This Docker image includes the libraries and packages to work with the Coral USB Accelerator (Google). The based image is balenalib/raspberrypi3-debian:buster.
The image contains the following packages/libraries:
- Python 3.7.x
- NodeJS 12.x
- Python Packages:
- numpy, matplotlib, pil, zmq
- supervisor, tornado, picamera, python-periphery
- jupyter, cython, jupyterlab, ipywebrtc, opencv-python
- google-auth, oauthlib, imutils
- Other libraries included (check the
Dockerfile)
A Jupyterlab is available (https://<ip-address>:8888) in which you can write code to process images obtained e.g. from the Pi camera.
An examples using the Coral USB Accelerator is also included:
webcam_obj_detector_opencv.py: detects and classifies objects on the fly processing the images taken with the Pi camera. The streaming images are available over http (http://<ip address>:8080). It uses theopencvlibrary to get images from the camera (USB port or CSI connector).
More examples can be found on the Coral website. Git is install, thus, you can download the repositories inside jupyter by typing e.g.:
!git clone https://github.com/google-coral/project-posenet.git
To run the container type the following on a Raspberry Pi terminal:
docker run -d --privileged -p 25:22 -p 8080:8080 -p 8888:8888 -e PASSWORD=<<JUPYTER_PASSWORD>> --restart unless-stopped -v /dev/bus/usb:/dev/bus/usb lemariva/raspbian-edgetpu
You need to activate the camera interface using sudo raspi-config to use live images of the Raspberry Pi camera.
More information about the repository can be found on the following links:
- #Edge-TPU: Coral USB Accelerator + rPI + Docker
- #Edge-TPU: Hands-On with Google's Coral USB accelerator
- Apache 2.0