[feature] Initial release of Yolo v3 node (#1202)

* Initial release of Yolo v3 node * Added extra documentation * * Missing header include
autowarefoundation · Apr 9, 2018 · 962dd47 · 962dd47
1 parent 98b5aa1
commit 962dd47
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diff --git a/ros/src/computing/perception/detection/packages/cv_tracker/launch/yolo2.launch b/ros/src/computing/perception/detection/packages/cv_tracker/launch/yolo2.launch
@@ -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>
diff --git a/ros/src/computing/perception/detection/packages/cv_tracker/nodes/yolo2/src/yolo2_node.cpp b/ros/src/computing/perception/detection/packages/cv_tracker/nodes/yolo2/src/yolo2_node.cpp
@@ -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);
 

diff --git a/ros/src/computing/perception/detection/packages/yolo3_detector/CMakeLists.txt b/ros/src/computing/perception/detection/packages/yolo3_detector/CMakeLists.txt
@@ -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 ()
diff --git a/ros/src/computing/perception/detection/packages/yolo3_detector/README.md b/ros/src/computing/perception/detection/packages/yolo3_detector/README.md
@@ -0,0 +1,49 @@
+# 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)