Update 'README.md'

git-subtree-dir: ros2_ws/src/perception_pcl
git-subtree-mainline: 0c9504b343
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README.md

@@ -1,3 +1,244 @@
 # greenhouse
 
-This repository contains code for detecting heat pipes in the greenhouse as well as estimating the pose of the pipes
+This repository contains code for detecting heat pipes in the greenhouse as well as estimating the pose of the pipes.
+
+Platform: ROS 2, Humble, Ubuntu 22.04
+
+## How to install dependencies??
+- Install `git`
+```
+sudo apt install git
+```
+- Install `ROS 2 Humble` on `Ubuntu 22.04` by following https://docs.ros.org/en/foxy/Installation/Ubuntu-Install-Debians.html
+- Install `colcon build` by following https://docs.ros.org/en/foxy/Tutorials/Beginner-CLI-Tools/Configuring-ROS2-Environment.html
+```
+sudo apt install python3-colcon-common-extensions
+```
+- Instal `pip` for python packages
+```
+sudo apt install python3-pip
+```
+- Now clone the repository
+```
+git clone https://tea.der-space.de/apoorva/greenhouse.git
+```
+- Install `ultralytics` for yolov3 package
+```
+pip install ultralytics
+```
+- For `yolov3_ros`, there are a bunch of other requirements. Go to `yolov3` folder and install using following commands:
+```
+cd ~/greenhouse/yolov3
+pip install -r requirements.txt
+```
+- Go to `ros2_ws` inside `greenhouse`. Make sure you only have `src` folder.
+```
+cd ~/greenhouse/ros2_ws
+ls
+src
+```
+- Inside `ros2_ws` folder, start building individual packages in the below sequence to avoid errors.
+```
+colcon build --packages-select pipe_msgs
+colcon build --packages-select pcl_ros
+colcon build --allow-overriding pcl_ros
+colcon build --packages-select pcl_conversions
+colcon build --allow-overriding pcl_conversions
+colcon build --packages-select find-pose
+colcon build --packages-select yolov3_ros
+. install/setup.bash
+```
+- The code should be ready to launch as explained in [How to run Live Detection?](#how-to-run-live-detection)
+This section explains what each module is responsible for.
+## perception_pcl
+This module is responsible for providing `pcl_conversions` and `pcl_ros` modules in `ros 2`.
+To build, run the following command:
+```
+cd ros2_ws/
+colcon build --packages-select perception_pcl
+. install/setup.bash
+```
+
+## pipe_msgs
+This module contains ros msgs for storing information about the detected object's bounding box.
+```
+cd ros2_ws/
+colcon build --packages-select pipe_msgs
+. install/setup.bash
+```
+To check if msgs are built properly, run following command
+```
+ros2 interface show pipe_msgs/msg/BoundingBox
+```
+The output will be:
+float64 probability
+int64 xmin
+int64 ymin
+int64 xmax
+int64 ymax
+int16 id
+string class_id
+
+
+## find-pose
+This ROS module is responsible for determining the position of the detected objects.
+The following input/ros topics are needed:
+- /rgb_img: RGB Image topic
+- /camera_info: Camera calibration parameters topic
+- /depth_img: Aligned depth image topic (aligned with rgb image)
+- /bboxes: Bounding box of each detected object. (Comes from yolov3 detection module)
+Output:
+- TF: Transform between camera_link and detected_object frame.
+How to build and run?
+This package is dependent on custom `pcl_conversion` and `pcl_ros` module. Make sure you have built those before building this package.
+```
+colcon build --packages-select find-pose
+. install/setup.bash
+ros2 launch find-pose find-pose-node.launch.py
+```
+All the topics can be remapped in the launch file.
+
+## yolov3_ros
+This ROS module is responsible for detecting the pipes from rgb image topic and also syncing the depth, rgb and camera_info topics.
+The following input/ros topics are needed:
+- /camera/color/image_raw: RGB Image topic
+- /camera/aligned_depth_to_color/image_raw: Aligned depth image topic (aligned with rgb image)
+- /camera/color/camera_info: Camera calibration parameters topic
+
+ROS Paramater Input:
+- best_weights: String that is the path to the best weights file of yolov3 detection
+Defaults: `'src/pipe_weights.pt'` inside `ros2_ws` folder
+
+The following are the output topics:
+- /detection_image: The RGB Image topic with bounding box drawn on it for visualization and debugging purpose
+- /bboxes: Bounding box of each detected object.
+- /rgb_img: Time Synced RGB Image topic
+- /camera_info: Time Synced Camera calibration parameters topic
+- /depth_img: Time Synced Aligned depth image topic (aligned with rgb image)
+
+How to build and run?
+```
+colcon build --packages-select yolov3_ros
+. install/setup.bash
+cd greenhouse/ros2_ws/
+ros2 launch yolov3_ros pipe_detection.launch.py
+```
+All the topics can be remapped in the launch file. The path to best_weights can also be changed inside the launch file.
+Launch file is stored in `yolov3_ros/launch/`.
+
+## yolov3
+This module contains code for yolov3. This method is being used to train the model to detect pipes in the greenhouse.
+- Ros bag was converted from ros 1 to ros 2 using rosbags module
+- Ros 2 bag was played, convert_2_img was used to subscribe to images and all the images were saved as .jpeg in a folder.
+- Images were labeled used labelImg.
+- Create a `custom-yolov3.yaml` file that has information about number of classes, location for labels,images.
+
+- Used google colab to run the yolov3 training.
+- Upload the label and images to drive and Mount the google drive in python notebook
+```
+from google.colab import drive
+drive.mount("/content/gdrive")
+```
+- Upload the yolov3 code and cd into the location of code
+```
+cd /content/gdrive/MyDrive/yolov3
+```
+- Run the training script
+```
+!python train.py --img 1280 --batch 16 --epochs 300 --data data/custom-yolov3.yaml --weights '' --cfg yolov3.yaml
+```
+- Important to note that we are not using any pre-trained weights.
+- Once training is finished, a `run` folder is created with exp number that stores the best weights (a .pt file).
+- This file is then used by detection to node to detect on new data. Update the image path and weights path to run detection.
+```
+!python detect.py --img 1280 --source ../pipe-dataset/validate/images/stereo_image103.jpeg --weights runs/train/exp14/weights/best.pt
+```
+- Once detect.py is finished, it create a new folder called `detect` inside `runs` folder that store the image with bounding box of detected object.
+More details: https://github.com/ultralytics/yolov3
+
+## convert_2_img
+This ROS module converts the rosbag data to images for yolo training purpose etc.
+- Make sure you have this module inside a ros workspace.
+- Create folder called `stereo` inside convert_2_img module.
+- Run following command to launch the node. Currently, this node listens for `/camera/color/image_raw` topic.
+```
+cd ros2_ws/src/convert_2_img
+python3 convert_2_img/convert_to_img.py
+```
+- Play the rosbag in another terminal
+```
+ros2 bag play bag/bag.db
+```
+- Once bag has finished playing, the images will be stored inside `stereo` folder.
+
+## labelImg
+This module is used to label images for yolo. The pre-defined custom classes file was changed to use new labels. This file is stored in `cd labelImg/data/predefined_classes.txt`
+To launch the gui, run
+```
+cd labelImg
+python3 labelImg.py 
+```
+More details: https://github.com/heartexlabs/labelImg
+
+## rosbags
+This module convert rosbags from ros 1 to ros 2. 
+```
+git clone https://gitlab.com/ternaris/rosbags.git
+cd rosbags
+python -m venv venv
+. venv/bin/activate
+
+pip install -r requirements-dev.txt
+pip install -e .
+
+rosbags-convert ../single_depth_color_640x480.bag
+```
+
+## flann_based
+Module that uses 3D model of the pipe to estimate pose. This method was not successful.
+
+## yolov7
+This module contains code for yolov7. This method was too heavy and didn't produce great results for detection.
+
+## darknet_ros2
+This module was provides interface to run neural network as rosnodes. The purpose was to use yolo model as ros node but this method was not successful
+
+## darknet_vendor
+This module was needed to build darknet_ros2.
+
+# How to run live detection?
+Once you have succefully built the ROS Modules specifically, `yolov3_ros` and `find-pose` along with dependencies like `pipe_msgs` and `perception_ros`, `perception_pcl`,you can do the following: 
+Assumption:
+You have the following required data in forms of ros topic:
+- /camera/color/image_raw: RGB Image topic
+- /camera/aligned_depth_to_color/image_raw: Aligned depth image topic (aligned with rgb image)
+- /camera/color/camera_info: Camera calibration parameters topic
+How do you get this data?
+- This data can come from a pre recorded Rosbag. If this is the case, do following:
+```
+ros2 bag play bag-folder/bag-name.db3
+```
+- This data can come directly from camera's (D455/ZED2I) ROS Node: Launch your node in a terminal. 
+- If your camera topics have different names than the default topic names mentioned above, update/remap ONLY the `pipe_detection.launch.py` script stored in `ros2_ws/src/yolov3_ros/launch` folder.
+- Once you have updated the launch file, build the code again using `colcon build --packages-select yolov3_ros` and proceedas mentioned below.
+
+Steps to run:
+- Open a terminal.
+- Run `$ cd greenhouse/ros2_ws/` and `$ . install/setup.bash`.
+- Launch node for object detection:
+```
+ros2 launch yolov3_ros pipe_detection.launch.py
+```
+- This node will output two topics: `/bboxes` and `/detection_image`.
+- Make sure that you run this launch file from `greenhouse/ros2_ws/` folder since the path of weights is relative (`/src/pipe_weights.pt`) inside the launch file.
+- Launch node for pose estimation:
+```
+ros2 launch find-pose find-pose-node.launch.py
+```
+- This node will output TF topics between `/camera_link` and `/${detected_object_name}`.
+- Open RVIZ by running `$ rviz2`. Change `fixed frame` from `map` to `camera_link`.
+    - Go to `Add` button. Under `By Display type`, select `tf`. Once tf is added, select required frames like `camera_link` and `l_trail` to see the tfs.
+    - To see the current image with detected object, Go to `Add` Button. Under `By Topic`, select topci called `detection_image`.
+    -You can add other topics as per the need and topic names. 
+- You can open launch files to update/remap topic name if different camera is being used. 
+- You can also update ros parameter from launch file. Currently, the `pipe_weights.pt` file is the one used. This file can be changed and you can update the parameter name `best_weights` inside the `pipe_detection.launch.py` file.

