...done.
Starting program: /root/catkin_ws/devel/lib/darknet_ros/darknet_ros __name:=darknet_ros __log:=/root/.ros/log/20180426-000028_d4333b82-48e4-11e8-830c-003064445192/darknet_ros-1.log
[tcsetpgrp failed in terminal_inferior: Inappropriate ioctl for device]
[tcsetpgrp failed in terminal_inferior: Inappropriate ioctl for device]
[Thread debugging using libthread_db enabled]
Using host libthread_db library "/lib/x86_64-linux-gnu/libthread_db.so.1".
[tcsetpgrp failed in terminal_inferior: Inappropriate ioctl for device]
[tcsetpgrp failed in terminal_inferior: Inappropriate ioctl for device]
[New Thread 0x7fffd5085700 (LWP 17390)]
[New Thread 0x7fffd4884700 (LWP 17391)]
[New Thread 0x7fffcffff700 (LWP 17392)]
[New Thread 0x7fffcf7fe700 (LWP 17393)]
[ INFO] [1524705011.716676073]: [YoloObjectDetector] Node started.
[ INFO] [1524705011.821020275]: [YoloObjectDetector] Xserver is running.
[ INFO] [1524705011.860997818]: [YoloObjectDetector] init().
YOLO V3
layer     filters    size              input                output
    0 [tcsetpgrp failed in terminal_inferior: Inappropriate ioctl for device]
[New Thread 0x7fffb6a1d700 (LWP 17394)]
[New Thread 0x7fffb621c700 (LWP 17395)]
[New Thread 0x7fffb57ff700 (LWP 17396)]
conv     32  3 x 3 / 1   416 x 416 x   3   ->   416 x 416 x  32  0.299 BFLOPs
    1 conv     64  3 x 3 / 2   416 x 416 x  32   ->   208 x 208 x  64  1.595 BFLOPs
    2 conv     32  1 x 1 / 1   208 x 208 x  64   ->   208 x 208 x  32  0.177 BFLOPs
    3 conv     64  3 x 3 / 1   208 x 208 x  32   ->   208 x 208 x  64  1.595 BFLOPs
    4 res    1                 208 x 208 x  64   ->   208 x 208 x  64
    5 conv    128  3 x 3 / 2   208 x 208 x  64   ->   104 x 104 x 128  1.595 BFLOPs
    6 conv     64  1 x 1 / 1   104 x 104 x 128   ->   104 x 104 x  64  0.177 BFLOPs
    7 conv    128  3 x 3 / 1   104 x 104 x  64   ->   104 x 104 x 128  1.595 BFLOPs
    8 res    5                 104 x 104 x 128   ->   104 x 104 x 128
    9 conv     64  1 x 1 / 1   104 x 104 x 128   ->   104 x 104 x  64  0.177 BFLOPs
   10 conv    128  3 x 3 / 1   104 x 104 x  64   ->   104 x 104 x 128  1.595 BFLOPs
   11 res    8                 104 x 104 x 128   ->   104 x 104 x 128
   12 conv    256  3 x 3 / 2   104 x 104 x 128   ->    52 x  52 x 256  1.595 BFLOPs
   13 conv    128  1 x 1 / 1    52 x  52 x 256   ->    52 x  52 x 128  0.177 BFLOPs
   14 conv    256  3 x 3 / 1    52 x  52 x 128   ->    52 x  52 x 256  1.595 BFLOPs
   15 res   12                  52 x  52 x 256   ->    52 x  52 x 256
   16 conv    128  1 x 1 / 1    52 x  52 x 256   ->    52 x  52 x 128  0.177 BFLOPs
   17 conv    256  3 x 3 / 1    52 x  52 x 128   ->    52 x  52 x 256  1.595 BFLOPs
   18 res   15                  52 x  52 x 256   ->    52 x  52 x 256
   19 conv    128  1 x 1 / 1    52 x  52 x 256   ->    52 x  52 x 128  0.177 BFLOPs
   20 conv    256  3 x 3 / 1    52 x  52 x 128   ->    52 x  52 x 256  1.595 BFLOPs
   21 res   18                  52 x  52 x 256   ->    52 x  52 x 256
   22 conv    128  1 x 1 / 1    52 x  52 x 256   ->    52 x  52 x 128  0.177 BFLOPs
   23 conv    256  3 x 3 / 1    52 x  52 x 128   ->    52 x  52 x 256  1.595 BFLOPs
   24 res   21                  52 x  52 x 256   ->    52 x  52 x 256
   25 conv    128  1 x 1 / 1    52 x  52 x 256   ->    52 x  52 x 128  0.177 BFLOPs
   26 conv    256  3 x 3 / 1    52 x  52 x 128   ->    52 x  52 x 256  1.595 BFLOPs
   27 res   24                  52 x  52 x 256   ->    52 x  52 x 256
