Edge Insights for Autonomous Mobile Robots (EI for AMR) Developer Guide
Visible to Intel only — GUID: GUID-44966531-B356-4F3E-A214-6FC24F2EA6F2
Visible to Intel only — GUID: GUID-44966531-B356-4F3E-A214-6FC24F2EA6F2
Run OpenVINO™ Sample Applications in Docker* Container
This tutorial tells you how to:
Run inference engine object detection on a pretrained network using the SSD method.
Run the detection demo application for a CPU and GPU.
Use a model optimizer to convert a TensorFlow* neural network model.
After conversion, run the neural network with inference engine for a CPU and GPU.
Run the Sample Application
Go to the AMR_containers folder:
cd <edge_insights_for_amr_path>/Edge_Insights_for_Autonomous_Mobile_Robots_<version>/AMR_containers
Prepare the environment setup:
source 01_docker_sdk_env/docker_compose/05_tutorials/config/docker_compose.source export CONTAINER_BASE_PATH=`pwd` export ROS_DOMAIN_ID=22
Run inference engine object detection on a pre-trained network using the Single-Shot multibox Detection (SSD) method. Run the detection demo application for a CPU:
CHOOSE_USER=root docker-compose -f 01_docker_sdk_env/docker_compose/05_tutorials/openvino_CPU.demo.yml up
Expected output: A video in a loop with cars being detected and labeled by the Neural Network using a CPU
To close this, do one of the following:
Type Ctrl-c in the terminal where you did the up command.
Run this command in another terminal:
CHOOSE_USER=eiforamr docker-compose -f 01_docker_sdk_env/docker_compose/05_tutorials/openvino_CPU.demo.yml down
For an explanation of what happened, open the yml file. The file is well documented. To use your own files, place them in your home directory, and change the respective lines in the yml files to target them.
Run the detection demo application for the GPU:
CHOOSE_USER=root docker-compose -f 01_docker_sdk_env/docker_compose/05_tutorials/openvino_GPU.demo.yml up
Expected output: A video in a loop with cars being detected and labeled by the Neural Network using a GPU
To close this, do one of the following:
Type Ctrl-c in the terminal where you did the up command.
Run this command in another terminal:
CHOOSE_USER=eiforamr docker-compose -f 01_docker_sdk_env/docker_compose/05_tutorials/openvino_GPU.demo.yml down
For an explanation of what happened, open the yml file. The file is well documented. To use your own files, place them in your home directory, and change the respective lines in the yml files to target them.
For system with an Intel® Movidius™ Myriad™ X accelerator, run the detection demo application on the Intel® Movidius™ Myriad™ X accelerator:
NOTE:Only execute this command on systems with an Intel® Movidius™ Myriad™ X accelerator.Check your system:
lsusb
Look for Intel Movidius MyriadX in the output.
CHOOSE_USER=root docker-compose -f 01_docker_sdk_env/docker_compose/05_tutorials/openvino_MYRIAD.demo.yml up
Expected output: A video in a loop with cars being detected and labeled by the Neural Network using the Intel® Movidius™ Myriad™ X accelerator.
NOTE:There is a known issue that if you choose to run the object_detection_demo using the –d MYRIAD option, a core dump error is thrown when the demo ends.If errors occur, remove the following file and try again:
rm -rf /tmp/mvnc.mutex
To close this, do one of the following:
Type Ctrl-c in the terminal where you did the up command.
Run this command in another terminal:
CHOOSE_USER=eiforamr docker-compose -f 01_docker_sdk_env/docker_compose/05_tutorials/openvino_MYRIAD.demo.yml down
For an explanation of what happened, open the yml file. The file is well documented. To use your own files, place them in your home directory, and change the respective lines in the yml files to target them.
Troubleshooting
For general robot issues, go to: Troubleshooting for Robot Tutorials.