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flann_based/build/cpp/example_cmake/CMakeFiles/opencv_example.dir/progress.make

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flann_based/build/cpp/example_cmake/CMakeFiles/progress.marks

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flann_based/build/cpp/example_cmake/cmake_install.cmake

@@ -1,44 +0,0 @@
-# Install script for directory: /media/psf/freelancing/greenhouse/flann_based/cpp/example_cmake
-
-# Set the install prefix
-if(NOT DEFINED CMAKE_INSTALL_PREFIX)
-  set(CMAKE_INSTALL_PREFIX "/usr/local")
-endif()
-string(REGEX REPLACE "/$" "" CMAKE_INSTALL_PREFIX "${CMAKE_INSTALL_PREFIX}")
-
-# Set the install configuration name.
-if(NOT DEFINED CMAKE_INSTALL_CONFIG_NAME)
-  if(BUILD_TYPE)
-    string(REGEX REPLACE "^[^A-Za-z0-9_]+" ""
-           CMAKE_INSTALL_CONFIG_NAME "${BUILD_TYPE}")
-  else()
-    set(CMAKE_INSTALL_CONFIG_NAME "")
-  endif()
-  message(STATUS "Install configuration: \"${CMAKE_INSTALL_CONFIG_NAME}\"")
-endif()
-
-# Set the component getting installed.
-if(NOT CMAKE_INSTALL_COMPONENT)
-  if(COMPONENT)
-    message(STATUS "Install component: \"${COMPONENT}\"")
-    set(CMAKE_INSTALL_COMPONENT "${COMPONENT}")
-  else()
-    set(CMAKE_INSTALL_COMPONENT)
-  endif()
-endif()
-
-# Install shared libraries without execute permission?
-if(NOT DEFINED CMAKE_INSTALL_SO_NO_EXE)
-  set(CMAKE_INSTALL_SO_NO_EXE "1")
-endif()
-
-# Is this installation the result of a crosscompile?
-if(NOT DEFINED CMAKE_CROSSCOMPILING)
-  set(CMAKE_CROSSCOMPILING "FALSE")
-endif()
-
-# Set default install directory permissions.
-if(NOT DEFINED CMAKE_OBJDUMP)
-  set(CMAKE_OBJDUMP "/usr/bin/objdump")
-endif()
-

ros2_ws/src/convert_2_img/convert_2_img/convert_to_img.py

@@ -1,25 +1,61 @@
-import rclpy
+#!/usr/bin/env python
-from sensor_msgs.msg import Image
+import os
 import cv2
-import cv_bridge
+from cv_bridge import CvBridge
+from sensor_msgs.msg import Image
+import rclpy
+from rclpy.node import Node
+import threading
 
