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vision package from vauv repo

bar30_py battery_management_unit custom_ros_interfaces generic_interfaces health_monitor localization mission_planning trajectory_tracking_lqr trajectory_tracking_mpc motion_planning pixhawk4 sensors vision

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Browse Code

Package Summary

Tags No category tags.
Version 0.0.0
License GNU GENERAL PUBLIC LICENSE
Build type AMENT_CMAKE
Use RECOMMENDED

Repository Summary

Description VorteX AUV
Checkout URI https://github.com/vortex-co/vauv.git
VCS Type git
VCS Version master
Last Updated 2022-02-13
Dev Status UNKNOWN
CI status No Continuous Integration
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

vision package

Additional Links

No additional links.

Maintainers

  • vortex-co

Authors

No additional authors.
Software/vortex_ws/src/vision/README.md

Vision

Description

The Vision package is responsible for image enhancement, image processing, and performing multiple deep learning models and computer vision algorithms on the video streams coming from the AUV cameras’ to detect its targets to publish the AUV current state to the other modules.

The source code is released under a GNU GENERAL PUBLIC LICENSE.

Author: vortex-co
Affiliation: VorteX-Co
Maintainer: vortex-co, info@vortex-co.com

The Vision package has been tested under ROS2 eloquent on Ubuntu 18.04.

Table of contents

Usage

  • Source your ROS2 installation. 
      source /opt/ros/eloquent/setup.bash
  • Navigate to your workspace 
          cd ~/$HOME/VAUV/Software/vortex_ws
  • Build your package 
      colcon build --packages-select <package_name>
  • Start to run node by node with 
      ros2 run <package_name> <node_name>
  • Or with launch file with 
      ros2 launch <package_name> launch_file_name.launch.py

Config files

  • image_enhancement_params.yaml

    Launch files

  • …

Nodes

image_enhancement

The image enhancement node is responsible for improving the quality of the raw images before processing. By applying many filters for histogram equalization, Noise removal, and so on.

Subscribed Topics

  • /raw frame ([sensor_msgs/Frame]) The raw frames from sensor package.

    Published Topics

  • /enhanced frame ([sensor_msgs/Frame]) The enhanced frames after removing noise and manipulate contrast, darkness, and so on.

object_detection

Contains deep learning models that take the enhanced frame to get the image details.

Subscribed Topics

  • /enhanced frame ([sensor_msgs/Frame]) The enhanced frame that published by image_enhancement node.

    Published Topics

  • /image details ([str_msgs/Data]) The image details data contains the target classes and their coordinates.

target_analysis

Contains computer vision algorithms that take the enhanced frames and image details data to get finer details about the detected target.

Subscribed Topics

  • /enhanced frame ([sensor_msgs/Frame])
  • /image details ([str_msgs/Data])

    Published Topics

  • /object details ([str_msgs/Data]) The object details data contains finer details inside the object itself.

data_fusion

Takes the data from object_detection and target_analysis nodes and handle it to get more informative messages about the AUV current state.

Subscribed Topics

  • /object details ([str_msgs/Data])
  • /image details ([str_msgs/Data])

    Published Topics

  • /current state ([str_msgs/Data]) The current state data contains informative messages about the AUV current state.

Hardware

This package acess the following hardware:

  • ZED 2 Camera
  • Low Light Camera
CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Package Dependencies

Deps Name
ament_cmake
ament_lint_auto
ament_lint_common

System Dependencies

No direct system dependencies.

Dependant Packages

Name Deps
bringup

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged vision at Robotics Stack Exchange

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