   28 conv    128  1 x 1 / 1    52 x  52 x 256   ->    52 x  52 x 128  0.177 BFLOPs
   29 conv    256  3 x 3 / 1    52 x  52 x 128   ->    52 x  52 x 256  1.595 BFLOPs
   30 res   27                  52 x  52 x 256   ->    52 x  52 x 256
   31 conv    128  1 x 1 / 1    52 x  52 x 256   ->    52 x  52 x 128  0.177 BFLOPs
   32 conv    256  3 x 3 / 1    52 x  52 x 128   ->    52 x  52 x 256  1.595 BFLOPs
   33 res   30                  52 x  52 x 256   ->    52 x  52 x 256
   34 conv    128  1 x 1 / 1    52 x  52 x 256   ->    52 x  52 x 128  0.177 BFLOPs
   35 conv    256  3 x 3 / 1    52 x  52 x 128   ->    52 x  52 x 256  1.595 BFLOPs
   36 res   33                  52 x  52 x 256   ->    52 x  52 x 256
   37 conv    512  3 x 3 / 2    52 x  52 x 256   ->    26 x  26 x 512  1.595 BFLOPs
   38 conv    256  1 x 1 / 1    26 x  26 x 512   ->    26 x  26 x 256  0.177 BFLOPs
   39 conv    512  3 x 3 / 1    26 x  26 x 256   ->    26 x  26 x 512  1.595 BFLOPs
   40 res   37                  26 x  26 x 512   ->    26 x  26 x 512
   41 conv    256  1 x 1 / 1    26 x  26 x 512   ->    26 x  26 x 256  0.177 BFLOPs
   42 conv    512  3 x 3 / 1    26 x  26 x 256   ->    26 x  26 x 512  1.595 BFLOPs
   43 res   40                  26 x  26 x 512   ->    26 x  26 x 512
   44 conv    256  1 x 1 / 1    26 x  26 x 512   ->    26 x  26 x 256  0.177 BFLOPs
   45 conv    512  3 x 3 / 1    26 x  26 x 256   ->    26 x  26 x 512  1.595 BFLOPs
   46 res   43                  26 x  26 x 512   ->    26 x  26 x 512
   47 conv    256  1 x 1 / 1    26 x  26 x 512   ->    26 x  26 x 256  0.177 BFLOPs
   48 conv    512  3 x 3 / 1    26 x  26 x 256   ->    26 x  26 x 512  1.595 BFLOPs
   49 res   46                  26 x  26 x 512   ->    26 x  26 x 512
   50 conv    256  1 x 1 / 1    26 x  26 x 512   ->    26 x  26 x 256  0.177 BFLOPs
   51 conv    512  3 x 3 / 1    26 x  26 x 256   ->    26 x  26 x 512  1.595 BFLOPs
   52 res   49                  26 x  26 x 512   ->    26 x  26 x 512
   53 conv    256  1 x 1 / 1    26 x  26 x 512   ->    26 x  26 x 256  0.177 BFLOPs
   54 conv    512  3 x 3 / 1    26 x  26 x 256   ->    26 x  26 x 512  1.595 BFLOPs
   55 res   52                  26 x  26 x 512   ->    26 x  26 x 512
   56 conv    256  1 x 1 / 1    26 x  26 x 512   ->    26 x  26 x 256  0.177 BFLOPs
   57 conv    512  3 x 3 / 1    26 x  26 x 256   ->    26 x  26 x 512  1.595 BFLOPs
   58 res   55                  26 x  26 x 512   ->    26 x  26 x 512
   59 conv    256  1 x 1 / 1    26 x  26 x 512   ->    26 x  26 x 256  0.177 BFLOPs
   60 conv    512  3 x 3 / 1    26 x  26 x 256   ->    26 x  26 x 512  1.595 BFLOPs
   61 res   58                  26 x  26 x 512   ->    26 x  26 x 512
   62 conv   1024  3 x 3 / 2    26 x  26 x 512   ->    13 x  13 x1024  1.595 BFLOPs
   63 conv    512  1 x 1 / 1    13 x  13 x1024   ->    13 x  13 x 512  0.177 BFLOPs
   64 conv   1024  3 x 3 / 1    13 x  13 x 512   ->    13 x  13 x1024  1.595 BFLOPs
   65 res   62                  13 x  13 x1024   ->    13 x  13 x1024
   66 conv    512  1 x 1 / 1    13 x  13 x1024   ->    13 x  13 x 512  0.177 BFLOPs
   67 conv   1024  3 x 3 / 1    13 x  13 x 512   ->    13 x  13 x1024  1.595 BFLOPs
   68 res   65                  13 x  13 x1024   ->    13 x  13 x1024
   69 conv    512  1 x 1 / 1    13 x  13 x1024   ->    13 x  13 x 512  0.177 BFLOPs
   70 conv   1024  3 x 3 / 1    13 x  13 x 512   ->    13 x  13 x1024  1.595 BFLOPs
