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[feature] Initial release of Yolo v3 node #1202

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Apr 9, 2018
Merged

[feature] Initial release of Yolo v3 node #1202

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63b2441
Initial release of Yolo v3 node
amc-nu Apr 6, 2018
57b350a
Added extra documentation
amc-nu Apr 6, 2018
925f467
* Missing header include
amc-nu Apr 9, 2018
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41 changes: 18 additions & 23 deletions ros/src/computing/perception/detection/packages/cv_tracker/launch/yolo2.launch
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@@ -1,26 +1,21 @@
<launch>
<arg name="car" default="true"/>
<arg name="pedestrian" default="false"/>
<arg name="use_gpu" default="true"/>
<arg name="gpu_device_id" default="0"/>
<arg name="score_threshold" default="0.3"/>

<!-- arguments list -->

<arg name="network_definition_file" default="$(env HOME)/darknet/cfg/yolo.cfg"/>
<arg name="pretrained_model_file" default="$(env HOME)/darknet/data/yolo.weights"/>
<arg name="gpu_device_id" default="0"/>
<arg name="score_threshold" default="0.3"/>
<arg name="nms_threshold" default="0.45"/>

<arg name="network_definition_file" default="$(env HOME)/darknet/cfg/yolo.cfg"/>
<arg name="pretrained_model_file" default="$(env HOME)/darknet/data/yolo.weights"/>

<arg name="camera_id" default="/"/>
<arg name="image_src" default="/image_raw"/>

<node pkg="cv_tracker" name="yolo2_wa" type="yolo2_wa">
<param name="network_definition_file" type="str" value="$(arg network_definition_file)"/>
<param name="pretrained_model_file" type="str" value="$(arg pretrained_model_file)"/>
<param name="score_threshold" type="double" value="$(arg score_threshold)"/>
<param name="nms_threshold" type="double" value="$(arg nms_threshold)"/>
<param name="gpu_device_id" type="int" value="$(arg gpu_device_id)"/>
<param name="image_raw_node" type="str" value="$(arg camera_id)$(arg image_src)"/>
</node>

<arg name="camera_id" default="/" />
<arg name="image_src" default="/image_raw"/>

<!-- SSD -->
<node pkg="cv_tracker" name="yolo2_wa" type="yolo2_wa">
<param name="network_definition_file" type="str" value="$(arg network_definition_file)"/>
<param name="pretrained_model_file" type="str" value="$(arg pretrained_model_file)"/>
<param name="use_gpu" type="bool" value="$(arg use_gpu)" />
<param name="score_threshold" type="double" value="$(arg score_threshold)"/>
<param name="gpu_device_id" type="int" value="$(arg gpu_device_id)"/>
<param name="image_raw_node" type="str" value="$(arg camera_id)$(arg image_src)"/>
</node>

</launch>
2 changes: 1 addition & 1 deletion ros/src/computing/perception/detection/packages/cv_tracker/nodes/yolo2/src/yolo2_node.cpp
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Expand Up @@ -191,7 +191,7 @@ class Yolo2DetectorNode
void image_callback(const sensor_msgs::ImageConstPtr& in_image_message)
{
std::vector< RectClassScore<float> > detections;
//darknet_image = yolo_detector_.convert_image(in_image_message);
//darknet_image_ = yolo_detector_.convert_image(in_image_message);

darknet_image = convert_ipl_to_image(in_image_message);

Expand Down
154 changes: 154 additions & 0 deletions ros/src/computing/perception/detection/packages/yolo3_detector/CMakeLists.txt
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@@ -0,0 +1,154 @@
cmake_minimum_required(VERSION 2.8.12)
project(yolo3_detector)

find_package(catkin REQUIRED COMPONENTS
cv_bridge
image_transport
roscpp
sensor_msgs
std_msgs
autoware_msgs
)

find_package(CUDA)
find_package(OpenCV REQUIRED)
find_package(OpenMP)

catkin_package(CATKIN_DEPENDS
cv_bridge
image_transport
roscpp
sensor_msgs
std_msgs
autoware_msgs
)

set(CMAKE_CXX_FLAGS "-std=c++11 -O3 -g -Wall ${CMAKE_CXX_FLAGS}")

IF (CUDA_FOUND)
list(APPEND CUDA_NVCC_FLAGS "--std=c++11 -I$${PROJECT_SOURCE_DIR}/darknet/src -I${PROJECT_SOURCE_DIR}/src -DGPU")
SET(CUDA_PROPAGATE_HOST_FLAGS OFF)

#darknet
cuda_add_library(yolo3_detector_lib SHARED
darknet/src/activation_kernels.cu
darknet/src/avgpool_layer_kernels.cu
darknet/src/convolutional_kernels.cu
darknet/src/crop_layer_kernels.cu
darknet/src/col2im_kernels.cu
darknet/src/blas_kernels.cu
darknet/src/deconvolutional_kernels.cu
darknet/src/dropout_layer_kernels.cu
darknet/src/im2col_kernels.cu
darknet/src/maxpool_layer_kernels.cu

