Uploaded December 2021 | Updated September 2026, 1 week ago

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Learn how to make your object detection model run faster using Google Coral Edge TPU in this final episode of Machine Learning for Raspberry Pi.

00:00 Introduction
00:15 What is EdgeTPU?
01:24 Connecting Google Coral USB Accelerator
02:11 3 steps to run an object detection model on EdgeTPU
02:36 Step 1: Compile the TFLite model
04:15 Step 2: Install the EdgeTPU runtime
05:20 Step 3: Enable EdgeTPU when running the model
07:27 Demo
08:43 EdgeTPU model code
09:14 Coral’s repository of pretrained models
09:36 Thank you for watching!

Colab notebook demonstrating how to compile a TensorFlow Lite model for Edge TPU → https://goo.gle/3G4RxUH
Instructions to install the EdgeTPU runtime → https://goo.gle/3xY3oBb
Sample app to run TensorFlow Lite object detection on Raspberry Pi → https://goo.gle/3GaABw3
Coral examples → https://goo.gle/3Dup355


Watch all Machine Learning for Raspberry Pi videos → https://goo.gle/ML-raspberrypi
Subscribe to TensorFlow → https://goo.gle/TensorFlow

#TensorFlow #MachineLearning #ML #RaspberryPi #EdgeAI



product: TensorFlow - TensorFlow Lite, TensorFlow - General; fullname: Khanh LeViet;