   71 res   68                  13 x  13 x1024   ->    13 x  13 x1024
   72 conv    512  1 x 1 / 1    13 x  13 x1024   ->    13 x  13 x 512  0.177 BFLOPs
   73 conv   1024  3 x 3 / 1    13 x  13 x 512   ->    13 x  13 x1024  1.595 BFLOPs
   74 res   71                  13 x  13 x1024   ->    13 x  13 x1024
   75 conv    512  1 x 1 / 1    13 x  13 x1024   ->    13 x  13 x 512  0.177 BFLOPs
   76 conv   1024  3 x 3 / 1    13 x  13 x 512   ->    13 x  13 x1024  1.595 BFLOPs
   77 conv    512  1 x 1 / 1    13 x  13 x1024   ->    13 x  13 x 512  0.177 BFLOPs
   78 conv   1024  3 x 3 / 1    13 x  13 x 512   ->    13 x  13 x1024  1.595 BFLOPs
   79 conv    512  1 x 1 / 1    13 x  13 x1024   ->    13 x  13 x 512  0.177 BFLOPs
   80 conv   1024  3 x 3 / 1    13 x  13 x 512   ->    13 x  13 x1024  1.595 BFLOPs
   81 conv    255  1 x 1 / 1    13 x  13 x1024   ->    13 x  13 x 255  0.088 BFLOPs
   82 detection
   83 route  79
   84 conv    256  1 x 1 / 1    13 x  13 x 512   ->    13 x  13 x 256  0.044 BFLOPs
   85 upsample            2x    13 x  13 x 256   ->    26 x  26 x 256
   86 route  85 61
   87 conv    256  1 x 1 / 1    26 x  26 x 768   ->    26 x  26 x 256  0.266 BFLOPs
   88 conv    512  3 x 3 / 1    26 x  26 x 256   ->    26 x  26 x 512  1.595 BFLOPs
   89 conv    256  1 x 1 / 1    26 x  26 x 512   ->    26 x  26 x 256  0.177 BFLOPs
   90 conv    512  3 x 3 / 1    26 x  26 x 256   ->    26 x  26 x 512  1.595 BFLOPs
   91 conv    256  1 x 1 / 1    26 x  26 x 512   ->    26 x  26 x 256  0.177 BFLOPs
   92 conv    512  3 x 3 / 1    26 x  26 x 256   ->    26 x  26 x 512  1.595 BFLOPs
   93 conv    255  1 x 1 / 1    26 x  26 x 512   ->    26 x  26 x 255  0.177 BFLOPs
   94 detection
   95 route  91
   96 conv    128  1 x 1 / 1    26 x  26 x 256   ->    26 x  26 x 128  0.044 BFLOPs
   97 upsample            2x    26 x  26 x 128   ->    52 x  52 x 128
   98 route  97 36
   99 conv    128  1 x 1 / 1    52 x  52 x 384   ->    52 x  52 x 128  0.266 BFLOPs
  100 conv    256  3 x 3 / 1    52 x  52 x 128   ->    52 x  52 x 256  1.595 BFLOPs
  101 conv    128  1 x 1 / 1    52 x  52 x 256   ->    52 x  52 x 128  0.177 BFLOPs
  102 conv    256  3 x 3 / 1    52 x  52 x 128   ->    52 x  52 x 256  1.595 BFLOPs
  103 conv    128  1 x 1 / 1    52 x  52 x 256   ->    52 x  52 x 128  0.177 BFLOPs
  104 conv    256  3 x 3 / 1    52 x  52 x 128   ->    52 x  52 x 256  1.595 BFLOPs
  105 conv    255  1 x 1 / 1    52 x  52 x 256   ->    52 x  52 x 255  0.353 BFLOPs
  106 detection
Loading weights from /root/catkin_ws/src/darknet_ros/darknet_ros/yolo_network_config/weights/yolov3.weights...Done!
Loading weights from /root/catkin_ws/src/darknet_ros/darknet_ros/yolo_network_config/weights/yolov3.weights...Done!
[New Thread 0x7fff415ff700 (LWP 17397)]
Waiting for image.
[tcsetpgrp failed in terminal_inferior: Inappropriate ioctl for device]
[New Thread 0x7fff40dfe700 (LWP 17398)]
[New Thread 0x7fff3bfff700 (LWP 17399)]
[New Thread 0x7fff337fe700 (LWP 17400)]
[New Thread 0x7fff3b7fe700 (LWP 17401)]
[New Thread 0x7fff3affd700 (LWP 17402)]
[New Thread 0x7fff3a7fc700 (LWP 17403)]
[New Thread 0x7fff39ffb700 (LWP 17404)]
[New Thread 0x7fff397fa700 (LWP 17405)]
[New Thread 0x7fff38ff9700 (LWP 17406)]
[New Thread 0x7fff33fff700 (LWP 17407)]
[New Thread 0x7fff32ffd700 (LWP 17408)]
[Thread 0x7fff33fff700 (LWP 17407) exited]
person: 96%
bench: 76%
refrigerator: 56%
refrigerator: 52%
chair: 49%
bottle: 36%