darknet/src/gemm.c
darknet/src/utils.c
darknet/src/cuda.c
darknet/src/deconvolutional_layer.c
darknet/src/convolutional_layer.c
darknet/src/list.c
darknet/src/image.c
darknet/src/activations.c
darknet/src/im2col.c
darknet/src/col2im.c
darknet/src/blas.c
darknet/src/crop_layer.c
darknet/src/dropout_layer.c
darknet/src/maxpool_layer.c
darknet/src/softmax_layer.c
darknet/src/data.c
darknet/src/matrix.c
darknet/src/network.c
darknet/src/connected_layer.c
darknet/src/cost_layer.c
darknet/src/parser.c
darknet/src/option_list.c
darknet/src/detection_layer.c
darknet/src/route_layer.c
darknet/src/upsample_layer.c
darknet/src/box.c
darknet/src/normalization_layer.c
darknet/src/avgpool_layer.c
darknet/src/layer.c
darknet/src/local_layer.c
darknet/src/shortcut_layer.c
darknet/src/logistic_layer.c
darknet/src/activation_layer.c
darknet/src/rnn_layer.c
darknet/src/gru_layer.c
darknet/src/crnn_layer.c
darknet/src/batchnorm_layer.c
darknet/src/region_layer.c
darknet/src/reorg_layer.c
darknet/src/tree.c
darknet/src/lstm_layer.c
darknet/src/l2norm_layer.c
darknet/src/yolo_layer.c
)

target_compile_definitions(yolo3_detector_lib PUBLIC -DGPU)
cuda_add_cublas_to_target(yolo3_detector_lib)

if (OPENMP_FOUND)
set_target_properties(yolo3_detector_lib PROPERTIES
COMPILE_FLAGS ${OpenMP_CXX_FLAGS}
LINK_FLAGS ${OpenMP_CXX_FLAGS}
)
endif ()

target_include_directories(yolo3_detector_lib PRIVATE
${OpenCV_INCLUDE_DIR}
${catkin_INCLUDE_DIRS}
${Boost_INCLUDE_DIRS}
${CUDA_INCLUDE_DIRS}
${PROJECT_SOURCE_DIR}/darknet
${PROJECT_SOURCE_DIR}/darknet/src
${PROJECT_SOURCE_DIR}/src
)

target_link_libraries(yolo3_detector_lib
${OpenCV_LIBRARIES}
${catkin_LIBRARIES}
${PCL_LIBRARIES}
${Qt5Core_LIBRARIES}
${CUDA_LIBRARIES}
${CUDA_CUBLAS_LIBRARIES}
${CUDA_curand_LIBRARY}
)

add_dependencies(yolo3_detector_lib
${catkin_EXPORTED_TARGETS}
)

#ros node
cuda_add_executable(yolo3_detector
src/yolo3_node.cpp
src/yolo3_detector.cpp
src/yolo3_detector.h
)

target_compile_definitions(yolo3_detector PUBLIC -DGPU)

target_include_directories(yolo3_detector PRIVATE
${CUDA_INCLUDE_DIRS}
${catkin_INCLUDE_DIRS}
${PROJECT_SOURCE_DIR}/darknet
${PROJECT_SOURCE_DIR}/darknet/src
${PROJECT_SOURCE_DIR}/src
)

target_link_libraries(yolo3_detector
${catkin_LIBRARIES}
${OpenCV_LIBS}
${CUDA_LIBRARIES}
${CUDA_CUBLAS_LIBRARIES}
${CUDA_curand_LIBRARY}
yolo3_detector_lib
)
add_dependencies(yolo3_detector
${catkin_EXPORTED_TARGETS}
)
ELSE()
message("YOLO3 won't be built, CUDA was not found.")
ENDIF ()
49 changes: 49 additions & 0 deletions ros/src/computing/perception/detection/packages/yolo3_detector/README.md
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# Yolo3 Detector

Autoware package based on Yolov3 image detector.

### Requirements

* NVIDIA GPU with CUDA installed
* Pretrained YOLOv3 model on COCO dataset.

### How to launch

* From a sourced terminal:

`roslaunch yolo3_detector yolo3.launch`

* From Runtime Manager:

Computing Tab -> Detection/ cv_detector -> `yolo3_wa`

### Parameters

Launch file available parameters:

|Parameter| Type| Description|
----------|-----|--------
|`score_threshold`|*Double* |Detections with a confidence value larger than this value will be displayed. Default `0.5`.|
|`nms_threshold`|*Double*|Non-Maximum suppresion area threshold ratio to merge proposals. Default `0.45`.|
|`network_definition_file`|*String*|Network architecture definition configuration file. Default `yolov3.cfg`.|
|`pretrained_model_file`|*String*|Path to pretrained model. Default `yolov3.weights`.|
|`camera_id`|*String*|Camera workspace. Default `/`.|
|`image_src`|*String*|Image source topic. Default `/image_raw`.|

### Subscribed topics

|Topic|Type|Objective|
------|----|---------
|`/image_raw`|`sensor_msgs/Image`|Source image stream to perform detection.|
|`/config/Yolo3`|`autoware_msgs/ConfigSsd`|Configuration adjustment for threshold.|

### Published topics

|Topic|Type|Objective|
------|----|---------
|`/obj_car/image_obj`|`autoware_msgs/image_obj`|Contains the coordinates of the bounding box in image coordinates for objects detected as vehicles.|
|`/obj_person/image_obj`|`autoware_msgs/image_obj`|Contains the coordinates of the bounding box in image coordinates for objects detected as pedestrian.|

### Video

[![Yolo v3 Autoware](https://img.youtube.com/vi/pO4vM4ehI98/0.jpg)](https://www.youtube.com/watch?v=pO4vM4ehI98)
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