-count = 0
+class ImageSaver(Node):
-def image_callback(data):
+    def __init__(self):
-    bridge = cv_bridge.CvBridge()
+        super().__init__('image_saver')
-    try:
+        self.depth_sub = self.create_subscription(Image, '/camera/aligned_depth_to_color/image_raw', self.depth_callback, 1)
-        cv_image = bridge.imgmsg_to_cv2(data, "bgr8")
+        self.image_sub = self.create_subscription(Image, '/camera/color/image_raw', self.image_callback, 1)
-    except cv_bridge.CvBridgeError as e:
+        self.cv_bridge = CvBridge()
-        print(e)
+        self.depth_image = None
+        self.color_image = None
+        self.count_stereo = 0
+        self.count_depth = 0
 
-    global count
+    def depth_callback(self, data):
-    cv2.imwrite('stereo_image' + str(count)+ '.jpeg', cv_image)   
+        print("depth cb")
-    count = count + 1
+        self.depth_image = self.cv_bridge.imgmsg_to_cv2(data, desired_encoding="passthrough")
+        self.save_images('d')
 
-def main(args=None):
+
-    rclpy.init(args=args)
+    def image_callback(self, data):
-    node = rclpy.create_node('stereo_image_subscriber')
+        print("image cb")
-    sub = node.create_subscription(Image, '/camera/color/image_raw', image_callback, False)
+        
-    rclpy.spin(node)
+        self.color_image = self.cv_bridge.imgmsg_to_cv2(data)
+        self.save_images('s')
+
+
+    def save_images(self, img_type):
+        print('save images')
+
+        if img_type == 's':
+            filename_stereo = "/stereo/stereo_{}.jpg".format(self.count_stereo)
+            # import pdb; pdb.set_trace()
+            path_stereo = os.getcwd() + filename_stereo
+            cv2.imwrite(path_stereo, self.color_image)
+            self.get_logger().info("Saved image to {}".format(path_stereo))
+            self.count_stereo += 1
+
+        if img_type == 'd':
+            filename_depth = "/depth/depth_{}.jpg".format(self.count_depth)
+            path_depth = os.getcwd() + filename_depth
+            cv2.imwrite(path_depth, self.depth_image)
+            self.get_logger().info("Saved image to {}".format(path_depth))
+            self.count_depth += 1
 
 if __name__ == '__main__':
-    main()
+    rclpy.init()
+    image_saver = ImageSaver()
+    # rate = image_saver.create_rate(1)  # 10 Hz
+    rclpy.spin(image_saver)
+    # while rclpy.ok():
+    #     image_saver.save_images()
+    #     # rate.sleep()
+    # image_saver.destroy_node()
+    # rclpy.shutdown()

ros2_ws/src/darknet_ros2/CMakeLists.txt

@@ -0,0 +1,75 @@
+cmake_minimum_required(VERSION 3.10)
+project(openrobotics_darknet_ros)
+
+# Default to C++14
+if(NOT CMAKE_CXX_STANDARD)
+  set(CMAKE_CXX_STANDARD 14)
+endif()
+
+if(NOT WIN32)
+  add_compile_options(-Wall -Wextra -Wpedantic)
+endif()
+
+find_package(ament_cmake REQUIRED)
+find_package(cv_bridge REQUIRED)
+find_package(darknet_vendor REQUIRED)
+find_package(rclcpp REQUIRED)
+find_package(rclcpp_components REQUIRED)
+find_package(sensor_msgs REQUIRED)
+find_package(vision_msgs REQUIRED)
+
+add_library(openrobotics_darknet_ros SHARED
+  src/detector_network.cpp
+  src/parse.cpp)
+target_include_directories(openrobotics_darknet_ros PUBLIC include)
+target_compile_definitions(openrobotics_darknet_ros PRIVATE "DARKNET_ROS_BUILDING_DLL")
+ament_target_dependencies(openrobotics_darknet_ros
+  cv_bridge
+  darknet_vendor
+  sensor_msgs
+  vision_msgs)
+
+add_library(detector_node SHARED
+  src/detector_node.cpp)
+target_compile_definitions(detector_node PRIVATE "DARKNET_ROS_NODE_BUILDING_DLL")
+ament_target_dependencies(detector_node PUBLIC
+  "rclcpp"
+  "rclcpp_components")
+target_link_libraries(detector_node PUBLIC openrobotics_darknet_ros)
+rclcpp_components_register_nodes(detector_node "openrobotics::darknet_ros::DetectorNode")
+
+add_executable(detector_node_main
+  src/detector_node_main.cpp)
+target_link_libraries(detector_node_main detector_node)
+set_target_properties(detector_node_main PROPERTIES OUTPUT_NAME "detector_node")
+
+if(BUILD_TESTING)
+  find_package(ament_lint_auto REQUIRED)
+  ament_lint_auto_find_test_dependencies()
+
+  ament_add_gtest(test_parser test/test_parser.cpp
+    WORKING_DIRECTORY "${CMAKE_CURRENT_SOURCE_DIR}/test/")
+  target_link_libraries(test_parser openrobotics_darknet_ros)
+
+  ament_add_gtest(test_detector_network test/test_detector_network.cpp)
+  target_link_libraries(test_detector_network openrobotics_darknet_ros)
+endif()
+
+ament_export_libraries(openrobotics_darknet_ros)
+
+install(TARGETS openrobotics_darknet_ros
+  ARCHIVE DESTINATION lib
+  LIBRARY DESTINATION lib
+  RUNTIME DESTINATION bin)
+
+install(TARGETS detector_node
+  ARCHIVE DESTINATION lib
+  LIBRARY DESTINATION lib
+  RUNTIME DESTINATION bin)
+
+install(TARGETS detector_node_main
+  DESTINATION lib/${PROJECT_NAME})
+
+install(DIRECTORY include/ DESTINATION include)
+
+ament_package()

ros2_ws/src/darknet_ros2/CONTRIBUTING.md

@@ -0,0 +1,18 @@
+Any contribution that you make to this repository will
+be under the Apache 2 License, as dictated by that
+[license](http://www.apache.org/licenses/LICENSE-2.0.html):
+
+~~~
+5. Submission of Contributions. Unless You explicitly state otherwise,
+   any Contribution intentionally submitted for inclusion in the Work
+   by You to the Licensor shall be under the terms and conditions of
+   this License, without any additional terms or conditions.
+   Notwithstanding the above, nothing herein shall supersede or modify
+   the terms of any separate license agreement you may have executed
+   with Licensor regarding such Contributions.
+~~~
+
+Contributors must sign-off each commit by adding a `Signed-off-by: ...`
+line to commit messages to certify that they have the right to submit
+the code they are contributing to the project according to the
+[Developer Certificate of Origin (DCO)](https://developercertificate.org/).