Thread 20 "darknet_ros" received signal SIGSEGV, Segmentation fault.
[Switching to Thread 0x7fff32ffd700 (LWP 17408)]
darknet_ros::YoloObjectDetector::detectInThread (this=0x7fffffffcff0)
    at /root/catkin_ws/src/darknet_ros/darknet_ros/src/YoloObjectDetector.cpp:373
---Type <return> to continue, or q <return> to quit---
</return></return></http:>

该提问来源于开源项目:leggedrobotics/darknet_ros

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6条回答

  • weixin_39950081 weixin_39950081 5月前

    Is this happening at every run?

    -Marko

    On 26 Apr 2018, at 07:23, Lotfi El Hafi wrote:

    I have some issues when running your latest commit that brought Yolo v3 support (c451234). darknet_ros crashes just after performing detections on the first image. I copy/pasted the log below using gdb.

    Do you have any idea? The same commit works very well with Yolo v2.

    roslaunch em_task_manager darknet_ros_yolo_v3_gdb.launch ... logging to /root/.ros/log/20180426-000028_d4333b82-48e4-11e8-830c-003064445192/roslaunch-hsr-17375.log Checking log directory for disk usage. This may take awhile. Press Ctrl-C to interrupt Done checking log file disk usage. Usage is <1GB.

    started roslaunch server http://192.168.1.21:45799/

    SUMMARY

    PARAMETERS * /darknet_ros/actions/camera_reading/name: /darknet_ros/chec... * /darknet_ros/config_path: /root/catkin_ws/s... * /darknet_ros/image_view/enable_console_output: False * /darknet_ros/image_view/enable_opencv: False * /darknet_ros/image_view/wait_key_delay: 1 * /darknet_ros/publishers/bounding_boxes/latch: False * /darknet_ros/publishers/bounding_boxes/queue_size: 1 * /darknet_ros/publishers/bounding_boxes/topic: /darknet_ros/boun... * /darknet_ros/publishers/detection_image/latch: True * /darknet_ros/publishers/detection_image/queue_size: 1 * /darknet_ros/publishers/detection_image/topic: /darknet_ros/dete... * /darknet_ros/publishers/object_detector/latch: False * /darknet_ros/publishers/object_detector/queue_size: 1 * /darknet_ros/publishers/object_detector/topic: /darknet_ros/foun... * /darknet_ros/subscribers/camera_reading/queue_size: 1 * /darknet_ros/subscribers/camera_reading/topic: /hsrb/head_rgbd_s... * /darknet_ros/weights_path: /root/catkin_ws/s... * /darknet_ros/yolo_model/config_file/name: yolov3.cfg * /darknet_ros/yolo_model/detection_classes/names: ['person', 'bicyc... * /darknet_ros/yolo_model/threshold/value: 0.3 * /darknet_ros/yolo_model/weight_file/name: yolov3.weights * /rosdistro: kinetic * /rosversion: 1.12.13

