Overview

This package provides support for parsing convolution neural networks (CNN), and publishing them as ROS messages. Currently the package supports both detection an segmentation networks.

Input can be either from camera topics, an OpenCV camera, or a video.

ROS Nodes

cnn_publisher

ROS node that opens a freeze graph and run it on images.

Publishes

detection

type = cnn_bridge/Detection Detection data. Published as boxes, scores, and classes. In addition, the header of the image that the network was run on (useful for statistics, and for hmi). OR

segmentation

type = cnn_bridge/Netmask Segmentation data. Published a 2-dimensional array of mask values. In addition, the header of the image that the network was run on (useful for statistics, and for hmi).

Parameters

• source type = string
  required = True
  The source of the images to be run through the network. There are three types of inputs allowed. The first, is a path to a video file (any OpenCV compatible files will work). The second, is a device number (0, 1, 2, 3,…) for an OpenCV device. The third is a ROS Image or CompressedImage topic. Currently, this option works for ‘usb_cam’ (subscribes to ‘usb_cam/image_raw’), ‘cv_cam’ (subscribes to ‘cv_camera/image_raw’), and ‘ueye’ subscribes to ‘ueye_0/image_raw’).
• logdir type = string
  required = True
  Path to the hypes file. See bellow for an example JSON file.
• metadata_source type = string
  required = True
  Path to the metadata file. See bellow for an example JSON file.
• mode type = string
  required = True
  Either ‘detection’ or ‘segmentation’ depending on the mode.
• input_tensor type = string
  required = True
  Self explanatory.
• output_tensor type = string/[string]
  required = True
  If segmentation, self explanatory. If detection an array of three tensors that are [boxes,scores,classes]
• display type = Boolean
  default = True
  Whether to display the output or not
• video_save type = Boolean/String
  default = True
  Not currently implemented! Whether to save the output or not. Use False to disable. True saves to ‘/Camera__datetime'. If a string is provided it will be the video title. The node saves both the raw video and the video with the mask / boxes overlay. If running on a video file, the raw is not saved.
• cpu type = string default = False Not currently implemented! Sets whether to run the network on the CPU if an Nvidia GPU is present.
• gpu_percent type = Float default = 1.0 Sets the percentage of an Nvidia GPU to use. This is used generally for running simultaneous networks.

Launch File Examples

Start a cnn_bridge in segmentation mode: $ roslaunch cnn_bridge segmentation_publisher.launch Start a cnn_bridge in detection mode: $ roslaunch cnn_bridge detection_publisher.launch

Hypes Example

` { “frozen_graph_path”: “", "image_height": 361, "image_width": 641, "resize_image": true, //TODO Add additional fields } `

Metadata JSON

If segmentation mode: ` { “classes”: [“CLASS_NAME_1”, “CLASS_NAME_2”, …, “CLASS_NAME_N”] } `

If detection mode: ` { “classes”: [{ “color”: (red, green, blue), “id”: < The ID of the class as outputted from the network >, “name”: < Name assigned to the class > “id_category”: < The ID of a parent class (ie. If class dog parent Animal) > “category”: < The name of a parent class (ie. If class dog parent Animal) > }] } `

Changelog for package cnn_bridge

0.8.4 (2019-05-10)

• Moved source to repo
• Initial commit
• Contributors: Noam C. Golombek