Les Lab | Raspberry Pi 4 (RPi4) & Google Coral Live object detection using MobileNet-SSD 70FPS! @LesLaboratory | Uploaded 5 years ago | Updated 11 minutes ago
Episode 3
#raspberrypi
#ai
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**Code below! Expand the description!**
The Raspberry Pi 4 can be made to work with the Google Coral for a killer AI combination! This combo an easily give your AI or robotics project the edge when it comes to object detection and machine learning!
This video discusses the installation script for Google Coral software on the RPi4 and also demonstrates two Live object detection scripts using MobileNet-SSD.
Amazing framerates and detection speed is possible with this combination!
The modified installation script and the two Object detection script are available at my GitHub:
github.com/leswright1977/RPi4-Google-Coral
Please don't forget to like and subscribe if you want to see more content and star my GitHub if you find my code useful!
Episode 3
#raspberrypi
#ai
Check out my other videos: youtube.com/leslaboratory
Please don't forget to like,subscribe and comment for more great content!
If you found this content useful, and would like to support this Channel, please consider supporting this work on Patreon: patreon.com/leslaboratory
Or donate directly: paypal.me/leslaboratory
Alternatively, please share this content on your social media platforms, it really helps me out!
**Code below! Expand the description!**
The Raspberry Pi 4 can be made to work with the Google Coral for a killer AI combination! This combo an easily give your AI or robotics project the edge when it comes to object detection and machine learning!
This video discusses the installation script for Google Coral software on the RPi4 and also demonstrates two Live object detection scripts using MobileNet-SSD.
Amazing framerates and detection speed is possible with this combination!
The modified installation script and the two Object detection script are available at my GitHub:
github.com/leswright1977/RPi4-Google-Coral
Please don't forget to like and subscribe if you want to see more content and star my GitHub if you find my code useful!
