danmartinez78 / coral_usb_ros

ROS package for Coral Edge TPU USB Accelerator

coral_usb_ros

ROS package for Coral Edge TPU USB Accelerator

Environment

• Ubuntu 16.04 + Kinetic
• Ubuntu 18.04 + Melodic

If you want to run this on Ubuntu 14.04 + Indigo, please see indigo branch.

If you want to run this on PR2, please see pr2 branch.

Notice

We need python3.5 or python3.6 to run this package.

ROS Node list

Object detector: edgetpu_object_detector.py

Face detector: edgetpu_face_detector.py

Human Pose Estimator: edgetpu_human_pose_estimator.py

For more detailed information, see here.

Setup

Install Edge TPU Dependencies

Follow this page.

Install the Edge TPU runtime

echo "deb https://packages.cloud.google.com/apt coral-edgetpu-stable main" | sudo tee /etc/apt/sources.list.d/coral-edgetpu.list
curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo apt-key add -
sudo apt-get update
# If you do not have USB3, install libedgetpu1-std
sudo apt-get install libedgetpu1-max
sudo apt-get install python3-edgetpu

Install just the TensorFlow Lite interpreter (kinetic)

sudo apt-get install python3-pip
wget https://dl.google.com/coral/python/tflite_runtime-1.14.0-cp35-cp35m-linux_x86_64.whl
pip3 install tflite_runtime-1.14.0-cp35-cp35m-linux_x86_64.whl

Install just the TensorFlow Lite interpreter (melodic)

sudo apt-get install python3-pip
wget https://dl.google.com/coral/python/tflite_runtime-1.14.0-cp36-cp36m-linux_x86_64.whl
pip3 install tflite_runtime-1.14.0-cp36-cp36m-linux_x86_64.whl

Workspace build (kinetic)

source /opt/ros/kinetic/setup.bash
mkdir -p ~/coral_ws/src
cd ~/coral_ws/src
git clone https://github.com/knorth55/coral_usb_ros.git
wstool init
wstool merge coral_usb_ros/fc.rosinstall
wstool update
rosdep install --from-paths . --ignore-src -y -r
cd ~/coral_ws
catkin init
catkin config -DPYTHON_EXECUTABLE=/usr/bin/python3 -DPYTHON_INCLUDE_DIR=/usr/include/python3.5m -DPYTHON_LIBRARY=/usr/lib/x86_64-linux-gnu/libpython3.5m.so
catkin build

Workspace build (melodic)

source /opt/ros/melodic/setup.bash
mkdir -p ~/coral_ws/src
cd ~/coral_ws/src
git clone https://github.com/knorth55/coral_usb_ros.git
wstool init
wstool merge coral_usb_ros/fc.rosinstall.melodic
wstool update
rosdep install --from-paths . --ignore-src -y -r
cd ~/coral_ws
catkin init
catkin config -DPYTHON_EXECUTABLE=/usr/bin/python3 -DPYTHON_INCLUDE_DIR=/usr/include/python3.6m -DPYTHON_LIBRARY=/usr/lib/x86_64-linux-gnu/libpython3.6m.so
catkin build

Model download

source ~/coral_ws/devel/setup.bash
roscd coral_usb/scripts
rosrun coral_usb download_models.py

Sample

Run image_publisher

# source normal workspace, not edge tpu workspace
# /opt/ros/kinetic/setup.bash or /opt/ros/melodic/setup.bash
source /opt/ros/kinetic/setup.bash
rosrun jsk_perception image_publisher.py _file_name:=$(rospack find jsk_perception)/sample/object_detection_example_1.jpg

Run Edge TPU launch

# source edge tpu workspace
source ~/coral_ws/devel/setup.bash
# object detector
roslaunch coral_usb edgetpu_object_detector.launch INPUT_IMAGE:=/image_publisher/output
# face detector
roslaunch coral_usb edgetpu_face_detector.launch INPUT_IMAGE:=/image_publisher/output
# human pose estimator
roslaunch coral_usb edgetpu_human_pose_estimator.launch INPUT_IMAGE:=/image_publisher/output

Run image_view

# source normal workspace, not edge tpu workspace
# /opt/ros/kinetic/setup.bash or /opt/ros/melodic/setup.bash
source /opt/ros/kinetic/setup.bash
# object detector
rosrun image_view image_view image:=/edgetpu_object_detector/output/image
# face detector
rosrun image_view image_view image:=/edgetpu_face_detector/output/image
# human pose estimator
rosrun image_view image_view image:=/edgetpu_human_pose_estimator/output/image

ROS Node information

Object detector: edgetpu_object_detector.py

Subscribing Topic

• ~input/image (sensor_msgs/Image)

  • Input image

Publishing Topic

• ~output/rects (jsk_recognition_msgs/RectArray)

  • Rectangles of detected objects

• ~output/class (jsk_recognition_msgs/ClassificationResult)

  • Classification results of detected objects

• ~output/image (sensor_msgs/Image)

  • Visualization of detection results

Parameters

• ~classifier_name (String, default: rospy.get_name())

  • Classifier name

• ~model_file (String, default: $(rospack find coral_usb)/models/mobilenet_ssd_v2_coco_quant_postprocess_edgetpu.tflite)

  • Model file path

• ~label_file (String, default: $(rospack find coral_usb)/models/coco_labels.txt)

  • Label file path.

Dynamic parameters

• ~score_thresh: (Float, default: 0.6)

  • Score threshold for object detection

• ~top_k: (Int, default: 100)

  • Maximum number of detected objects

Face detector: edgetpu_face_detector.py

Subscribing Topic

• ~input/image (sensor_msgs/Image)

  • Input image

Publishing Topic

• ~output/rects (jsk_recognition_msgs/RectArray)

  • Rectangles of detected faces

• ~output/class (jsk_recognition_msgs/ClassificationResult)

  • Classification results of detected faces

• ~output/image (sensor_msgs/Image)

  • Visualization of detection results

Parameters

• ~classifier_name (String, default: rospy.get_name())

  • Classifier name

• ~model_file (String, default: $(rospack find coral_usb)/models/mobilenet_ssd_v2_face_quant_postprocess_edgetpu.tflite)

  • Model file path

Dynamic parameters

• ~score_thresh: (Float, default: 0.6)

  • Score threshold for face detection

• ~top_k: (Int, default: 100)

  • Maximum number of detected faces

Human pose estimator: edgetpu_human_pose_estimator.py

Subscribing Topic

• ~input/image (sensor_msgs/Image)

  • Input image

Publishing Topic

• ~output/poses (jsk_recognition_msgs/PeoplePoseArray)

  • Estimated human poses

• ~output/image (sensor_msgs/Image)

  • Visualization of estimation results

Parameters

• ~classifier_name (String, default: rospy.get_name())

  • Classifier name

• ~model_file (String, default: $(rospack find coral_usb)/python/coral_usb/posenet/models/posenet_mobilenet_v1_075_481_641_quant_decoder_edgetpu.tflite)

  • Model file path

Dynamic parameters

• ~score_thresh: (Float, default: 0.2)

  • Score threshold for human pose estimation

• ~joint_score_thresh: (Float, default: 0.2)

  • Score threshold of each joint for human pose estimation