ros2_ws/src/darknet_ros2/LICENSE

@@ -0,0 +1,202 @@
+
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+   1. Definitions.
+
+      "License" shall mean the terms and conditions for use, reproduction,
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+          do not modify the License. You may add Your own attribution
+          notices within Derivative Works that You distribute, alongside
+          or as an addendum to the NOTICE text from the Work, provided
+          that such additional attribution notices cannot be construed
+          as modifying the License.
+
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+      may provide additional or different license terms and conditions
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+      for any such Derivative Works as a whole, provided Your use,
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+   5. Submission of Contributions. Unless You explicitly state otherwise,
+      any Contribution intentionally submitted for inclusion in the Work
+      by You to the Licensor shall be under the terms and conditions of
+      this License, without any additional terms or conditions.
+      Notwithstanding the above, nothing herein shall supersede or modify
+      the terms of any separate license agreement you may have executed
+      with Licensor regarding such Contributions.
+
+   6. Trademarks. This License does not grant permission to use the trade
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ros2_ws/src/darknet_ros2/README.md

@@ -0,0 +1,58 @@
+# Open Robotics Darknet ROS
+
+This is a ROS 2 wrapper around [darknet](https://pjreddie.com/darknet), an open source neural network framework.
+
+![Example image with bounding boxes created using darknet and the yolov3-tiny network](doc/example_darknet_yolov3-tiny.png)
+
+## DetectorNode
+
+This node can run object detectors like [YOLOv3](https://pjreddie.com/darknet/yolo/) on images.
+
+### Subscribers
+
+* `~/images` (type `sensor_msgs/msg/Image`) - Input mages to feed to the detector
+
+### Publishers
+
+* `~/detections` (type `vision_msgs/msg/Detection2DArray`) - Objects detected in an image (if any)
+
+### Parameters
+
+* `network.config` - a path to a file describing a darknet detector network
+* `network.weights` - a path to a file with weights for the given network
+* `network.class_names` - a path to a file with names of classes the network can detect (1 per line)
+* `detection.threshold` - Minimum probability of a detection to be published
+* `detection.nms_threshold` - Non-maximal Suppression threshold - controls filtering of overlapping boxes
+
+### Example
+
+Download `YOLOv3-tiny`.
+
+```
+wget https://raw.githubusercontent.com/pjreddie/darknet/f86901f6177dfc6116360a13cc06ab680e0c86b0/cfg/yolov3-tiny.cfg
+wget https://pjreddie.com/media/files/yolov3-tiny.weights
+wget https://raw.githubusercontent.com/pjreddie/darknet/c6afc7ff1499fbbe64069e1843d7929bd7ae2eaa/data/coco.names
+```
+
+Save the following as `detector_node_params.yaml`
+
+```yaml
+/**:
+  ros__parameters:
+    network:
+      config: "./yolov3-tiny.cfg"
+      weights: "./yolov3-tiny.weights"
+      class_names: "./coco.names"
+    detection:
+      threshold: 0.25
+      nms_threshold: 0.45
+```
+
+Then run the node.
+
+```
+ros2 run openrobotics_darknet_ros detector_node __params:=detector_node_params.yaml
+```
+
+The node is now running.
+Publish images on `~/images` to get the node to detect objects.

ros2_ws/src/darknet_ros2/include/openrobotics_darknet_ros/detector_network.hpp

@@ -0,0 +1,72 @@
+// Copyright 2019 Open Source Robotics Foundation, Inc.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#ifndef OPENROBOTICS_DARKNET_ROS__DETECTOR_NETWORK_HPP_
+#define OPENROBOTICS_DARKNET_ROS__DETECTOR_NETWORK_HPP_
+
+#include <memory>
+#include <string>
+#include <vector>
+
+#include "openrobotics_darknet_ros/visibility.hpp"
+#include "sensor_msgs/msg/image.hpp"
+#include "vision_msgs/msg/detection2_d_array.hpp"
+#include "vision_msgs/msg/object_hypothesis_with_pose.hpp"
+
+namespace openrobotics
+{
+namespace darknet_ros
+{
+// Forward declaration
+class DetectorNetworkPrivate;
+
+class DetectorNetwork
+{
+public:
+  /// \brief load a network from disk
+  /// \param[in] config_file Path to a file describing the network
+  /// \param[in] weights_file Path to a file containing the network's weights
+  /// \param[in] classes Ordered list of class names the network can predict
+  DARKNET_ROS_PUBLIC
+  DetectorNetwork(
+    const std::string & config_file,
+    const std::string & weights_file,
+    const std::vector<std::string> & classes);
+
+  DARKNET_ROS_PUBLIC
+  ~DetectorNetwork();
+
+  /// \brief Detect objects in image
+  /// \param[in] image An image to analyze
+  /// \param[in] threshold How confident the network must be to detect something [0.0, 1.0]
+  /// \param[in] nms_threshold Non-Maximal Suppression threhsold [0.0, 1.0].
+  ///   When the intersection over union (iou) of two bounding boxes is greater than nms_threshold,
+  ///   the box with the lower objectness score is discarded.
+  /// \param[out] output_detections Things detected in the image (does not set source_img)
+  /// \return number of objects detected
+  DARKNET_ROS_PUBLIC
+  size_t
+  detect(
+    const sensor_msgs::msg::Image & image,
+    double threshold,
+    double nms_threshold,
+    vision_msgs::msg::Detection2DArray * output_detections);
+
+private:
+  std::unique_ptr<DetectorNetworkPrivate> impl_;
+};
+}  // namespace darknet_ros
+}  // namespace openrobotics
+
+#endif  // OPENROBOTICS_DARKNET_ROS__DETECTOR_NETWORK_HPP_

ros2_ws/src/darknet_ros2/include/openrobotics_darknet_ros/detector_node.hpp

@@ -0,0 +1,49 @@
+// Copyright 2019 Open Source Robotics Foundation, Inc.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#ifndef OPENROBOTICS_DARKNET_ROS__DETECTOR_NODE_HPP_
+#define OPENROBOTICS_DARKNET_ROS__DETECTOR_NODE_HPP_
+
+#include <memory>
+#include <string>
+
+#include "rclcpp/node.hpp"
+#include "openrobotics_darknet_ros/visibility_node.hpp"
+
+
+namespace openrobotics
+{
+namespace darknet_ros
+{
+// Forward declaration
+class DetectorNodePrivate;
+
+class DetectorNode : public rclcpp::Node
+{
+public:
+  /// \brief Create a node that uses ROS parameters to get the network
+  DARKNET_ROS_NODE_PUBLIC
+  explicit DetectorNode(rclcpp::NodeOptions options);
+
+  DARKNET_ROS_NODE_PUBLIC
+  virtual ~DetectorNode();
+
+private:
+  std::unique_ptr<DetectorNodePrivate> impl_;
+  OnSetParametersCallbackHandle::SharedPtr callback_handle_;
+};
+}  // namespace darknet_ros
+}  // namespace openrobotics
+
+#endif  // OPENROBOTICS_DARKNET_ROS__DETECTOR_NODE_HPP_

