|author||Scott Main <firstname.lastname@example.org>||Wed Mar 31 16:46:18 2021 -0700|
|committer||Scott Main <email@example.com>||Wed Mar 31 17:29:14 2021 -0700|
add object detection example and add code to draw labels with boxes Also remove the custom load_labels function and use pycoral's util instead (only the pycoral version properly handles the weird COCO label IDs) Change-Id: I2405ce0150559f50a3951b08a86bb4133c82da9b
This repository provides several Python modules that are required for the Edge ML Club projects, including starter script files for those projects.
TODO: Update the RPI image URL and git clone URL below with final version.
Download this Raspberry Pi image and flash it onto your SD card. If you're not familiar with flashing, follow these steps:
Plug in a microSD card to a desktop/laptop computer (you might need an SD card adapter).
On the same computer, install the Raspberry Pi Imager.
Open the Raspberry Pi Imager, click Choose OS, then scroll down and click Use custom.
In the window that appears, select the ZIP file you downloaded in the first step above (the filename starts with “codenext”).
Back in the Raspberry Pi Imager, click Choose SD Card, and select your microSD card.
Now click Write to begin flashing the card.
When flashing is complete, insert the SD card into your Raspberry Pi and power it on.
Connect a USB camera and Coral USB Accelerator to the blue USB ports on your Raspberry Pi. (The blue ports are USB 3.0, the others are 2.0.)
On the Raspberry Pi, download this Git repository by opening the Terminal application and running this command:
git clone https://coral.googlesource.com/codenext-raspimon
Enter the directory and download some required files:
cd codenext-raspimon make download
Now run the
test.py script to be sure the camera and accelerator are working: