When I roslaunch darknet_ros yolo_v3.launch I get this :
`/
darknet_ros (darknet_ros/darknet_ros)
ROS_MASTER_URI=http://localhost:11311
process[darknet_ros-1]: started with pid [17269]
[ INFO] [1673750946.743184246]: [YoloObjectDetector] Node started.
[ INFO] [1673750946.749640549]: [YoloObjectDetector] Xserver is running.
[ INFO] [1673750946.752220959]: [YoloObjectDetector] init().
YOLO V3
layer filters size input output
0 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 yolo
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 yolo
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 yolo
Loading weights from /home/philip/obj_ws/src/darknet_ros/darknet_ros/yolo_network_config/weights/yolov3.weights...Done!
Waiting for image.
[darknet_ros-1] process has died [pid 17269, exit code -11, cmd /home/philip/obj_ws/devel/lib/darknet_ros/darknet_ros camera/rgb/image_raw:=wam_v/front/image_raw __name:=darknet_ros __log:=/home/philip/.ros/log/c81dc520-947e-11ed-8da9-d43b04207196/darknet_ros-1.log].
log file: /home/philip/.ros/log/c81dc520-947e-11ed-8da9-d43b04207196/darknet_ros-1*.log
all processes on machine have died, roslaunch will exit
shutting down processing monitor...
... shutting down processing monitor complete
done`
I assume this must have something to do with the camera topic which in this case is wam_v\front\image_raw. This topic is what I have for my image topic in my launch file, and I know data is being published t this topic. I also tried rosnode info darknet_ros:
Node [/darknet_ros]
Publications:
* /darknet_ros/bounding_boxes [darknet_ros_msgs/BoundingBoxes]
* /darknet_ros/check_for_objects/feedback [darknet_ros_msgs/CheckForObjectsActionFeedback]
* /darknet_ros/check_for_objects/result [darknet_ros_msgs/CheckForObjectsActionResult]
* /darknet_ros/check_for_objects/status [actionlib_msgs/GoalStatusArray]
* /darknet_ros/detection_image [sensor_msgs/Image]
* /darknet_ros/found_object [darknet_ros_msgs/ObjectCount]
* /rosout [rosgraph_msgs/Log]
Subscriptions:
* /clock [rosgraph_msgs/Clock]
* /darknet_ros/check_for_objects/cancel [unknown type]
* /darknet_ros/check_for_objects/goal [unknown type]
* /wam_v/front/image_raw [sensor_msgs/Image]
Services:
* /darknet_ros/get_loggers
* /darknet_ros/set_logger_level
contacting node http://localhost:39865/ ...
Pid: 17766
Connections:
* topic: /rosout
* to: /rosout
* direction: outbound (51267 - 127.0.0.1:59632) [14]
* transport: TCPROS
* topic: /clock
* to: /gazebo (http://localhost:39329/)
* direction: inbound (56290 - localhost:48481) [13]
* transport: TCPROS
* topic: /wam_v/front/image_raw
* to: /gazebo (http://localhost:39329/)
* direction: inbound (40672 - localhost:48481) [12]
* transport: TCPROS
It seems the camera topic is being subscribed to. I'm not sure what going on.
I try catkin_make -DCMAKE_BUILD_TYPE=Debug:
I get ......
[ 98%] Linking CXX shared library /home/philip/obj_ws/devel/lib/libdarknet_ros_lib.so
[ 98%] Built target darknet_ros_lib
[ 98%] Building CXX object darknet_ros/darknet_ros/CMakeFiles/darknet_ros.dir/src/yolo_object_detector_node.cpp.o
In file included from /home/philip/obj_ws/src/darknet_ros/darknet_ros/include/darknet_ros/YoloObjectDetector.hpp:56:0,
from /home/philip/obj_ws/src/darknet_ros/darknet_ros/src/yolo_object_detector_node.cpp:9:
/home/philip/obj_ws/src/darknet_ros/darknet_ros/include/darknet_ros/image_interface.h:15:14: warning: ‘float get_pixel(image, int, int, int)’ declared ‘static’ but never defined [-Wunused-function]
static float get_pixel(image m, int x, int y, int c);
^~~~~~~~~
[100%] Linking CXX executable /home/philip/obj_ws/devel/lib/darknet_ros/darknet_ros
/home/philip/obj_ws/devel/lib/libdarknet_ros_lib.so: undefined reference to `cv::VideoCapture::VideoCapture(int)'
/home/philip/obj_ws/devel/lib/libdarknet_ros_lib.so: undefined reference to `cv::VideoCapture::VideoCapture(cv::String const&)'
collect2: error: ld returned 1 exit status
darknet_ros/darknet_ros/CMakeFiles/darknet_ros.dir/build.make:173: recipe for target '/home/philip/obj_ws/devel/lib/darknet_ros/darknet_ros' failed
make[2]: *** [/home/philip/obj_ws/devel/lib/darknet_ros/darknet_ros] Error 1
CMakeFiles/Makefile2:2048: recipe for target 'darknet_ros/darknet_ros/CMakeFiles/darknet_ros.dir/all' failed
make[1]: *** [darknet_ros/darknet_ros/CMakeFiles/darknet_ros.dir/all] Error 2
Makefile:145: recipe for target 'all' failed
make: *** [all] Error 2
Invoking "make -j12 -l12" failed
This is solved now, I had to attach linker flags or something. Here's a snippet how to change your CMakeLists.txt for the darknet_ros package. Mind that I'm using openCV 3.2.0 without CUDA.
.........
if (CUDA_FOUND)
link_directories(
${CUDA_TOOLKIT_ROOT_DIR}/lib
)
cuda_add_library(${PROJECT_NAME}_lib
${PROJECT_LIB_FILES} ${DARKNET_CORE_FILES}
${DARKNET_CUDA_FILES}
)
target_link_libraries(${PROJECT_NAME}_lib
cuda
cudart
cublas
curand
)
cuda_add_executable(${PROJECT_NAME}
src/yolo_object_detector_node.cpp
)
else()
add_library(${PROJECT_NAME}_lib
${PROJECT_LIB_FILES} ${DARKNET_CORE_FILES}
)
execute_process(COMMAND pkg-config --libs opencv
OUTPUT_VARIABLE OpenCV_LIBS
OUTPUT_STRIP_TRAILING_WHITESPACE)
target_link_libraries(${PROJECT_NAME}_lib ${OpenCV_LIBRARIES} ${Boost_LIBRARIES} ${X11_LIBRARIES})
add_executable(${PROJECT_NAME}
src/yolo_object_detector_node.cpp
)
endif()
..........