ros2_ws/src/darknet_ros2/include/openrobotics_darknet_ros/parse.hpp

@@ -0,0 +1,36 @@
+// Copyright 2019 Open Source Robotics Foundation, Inc.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#ifndef OPENROBOTICS_DARKNET_ROS__PARSE_HPP_
+#define OPENROBOTICS_DARKNET_ROS__PARSE_HPP_
+
+#include <string>
+#include <vector>
+
+#include "openrobotics_darknet_ros/visibility.hpp"
+
+namespace openrobotics
+{
+namespace darknet_ros
+{
+/// \brief Read file containing class names, one per line
+/// \param[in] filename a path to a file containing classes a network can detect
+/// \return a container with all of the class names detected
+DARKNET_ROS_PUBLIC
+std::vector<std::string>
+parse_class_names(const std::string & filename);
+}  // namespace darknet_ros
+}  // namespace openrobotics
+
+#endif  // OPENROBOTICS_DARKNET_ROS__PARSE_HPP_

ros2_ws/src/darknet_ros2/include/openrobotics_darknet_ros/visibility.hpp

@@ -0,0 +1,56 @@
+// Copyright 2019 Open Source Robotics Foundation, Inc.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+/* This header must be included by all rclcpp headers which declare symbols
+ * which are defined in the rclcpp library. When not building the rclcpp
+ * library, i.e. when using the headers in other package's code, the contents
+ * of this header change the visibility of certain symbols which the rclcpp
+ * library cannot have, but the consuming code must have inorder to link.
+ */
+
+#ifndef OPENROBOTICS_DARKNET_ROS__VISIBILITY_HPP_
+#define OPENROBOTICS_DARKNET_ROS__VISIBILITY_HPP_
+
+// This logic was borrowed (then namespaced) from the examples on the gcc wiki:
+//     https://gcc.gnu.org/wiki/Visibility
+
+#if defined _WIN32 || defined __CYGWIN__
+  #ifdef __GNUC__
+    #define DARKNET_ROS_EXPORT __attribute__ ((dllexport))
+    #define DARKNET_ROS_IMPORT __attribute__ ((dllimport))
+  #else
+    #define DARKNET_ROS_EXPORT __declspec(dllexport)
+    #define DARKNET_ROS_IMPORT __declspec(dllimport)
+  #endif
+  #ifdef DARKNET_ROS_BUILDING_LIBRARY
+    #define DARKNET_ROS_PUBLIC DARKNET_ROS_EXPORT
+  #else
+    #define DARKNET_ROS_PUBLIC DARKNET_ROS_IMPORT
+  #endif
+  #define DARKNET_ROS_PUBLIC_TYPE DARKNET_ROS_PUBLIC
+  #define DARKNET_ROS_LOCAL
+#else
+  #define DARKNET_ROS_EXPORT __attribute__ ((visibility("default")))
+  #define DARKNET_ROS_IMPORT
+  #if __GNUC__ >= 4
+    #define DARKNET_ROS_PUBLIC __attribute__ ((visibility("default")))
+    #define DARKNET_ROS_LOCAL  __attribute__ ((visibility("hidden")))
+  #else
+    #define DARKNET_ROS_PUBLIC
+    #define DARKNET_ROS_LOCAL
+  #endif
+  #define DARKNET_ROS_PUBLIC_TYPE
+#endif
+
+#endif  // OPENROBOTICS_DARKNET_ROS__VISIBILITY_HPP_

ros2_ws/src/darknet_ros2/include/openrobotics_darknet_ros/visibility_node.hpp

@@ -0,0 +1,56 @@
+// Copyright 2019 Open Source Robotics Foundation, Inc.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+/* This header must be included by all rclcpp headers which declare symbols
+ * which are defined in the rclcpp library. When not building the rclcpp
+ * library, i.e. when using the headers in other package's code, the contents
+ * of this header change the visibility of certain symbols which the rclcpp
+ * library cannot have, but the consuming code must have inorder to link.
+ */
+
+#ifndef OPENROBOTICS_DARKNET_ROS__VISIBILITY_NODE_HPP_
+#define OPENROBOTICS_DARKNET_ROS__VISIBILITY_NODE_HPP_
+
+// This logic was borrowed (then namespaced) from the examples on the gcc wiki:
+//     https://gcc.gnu.org/wiki/Visibility
+
+#if defined _WIN32 || defined __CYGWIN__
+  #ifdef __GNUC__
+    #define DARKNET_ROS_NODE_EXPORT __attribute__ ((dllexport))
+    #define DARKNET_ROS_NODE_IMPORT __attribute__ ((dllimport))
+  #else
+    #define DARKNET_ROS_NODE_EXPORT __declspec(dllexport)
+    #define DARKNET_ROS_NODE_IMPORT __declspec(dllimport)
+  #endif
+  #ifdef DARKNET_ROS_NODE_BUILDING_LIBRARY
+    #define DARKNET_ROS_NODE_PUBLIC DARKNET_ROS_NODE_EXPORT
+  #else
+    #define DARKNET_ROS_NODE_PUBLIC DARKNET_ROS_NODE_IMPORT
+  #endif
+  #define DARKNET_ROS_NODE_PUBLIC_TYPE DARKNET_ROS_NODE_PUBLIC
+  #define DARKNET_ROS_NODE_LOCAL
+#else
+  #define DARKNET_ROS_NODE_EXPORT __attribute__ ((visibility("default")))
+  #define DARKNET_ROS_NODE_IMPORT
+  #if __GNUC__ >= 4
+    #define DARKNET_ROS_NODE_PUBLIC __attribute__ ((visibility("default")))
+    #define DARKNET_ROS_NODE_LOCAL  __attribute__ ((visibility("hidden")))
+  #else
+    #define DARKNET_ROS_NODE_PUBLIC
+    #define DARKNET_ROS_NODE_LOCAL
+  #endif
+  #define DARKNET_ROS_NODE_PUBLIC_TYPE
+#endif
+
+#endif  // OPENROBOTICS_DARKNET_ROS__VISIBILITY_NODE_HPP_

