The ROS Package of Mask R-CNN for Object Detection and Segmentation

This is a ROS package of Mask R-CNN algorithm for object detection and segmentation.

The package contains ROS node of Mask R-CNN with topic-based ROS interface.

Most of core algorithm code was based on Mask R-CNN implementation by Matterport, Inc.

This is for Object detection which can detect several objects regardless of their classes.

But it can not classify their classes. It just detects objects.

Training

This repository doesn't contain code for training Mask R-CNN network model. If you want to train the model on your own class definition or dataset, try it on the upstream reposity and give the result weight to model_path parameter.

Requirements

• ROS kinetic/Melodic
• TensorFlow 1.14
• Keras 2.1.13
• Numpy, skimage, scipy, Pillow, cython, h5py
• I only test code on Python3.X.

ROS Interfaces

Parameters

• ~model_path: string

  Path to the HDF5 model file. If the model_path is default value and the file doesn't exist, the node automatically downloads the file.

  Default: $ROS_HOME/mask_rcnn_coco.h5

• ~visualization: bool

  If true, the node publish visualized images to ~visualization topic. Default: true

• ~class_names: string[]

  Class names to be treated as detection targets. Default: All MS COCO classes.

Topics Published

• ~result: mask_rcnn_ros/Result

  Result of detection. See also Result.msg for detailed description.

• ~visualization: sensor_mgs/Image

  Visualized result over an input image.

Topics Subscribed

• ~input: sensor_msgs/Image

  Input image to be proccessed

Getting Started

1. Clone this repository to your catkin workspace, build workspace and source devel environment
2. Download the trained model and locate it at proper path.
3. Run mask_rcnn node

   $ rosrun mask_rcnn_ros mask_rcnn_node
   

Example

There is a simple example launch file using RGB-D SLAM Dataset.

$ sudo chmod 777 scripts/download_freiburg3_rgbd_example_bag.sh
$ ./scripts/download_freiburg3_rgbd_example_bag.sh
$ roslaunch mask_rcnn_ros freiburg3_rgbd_example.launch