    NODES / darknet_ros (darknet_ros/darknet_ros)

    ROS_MASTER_URI=http://hsrb.local:11311

    process[darknet_ros-1]: started with pid [17384] GNU gdb (Ubuntu 7.11.1-0ubuntu1~16.5) 7.11.1 Copyright (C) 2016 Free Software Foundation, Inc. License GPLv3+: GNU GPL version 3 or later http://gnu.org/licenses/gpl.html This is free software: you are free to change and redistribute it. There is NO WARRANTY, to the extent permitted by law. Type "show copying" and "show warranty" for details. This GDB was configured as "x86_64-linux-gnu". Type "show configuration" for configuration details. For bug reporting instructions, please see: http://www.gnu.org/software/gdb/bugs/. Find the GDB manual and other documentation resources online at: http://www.gnu.org/software/gdb/documentation/. For help, type "help". Type "apropos word" to search for commands related to "word"... Reading symbols from /root/catkin_ws/devel/lib/darknet_ros/darknet_ros...done. Starting program: /root/catkin_ws/devel/lib/darknet_ros/darknet_ros __name:=darknet_ros __log:=/root/.ros/log/20180426-000028_d4333b82-48e4-11e8-830c-003064445192/darknet_ros-1.log [tcsetpgrp failed in terminal_inferior: Inappropriate ioctl for device] [tcsetpgrp failed in terminal_inferior: Inappropriate ioctl for device] [Thread debugging using libthread_db enabled] Using host libthread_db library "/lib/x86_64-linux-gnu/libthread_db.so.1". [tcsetpgrp failed in terminal_inferior: Inappropriate ioctl for device] [tcsetpgrp failed in terminal_inferior: Inappropriate ioctl for device] [New Thread 0x7fffd5085700 (LWP 17390)] [New Thread 0x7fffd4884700 (LWP 17391)] [New Thread 0x7fffcffff700 (LWP 17392)] [New Thread 0x7fffcf7fe700 (LWP 17393)] [ INFO] [1524705011.716676073]: [YoloObjectDetector] Node started. [ INFO] [1524705011.821020275]: [YoloObjectDetector] Xserver is running. [ INFO] [1524705011.860997818]: [YoloObjectDetector] init(). YOLO V3 layer filters size input output 0 [tcsetpgrp failed in terminal_inferior: Inappropriate ioctl for device] [New Thread 0x7fffb6a1d700 (LWP 17394)] [New Thread 0x7fffb621c700 (LWP 17395)] [New Thread 0x7fffb57ff700 (LWP 17396)] conv 32 3 x 3 / 1 416 x 416 x 3 -> 416 x 416 x 32 0.299 BFLOPs 1 conv 64 3 x 3 / 2 416 x 416 x 32 -> 208 x 208 x 64 1.595 BFLOPs 2 conv 32 1 x 1 / 1 208 x 208 x 64 -> 208 x 208 x 32 0.177 BFLOPs 3 conv 64 3 x 3 / 1 208 x 208 x 32 -> 208 x 208 x 64 1.595 BFLOPs 4 res 1 208 x 208 x 64 -> 208 x 208 x 64 5 conv 128 3 x 3 / 2 208 x 208 x 64 -> 104 x 104 x 128 1.595 BFLOPs 6 conv 64 1 x 1 / 1 104 x 104 x 128 -> 104 x 104 x 64 0.177 BFLOPs 7 conv 128 3 x 3 / 1 104 x 104 x 64 -> 104 x 104 x 128 1.595 BFLOPs 8 res 5 104 x 104 x 128 -> 104 x 104 x 128 9 conv 64 1 x 1 / 1 104 x 104 x 128 -> 104 x 104 x 64 0.177 BFLOPs 10 conv 128 3 x 3 / 1 104 x 104 x 64 -> 104 x 104 x 128 1.595 BFLOPs 11 res 8 104 x 104 x 128 -> 104 x 104 x 128 12 conv 256 3 x 3 / 2 104 x 104 x 128 -> 52 x 52 x 256 1.595 BFLOPs 13 conv 128 1 x 1 / 1 52 x 52 x 256 -> 52 x 52 x 128 0.177 BFLOPs 14 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256 1.595 BFLOPs 15 res 12 52 x 52 x 256 -> 52 x 52 x 256 16 conv 128 1 x 1 / 1 52 x 52 x 256 -> 52 x 52 x 128 0.177 BFLOPs 17 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256 1.595 BFLOPs 18 res 15 52 x 52 x 256 -> 52 x 52 x 256 19 conv 128 1 x 1 / 1 52 x 52 x 256 -> 52 x 52 x 128 0.177 BFLOPs 20 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256 1.595 BFLOPs 21 res 18 52 x 52 x 256 -> 52 x 52 x 256 22 conv 128 1 x 1 / 1 52 x 52 x 256 -> 52 x 52 x 128 0.177 BFLOPs 23 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256 1.595 BFLOPs 24 res 21 52 x 52 x 256 -> 52 x 52 x 256 25 conv 128 1 x 1 / 1 52 x 52 x 256 -> 52 x 52 x 128 0.177 BFLOPs 26 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256 1.595 BFLOPs 27 res 24 52 x 52 x 256 -> 52 x 52 x 256 28 conv 128 1 x 1 / 1 52 x 52 x 256 -> 52 x 52 x 128 0.177 BFLOPs 29 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256 1.595 BFLOPs 30 res 27 52 x 52 x 256 -> 52 x 52 x 256 31 conv 128 1 x 1 / 1 52 x 52 x 256 -> 52 x 52 x 128 0.177 BFLOPs 32 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256 1.595 BFLOPs 33 res 30 52 x 52 x 256 -> 52 x 52 x 256 34 conv 128 1 x 1 / 1 52 x 52 x 256 -> 52 x 52 x 128 0.177 BFLOPs 35 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256 1.595 BFLOPs 36 res 33 52 x 52 x 256 -> 52 x 52 x 256 37 conv 512 3 x 3 / 2 52 x 52 x 256 -> 26 x 26 x 512 1.595 BFLOPs 38 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256 0.177 BFLOPs 39 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 1.595 BFLOPs 40 res 37 26 x 26 x 512 -> 26 x 26 x 512 41 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256 0.177 BFLOPs 42 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 1.595 BFLOPs 43 res 40 