ros2_ws/src/darknet_ros2/package.xml

@@ -0,0 +1,29 @@
+<?xml version="1.0"?>
+<package format="2">
+  <name>openrobotics_darknet_ros</name>
+  <version>0.1.0</version>
+  <description>ROS wrapper around darknet, an open source neural network framework.</description>
+
+  <author email="sloretz@openrobotics.org">Shane Loretz</author>
+  <maintainer email="sloretz@openrobotics.org">Shane Loretz</maintainer>
+
+  <license>Apache License 2.0</license>
+
+  <buildtool_depend>ament_cmake</buildtool_depend>
+
+  <depend>cv_bridge</depend>
+  <depend>darknet_vendor</depend>
+  <depend>rclcpp</depend>
+  <depend>rclcpp_components</depend>
+  <depend>sensor_msgs</depend>
+  <depend>vision_msgs</depend>
+
+  <test_depend>ament_cmake_gtest</test_depend>
+  <test_depend>ament_lint_auto</test_depend>
+  <test_depend>ament_lint_common</test_depend>
+
+  <export>
+    <build_type>ament_cmake</build_type>
+  </export>
+</package>
+

ros2_ws/src/darknet_ros2/src/darknet_detections.hpp

@@ -0,0 +1,44 @@
+// Copyright 2019 Open Source Robotics Foundation, Inc.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+//
+#ifndef DARKNET_DETECTIONS_HPP_
+#define DARKNET_DETECTIONS_HPP_
+
+#include <darknet_vendor/darknet_vendor.h>
+
+namespace openrobotics
+{
+namespace darknet_ros
+{
+/// \brief RAII wrapper around darknet type `detections`
+class DarknetDetections
+{
+public:
+  /// \brief Steal ownership of detections
+  DarknetDetections(detection * darknet_detections, size_t num_detections)
+  : detections_(darknet_detections), num_detections_(num_detections)
+  {
+  }
+
+  ~DarknetDetections()
+  {
+    free_detections(detections_, num_detections_);
+  }
+
+  detection * detections_;
+  const size_t num_detections_ = 0;
+};
+}  // namespace darknet_ros
+}  // namespace openrobotics
+#endif  // DARKNET_DETECTIONS_HPP_

ros2_ws/src/darknet_ros2/src/darknet_image.hpp

@@ -0,0 +1,71 @@
+// Copyright 2019 Open Source Robotics Foundation, Inc.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#ifndef DARKNET_IMAGE_HPP_
+#define DARKNET_IMAGE_HPP_
+
+#include <darknet_vendor/darknet_vendor.h>
+#include <cv_bridge/cv_bridge.h>
+
+#include <memory>
+
+namespace openrobotics
+{
+namespace darknet_ros
+{
+/// \brief RAII wrapper around darknet type `image`
+class DarknetImage
+{
+public:
+  /// \brief Steal ownership of image
+  explicit DarknetImage(image darknet_image)
+  : image_(darknet_image)
+  {
+  }
+
+  explicit DarknetImage(const sensor_msgs::msg::Image & image_msg)
+  {
+    // Convert to open cv type with a known format
+    std::shared_ptr<void const> dummy_object;
+    cv_bridge::CvImageConstPtr opencv_image = cv_bridge::toCvShare(image_msg, dummy_object, "rgb8");
+    const cv::Mat & image_matrix = opencv_image->image;
+
+    // Make a darknet image with this data
+    const int width = image_matrix.cols;
+    const int height = image_matrix.rows;
+    const int channels = 3;  // rgb
+    image_ = make_image(width, height, channels);
+
+    for (int channel = 0; channel < channels; ++channel) {
+      for (int row = 0; row < image_matrix.rows; ++row) {
+        for (int column = 0; column < image_matrix.cols; ++column) {
+          // Darknet stores each channel separately in R G B order
+          // Within a channel pixels are in row-major order
+          size_t darknet_idx = channel * height * width + row * width + column;
+          image_.data[darknet_idx] = image_matrix.ptr(row, column)[channel] / 255.0f;
+        }
+      }
+    }
+  }
+
+  ~DarknetImage()
+  {
+    free_image(image_);
+  }
+
+  image image_;
+};
+}  // namespace darknet_ros
+}  // namespace openrobotics
+#endif  // DARKNET_IMAGE_HPP_

