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yolov5_ros

yolov5 with ROS

Environment
OS Ubuntu 18.04
CUDA 10.2
Pytorch version 1.8
ROS version Melodic
Language Python3

Based on YOLOv5.

How to use

  1. Locate weight files on weights folder, data.yaml files on data folder(maybe data.yaml file is not necessary).

  2. Edit your detector.launch file.

<?xml version="1.0" encoding="UTF-8"?>
<launch>
    <arg name="weights_name"    default="yolov5s_door.pt" />
    <arg name="data_name"       default="door_handle.yaml" />

    <!-- Camera topic and weights, config arguments -->
    <arg name="image_topic"     default="/camera/color/image_raw" />
    <arg name="weights"         default="$(find yolov5_ros)/weights/$(arg weights_name)" />
    <arg name="data"            default="$(find yolov5_ros)/data/$(arg data_name)" />
    <arg name="width"           default="640" />
    <arg name="height"          default="480" />
    <arg name="conf_thres"      default="0.25" />

    <!-- Node -->
    <node name="detector" pkg="yolov5_ros" type="detect.py" output="screen" respawn="true">
        <param name="image_topic"   value="$(arg image_topic)" />
        <param name="weights"       value="$(arg weights)" />
        <param name="data"          value="$(arg data)" />
        <param name="width"         value="$(arg width)" />
        <param name="height"        value="$(arg height)" />
        <param name="conf_thres"    value="$(arg conf_thres)" />
    </node>
</launch>

Change arguments, "weights_name", "data_name" to yours. Also change "image_topic" too. Or you can just declare argument when you launch the launch file.

$ roslaunch yolov5_ros detector.launch weights_name:=${your weight file name} data_name:=${your yaml data file name} image_topic:=${image topic name}

Published topic

  • /detected_img

sensor_msgs/Image

  • /bounding_box_array

yolov5_ros/BoundingBoxes

header

bounding_boxes[]

string Class

float64 probability

int64 xmin

int64 ymin

int64 xmax

int64 ymax

TensorRT

If you want to use tensorrt model, file name "~~.engine", you have to check tensorrt version. If tensorrt version is mismatched, would face serialization error like this.

Serialization (Serialization assertion safeVersionRead == safeSerializationVersion failed.Version tag does not match.

So, it is recommended that make your own tenorrt model at your PC, with following this doc.