This documentation is a step by step guide to runninng the YOLO object detection demo with your webcam.
This demo is validated on a Dell PowerEdge C4130 system having the following specs:
##### H/W Specs:
* 2 X Intel(R) Xeon(R) CPU E5-2690 v4 @ 2.60GHz
* 256 GB DDR4 Ram Memory
* 2TB disk space
* 4 X Nvidia Tesla P100 PCIe 16GB graphic cards.
* Logitech HD Pro Webcam C920
##### S/W Specs:
* CentOS Linux 7 (Core)
* Docker 1.13.1
* Git 1.8.3.1
Although you might not need an extensive system as the validation system, at the very least you need to have a base installation of Linux OS such as RHEL Centos or Ubuntu, Git and Docker. This also requires atleast 4GB of disk space, an Nvidia GPU, a working webcam (that already has drivers installed).
- You can check if the camera is installed by typing the following command on the terminal.
ls /dev/video*
You must see the following as a result:
/dev/video0
If you don't see anything or you see something like this ls: cannot access /dev/video*: No such file or directory
then please go back and install the drivers for your
webcam and confirm it works.
If you don't have docker installed, the following links explain how to install docker.
OR you can follow through these written articles:
For Centos
https://docs.docker.com/install/linux/docker-ce/centos/
For Ubunutu
https://docs.docker.com/install/linux/docker-ce/ubuntu/
Once you confirm that the prerequisites are present, run the script that pulls the docker image.
First, clone the repo:
git clone https://github.com/dellemc-hpc-ai/yolo_demo.git
cd into the folder:
cd yolo_demo
Run the script
bash run-yolo.sh
Note: If you have more than one webcam, please either use the webcam linked video0
or alter the run-yolo.sh
bash script which mounts to the docker volume to your preferred webcam.
The container is hosted on Dockerhub at : https://hub.docker.com/r/dellemchpcai/yolo_demo