ros2_ws/src/darknet_ros2/src/detector_network.cpp

@@ -0,0 +1,176 @@
+// Copyright 2019 Open Source Robotics Foundation, Inc.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <darknet_vendor/darknet_vendor.h>
+
+#include <fstream>
+#include <memory>
+#include <sstream>
+#include <string>
+#include <vector>
+
+#include "darknet_detections.hpp"
+#include "darknet_image.hpp"
+#include "openrobotics_darknet_ros/detector_network.hpp"
+
+namespace openrobotics
+{
+namespace darknet_ros
+{
+class DetectorNetworkPrivate
+{
+public:
+  DetectorNetworkPrivate() {}
+
+  ~DetectorNetworkPrivate()
+  {
+    if (network_) {
+      free_network(network_);
+      network_ = nullptr;
+    }
+  }
+
+  // darknet network
+  network * network_ = nullptr;
+  // Classes the network can detect
+  std::vector<std::string> class_names_;
+};
+
+DetectorNetwork::DetectorNetwork(
+  const std::string & config_file,
+  const std::string & weights_file,
+  const std::vector<std::string> & classes)
+: impl_(new DetectorNetworkPrivate())
+{
+  if (!std::ifstream(config_file)) {
+    std::stringstream str;
+    str << "Could not open " << config_file;
+    throw std::invalid_argument(str.str());
+  } else if (!std::ifstream(weights_file)) {
+    std::stringstream str;
+    str << "Could not open " << weights_file;
+    throw std::invalid_argument(str.str());
+  }
+
+  impl_->class_names_ = classes;
+
+  // Make copies because of darknet's lack of const
+  std::unique_ptr<char> config_mutable(new char[config_file.size() + 1]);
+  std::unique_ptr<char> weights_mutable(new char[weights_file.size() + 1]);
+  snprintf(&*config_mutable, config_file.size() + 1, "%s", config_file.c_str());
+  snprintf(&*weights_mutable, weights_file.size() + 1, "%s", weights_file.c_str());
+
+  const int clear = 0;
+  impl_->network_ = load_network(&*config_mutable, &*weights_mutable, clear);
+  if (nullptr == impl_->network_) {
+    std::stringstream str;
+    str << "Failed to load network from " << config_file << " and " << weights_file;
+    throw std::invalid_argument(str.str());
+  }
+
+  // TODO(sloretz) what is this and why do examples set it?
+  const int batch = 1;
+  set_batch_network(impl_->network_, batch);
+
+  const int num_classes_int = impl_->network_->layers[impl_->network_->n - 1].classes;
+  if (num_classes_int <= 0) {
+    throw std::invalid_argument("Invalid network, it expects no classes");
+  }
+  size_t num_classes = static_cast<size_t>(num_classes_int);
+  if (num_classes != classes.size()) {
+    std::stringstream str;
+    str << "DetectorNetwork expects " << num_classes << " class names but got " << classes.size();
+    throw std::invalid_argument(str.str());
+  }
+}
+
+DetectorNetwork::~DetectorNetwork()
+{
+}
+
+size_t
+DetectorNetwork::detect(
+  const sensor_msgs::msg::Image & image_msg,
+  double threshold,
+  double nms_threshold,
+  vision_msgs::msg::Detection2DArray * output_detections)
+{
+  DarknetImage orig_image(image_msg);
+
+  // resize image to network size, filling rest with gray
+  DarknetImage resized_image(
+    letterbox_image(orig_image.image_, impl_->network_->w, impl_->network_->h));
+
+  // Ask network to make predictions
+  network_predict(impl_->network_, resized_image.image_.data);
+
+  // Get predictions from network
+  int num_detections = 0;
+  // TODO(sloretz) what do hier, map, and relative do?
+  const float hier = 0;
+  int * map = nullptr;
+  const int relative = 0;
+  detection * darknet_detections = get_network_boxes(
+    impl_->network_, image_msg.width, image_msg.height, threshold,
+    hier, map, relative,
+    &num_detections);
+
+  if (num_detections <= 0) {
+    return 0;
+  }
+
+  DarknetDetections raii_detections(darknet_detections, static_cast<size_t>(num_detections));
+
+  // Non-maximal suppression: filters overlapping bounding boxes
+  if (nms_threshold > 0.0f) {
+    const int num_classes = impl_->network_->layers[impl_->network_->n - 1].classes;
+    do_nms_sort(darknet_detections, num_detections, num_classes, nms_threshold);
+  }
+
+  // Populate output message
+  output_detections->header = image_msg.header;
+  output_detections->detections.reserve(num_detections);
+  for (int i = 0; i < num_detections; ++i) {
+    auto & detection = darknet_detections[i];
+    output_detections->detections.emplace_back();
+    auto & detection_ros = output_detections->detections.back();
+
+    // Copy probabilities of each class
+    for (int cls = 0; cls < detection.classes; ++cls) {
+      if (detection.prob[cls] > 0.0f) {
+        detection_ros.results.emplace_back();
+        vision_msgs::msg::ObjectHypothesisWithPose hypothesis = detection_ros.results.back();
+        hypothesis.hypothesis.class_id = impl_->class_names_.at(cls);
+        hypothesis.hypothesis.score = detection.prob[cls];
+      }
+    }
+
+    if (detection_ros.results.empty()) {
+      // nms suppressed this detection
+      output_detections->detections.pop_back();
+      continue;
+    }
+
+    // Copy bounding box, darknet uses center of bounding box too
+    detection_ros.bbox.center.position.x = detection.bbox.x;
+    detection_ros.bbox.center.position.y = detection.bbox.y;
+    detection_ros.bbox.size_x = detection.bbox.w;
+    detection_ros.bbox.size_y = detection.bbox.h;
+  }
+
+  // Not using num_detections because nms may have suppressed some
+  return output_detections->detections.size();
+}
+}  // namespace darknet_ros
+}  // namespace openrobotics

