This package provides a ros warpper for py-faster-rcnn here.
You should make a new catkin workspace for the code in this repo. This is all of the code that will need to run in the docker image. You should save model files in py_faster_rcnn_ros/models/caffe/.
You need to have nvidia-docker2 installed Follow the instructions here. https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#install-guide
Download the docker image from dockerhub
docker pull kschmeckpeper/py_faster_rcnn_ros
Start the docker image
docker run -rm -v ~/PATH/TO/catkin_ws_docker:/curiosity/catkin_ws_docker -it --network host --gpus all -w /curiosity/catkin_ws_docker kschmeckpeper/py_faster_rcnn_ros bash
The first time you start the docker image, you will need to build the code in the catkin workspace.
On the host machine, start ros.
Inside the docker image, run
roslaunch py_faster_rcnn_ros detector.launch
This should connect to the ros network on the host machine.