26 x 26 x 512 -> 26 x 26 x 512 44 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256 0.177 BFLOPs 45 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 1.595 BFLOPs 46 res 43 26 x 26 x 512 -> 26 x 26 x 512 47 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256 0.177 BFLOPs 48 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 1.595 BFLOPs 49 res 46 26 x 26 x 512 -> 26 x 26 x 512 50 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256 0.177 BFLOPs 51 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 1.595 BFLOPs 52 res 49 26 x 26 x 512 -> 26 x 26 x 512 53 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256 0.177 BFLOPs 54 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 1.595 BFLOPs 55 res 52 26 x 26 x 512 -> 26 x 26 x 512 56 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256 0.177 BFLOPs 57 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 1.595 BFLOPs 58 res 55 26 x 26 x 512 -> 26 x 26 x 512 59 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256 0.177 BFLOPs 60 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 1.595 BFLOPs 61 res 58 26 x 26 x 512 -> 26 x 26 x 512 62 conv 1024 3 x 3 / 2 26 x 26 x 512 -> 13 x 13 x1024 1.595 BFLOPs 63 conv 512 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 512 0.177 BFLOPs 64 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024 1.595 BFLOPs 65 res 62 13 x 13 x1024 -> 13 x 13 x1024 66 conv 512 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 512 0.177 BFLOPs 67 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024 1.595 BFLOPs 68 res 65 13 x 13 x1024 -> 13 x 13 x1024 69 conv 512 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 512 0.177 BFLOPs 70 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024 1.595 BFLOPs 71 res 68 13 x 13 x1024 -> 13 x 13 x1024 72 conv 512 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 512 0.177 BFLOPs 73 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024 1.595 BFLOPs 74 res 71 13 x 13 x1024 -> 13 x 13 x1024 75 conv 512 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 512 0.177 BFLOPs 76 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024 1.595 BFLOPs 77 conv 512 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 512 0.177 BFLOPs 78 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024 1.595 BFLOPs 79 conv 512 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 512 0.177 BFLOPs 80 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024 1.595 BFLOPs 81 conv 255 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 255 0.088 BFLOPs 82 detection 83 route 79 84 conv 256 1 x 1 / 1 13 x 13 x 512 -> 13 x 13 x 256 0.044 BFLOPs 85 upsample 2x 13 x 13 x 256 -> 26 x 26 x 256 86 route 85 61 87 conv 256 1 x 1 / 1 26 x 26 x 768 -> 26 x 26 x 256 0.266 BFLOPs 88 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 1.595 BFLOPs 89 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256 0.177 BFLOPs 90 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 1.595 BFLOPs 91 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256 0.177 BFLOPs 92 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 1.595 BFLOPs 93 conv 255 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 255 0.177 BFLOPs 94 detection 95 route 91 96 conv 128 1 x 1 / 1 26 x 26 x 256 -> 26 x 26 x 128 0.044 BFLOPs 97 upsample 2x 26 x 26 x 128 -> 52 x 52 x 128 98 route 97 36 99 conv 128 1 x 1 / 1 52 x 52 x 384 -> 52 x 52 x 128 0.266 BFLOPs 100 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256 1.595 BFLOPs 101 conv 128 1 x 1 / 1 52 x 52 x 256 -> 52 x 52 x 128 0.177 BFLOPs 102 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256 1.595 BFLOPs 103 conv 128 1 x 1 / 1 52 x 52 x 256 -> 52 x 52 x 128 0.177 BFLOPs 104 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256 1.595 BFLOPs 105 conv 255 1 x 1 / 1 52 x 52 x 256 -> 52 x 52 x 255 0.353 BFLOPs 106 detection Loading weights from /root/catkin_ws/src/darknet_ros/darknet_ros/yolo_network_config/weights/yolov3.weights...Done! Loading weights from /root/catkin_ws/src/darknet_ros/darknet_ros/yolo_network_config/weights/yolov3.weights...Done! [New Thread 0x7fff415ff700 (LWP 17397)] Waiting for image. [tcsetpgrp failed in terminal_inferior: Inappropriate ioctl for device] [New Thread 0x7fff40dfe700 (LWP 17398)] [New Thread 0x7fff3bfff700 (LWP 17399)] [New Thread 0x7fff337fe700 (LWP 17400)] [New Thread 0x7fff3b7fe700 (LWP 17401)] [New Thread 0x7fff3affd700 (LWP 17402)] [New Thread 0x7fff3a7fc700 (LWP 17403)] [New Thread 0x7fff39ffb700 (LWP 17404)] [New Thread 0x7fff397fa700 (LWP 17405)] [New Thread 0x7fff38ff9700 (LWP 17406)] [New Thread 0x7fff33fff700 (LWP 17407)] [New Thread 0x7fff32ffd700 (LWP 17408)] [Thread 0x7fff33fff700 (LWP 17407) exited] person: 96% bench: 76% refrigerator: 56% refrigerator: 52% chair: 49% bottle: 36%