ros2_ws/src/darknet_ros2/src/detector_node.cpp

@@ -0,0 +1,167 @@
+// Copyright 2019 Open Source Robotics Foundation, Inc.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <darknet_vendor/darknet_vendor.h>
+
+#include <memory>
+#include <string>
+#include <utility>
+#include <vector>
+
+#include "openrobotics_darknet_ros/detector_node.hpp"
+#include "openrobotics_darknet_ros/detector_network.hpp"
+#include "openrobotics_darknet_ros/parse.hpp"
+#include "rcl_interfaces/msg/parameter_descriptor.hpp"
+#include "rclcpp/parameter_value.hpp"
+#include "rclcpp/parameter_client.hpp"
+
+namespace openrobotics
+{
+namespace darknet_ros
+{
+class DetectorNodePrivate
+{
+public:
+  void on_image_rx(const sensor_msgs::msg::Image::ConstSharedPtr image_msg)
+  {
+    vision_msgs::msg::Detection2DArray::UniquePtr detections(
+      new vision_msgs::msg::Detection2DArray);
+    // std::cerr << "using threshold " << threshold_ << " nms " << nms_threshold_ << "\n";
+    if (network_->detect(*image_msg, threshold_, nms_threshold_, &*detections)) {
+      detections_pub_->publish(std::move(detections));
+    }
+  }
+
+  rcl_interfaces::msg::SetParametersResult
+  on_parameters_change(const std::vector<rclcpp::Parameter> & new_values)
+  {
+    rcl_interfaces::msg::SetParametersResult result;
+    result.successful = true;
+    double new_threshold = threshold_;
+    double new_nms_threshold = nms_threshold_;
+
+    for (const auto & parameter : new_values) {
+      if (threshold_desc_.name == parameter.get_name()) {
+        new_threshold = parameter.as_double();
+        // TODO(sloretz) range constraints in parameter description
+        if (new_threshold < 0.0 || new_threshold > 1.0) {
+          result.successful = false;
+          result.reason = "threshold out of range [0.0, 1.0]";
+        }
+      } else if (nms_threshold_desc_.name == parameter.get_name()) {
+        new_nms_threshold = parameter.as_double();
+        if (new_nms_threshold < 0.0 || new_nms_threshold > 1.0) {
+          result.successful = false;
+          result.reason = "nms_threshold out of range [0.0, 1.0]";
+        }
+      }
+    }
+    if (result.successful) {
+      threshold_ = new_threshold;
+      nms_threshold_ = new_nms_threshold;
+      // std::cerr << "New threshold " << threshold_ << " nms " << nms_threshold_ << "\n";
+    }
+    return result;
+  }
+
+  std::unique_ptr<DetectorNetwork> network_;
+  rclcpp::Publisher<vision_msgs::msg::Detection2DArray>::SharedPtr detections_pub_;
+  rclcpp::Subscription<sensor_msgs::msg::Image>::SharedPtr image_sub_;
+
+  double threshold_ = 0.25;
+  double nms_threshold_ = 0.45;
+
+  rcl_interfaces::msg::ParameterDescriptor threshold_desc_;
+  rcl_interfaces::msg::ParameterDescriptor nms_threshold_desc_;
+};
+
+DetectorNode::DetectorNode(rclcpp::NodeOptions options)
+: rclcpp::Node("detector_node", options), impl_(new DetectorNodePrivate)
+{
+  // Read-only input parameters: cfg, weights, classes
+  rcl_interfaces::msg::ParameterDescriptor network_cfg_desc;
+  network_cfg_desc.description = "Path to config file describing network";
+  network_cfg_desc.type = rcl_interfaces::msg::ParameterType::PARAMETER_STRING;
+  network_cfg_desc.read_only = true;
+  network_cfg_desc.name = "network.config";
+  const std::string network_config_path = declare_parameter(
+    network_cfg_desc.name,
+    rclcpp::ParameterValue(),
+    network_cfg_desc).get<std::string>();
+
+  rcl_interfaces::msg::ParameterDescriptor network_weights_desc;
+  network_weights_desc.description = "Path to file describing network weights";
+  network_weights_desc.type = rcl_interfaces::msg::ParameterType::PARAMETER_STRING;
+  network_weights_desc.read_only = true;
+  network_weights_desc.name = "network.weights";
+  const std::string network_weights_path = declare_parameter(
+    network_weights_desc.name,
+    rclcpp::ParameterValue(),
+    network_weights_desc).get<std::string>();
+
+  rcl_interfaces::msg::ParameterDescriptor network_class_names_desc;
+  network_class_names_desc.description = "Path to file with class names (one per line)";
+  network_class_names_desc.type = rcl_interfaces::msg::ParameterType::PARAMETER_STRING;
+  network_class_names_desc.read_only = true;
+  network_class_names_desc.name = "network.class_names";
+  const std::string network_class_names_path = declare_parameter(
+    network_class_names_desc.name,
+    rclcpp::ParameterValue(),
+    network_class_names_desc).get<std::string>();
+
+  impl_->threshold_desc_.description = "Minimum detection confidence [0.0, 1.0]";
+  impl_->threshold_desc_.type = rcl_interfaces::msg::ParameterType::PARAMETER_DOUBLE;
+  impl_->threshold_desc_.name = "detection.threshold";
+  impl_->threshold_ = declare_parameter(
+    impl_->threshold_desc_.name,
+    rclcpp::ParameterValue(impl_->threshold_),
+    impl_->threshold_desc_).get<double>();
+
+  impl_->nms_threshold_desc_.description =
+    "Non Maximal Suppression threshold for filtering overlapping boxes [0.0, 1.0]";
+  impl_->nms_threshold_desc_.type = rcl_interfaces::msg::ParameterType::PARAMETER_DOUBLE;
+  impl_->nms_threshold_desc_.name = "detection.nms_threshold";
+  impl_->nms_threshold_ = declare_parameter(
+    impl_->nms_threshold_desc_.name,
+    rclcpp::ParameterValue(impl_->nms_threshold_),
+    impl_->nms_threshold_desc_).get<double>();
+
+  // Register a callback for parameter changes
+  // auto parameters_client = std::make_shared<rclcpp::SyncParametersClient>(this);
+  // parameters_client->add_on_set_parameters_callback(std::bind(&DetectorNodePrivate::on_parameters_change, &*impl_, std::placeholders::_1));
+  callback_handle_ = this->add_on_set_parameters_callback(std::bind(&DetectorNodePrivate::on_parameters_change, &*impl_, std::placeholders::_1));
+  // TODO(sloretz) raise if user tried to initialize node with undeclared parameters
+
+  std::vector<std::string> class_names = parse_class_names(network_class_names_path);
+  impl_->network_.reset(
+    new DetectorNetwork(network_config_path, network_weights_path, class_names));
+
+  // Ouput topic ~/detections [vision_msgs/msg/Detection2DArray]
+  impl_->detections_pub_ = this->create_publisher<vision_msgs::msg::Detection2DArray>(
+    "~/detections", 1);
+
+  // Input topic ~/images [sensor_msgs/msg/Image]
+  impl_->image_sub_ = this->create_subscription<sensor_msgs::msg::Image>(
+    "~/images", 12, std::bind(&DetectorNodePrivate::on_image_rx, &*impl_, std::placeholders::_1));
+}
+
+DetectorNode::~DetectorNode()
+{
+}
+}  // namespace darknet_ros
+}  // namespace openrobotics
+
+#include "rclcpp_components/register_node_macro.hpp"
+
+RCLCPP_COMPONENTS_REGISTER_NODE(openrobotics::darknet_ros::DetectorNode)

ros2_ws/src/darknet_ros2/src/detector_node_main.cpp

@@ -0,0 +1,31 @@
+// Copyright 2019 Open Source Robotics Foundation, Inc.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <memory>
+
+#include "openrobotics_darknet_ros/detector_node.hpp"
+#include "rclcpp/rclcpp.hpp"
+
+int main(int argc, char ** argv)
+{
+  rclcpp::init(argc, argv);
+
+  rclcpp::NodeOptions options;
+  auto detector_node = std::make_shared<openrobotics::darknet_ros::DetectorNode>(options);
+
+  rclcpp::spin(detector_node);
+
+  rclcpp::shutdown();
+  return 0;
+}

ros2_ws/src/darknet_ros2/src/parse.cpp

@@ -0,0 +1,51 @@
+// Copyright 2019 Open Source Robotics Foundation, Inc.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <fstream>
+#include <sstream>
+#include <string>
+#include <vector>
+
+#include "openrobotics_darknet_ros/parse.hpp"
+
+namespace openrobotics
+{
+namespace darknet_ros
+{
+std::vector<std::string>
+parse_class_names(const std::string & filename)
+{
+  std::ifstream fin(filename);
+  std::vector<std::string> class_names;
+  std::string line;
+  while (fin) {
+    std::getline(fin, line);
+    if (!fin) {
+      if (!fin.eof()) {
+        std::stringstream str;
+        str << "Failed to read [" << filename << "] line " << class_names.size();
+        throw std::runtime_error(str.str());
+      }
+      break;
+    }
+    if (line.empty()) {
+      // Ignore blank lines
+      continue;
+    }
+    class_names.emplace_back(line);
+  }
+  return class_names;
+}
+}  // namespace darknet_ros
+}  // namespace openrobotics

ros2_ws/src/darknet_ros2/test/data/1_class_name.txt

@@ -0,0 +1 @@
+tomato

ros2_ws/src/darknet_ros2/test/data/3_class_names_with_whitespace.txt

@@ -0,0 +1,10 @@
+
+
+
+foo
+
+
+bar
+
+
+baz