Introduction to object detection on Raspberry Pi

In the first episode of Machine Learning for Raspberry Pi, learn how to download a pre-trained TensorFlow Lite object detection model and deploy it to your Raspberry Pi. This model can be used to recognize general objects such as an apple, a television, or a car.

00:00 Welcome to the Machine Learning for Raspberry Pi
00:12 What you’ll learn in this series
1:14 Get started running object detection
1:35 Download the latest version of Raspberry Pi OS (link below)
2:29 Connect a camera to Raspberry Pi
3:12 Setting up Raspberry Pi
3:42 Create a Python virtual environment
4:30 Clone the TensorFlow examples
5:18 Run python to see what the model can detect!
5:45 Specific objects and faster speeds
6:16 A closer look at the code
9:34 What’s next

Download Raspberry Pi OS →
Gist to setup your Raspberry Pi environment →
GitHub repository containing the sample code →

Train a custom object detection model using your data →
Choose an object detection model architecture for Raspberry Pi →
Make object detection run faster by using Coral →

Watch all Machine Learning for Raspberry Pi videos →
Subscribe to TensorFlow →

#TensorFlow #MachineLearning #ML #RaspberryPi

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

Source of this TensorFlow AI Video

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