    Thread 20 "darknet_ros" received signal SIGSEGV, Segmentation fault. [Switching to Thread 0x7fff32ffd700 (LWP 17408)] darknet_ros::YoloObjectDetector::detectInThread (this=0x7fffffffcff0) at /root/catkin_ws/src/darknet_ros/darknet_ros/src/YoloObjectDetector.cpp:373 ---Type to continue, or q to quit--- — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub, or mute the thread.

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  • weixin_39797693 weixin_39797693 5月前

    Yes, it seems. If I type return to continue I get nothing more than 373 if (dets[i].prob[j]) {. Please note however that I am running it within a Docker container. Maybe this could be an issue? Or maybe a missing runtime dependency?

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  • weixin_39950081 weixin_39950081 5月前

    I do not have much experience with Docker. But this might be an issue. But if you use the yolo v2 network, it does not crash, right? I try to check if can provoke the same segfault.

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  • weixin_39950081 weixin_39950081 5月前

    I updated master. Can you please check if this fixes your issue? Please also check the yolo v2 network. Thanks!

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  • weixin_39797693 weixin_39797693 5月前

    : Thank you for your amazing support. I confirmed that Yolo v3 is no more crashing while v2 is still perfectly working, both locally or within a Docker container. Great!

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  • weixin_39950081 weixin_39950081 5月前

    : thanks for spotting the bug and checking that all works on your machine.

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