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 detect.py 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 → https://goo.gle/raspberrypi_software
Gist to setup your Raspberry Pi environment → https://goo.gle/3GdeQvz
GitHub repository containing the sample code → https://goo.gle/3GaABw3

Train a custom object detection model using your data → https://goo.gle/31qq4yg
Choose an object detection model architecture for Raspberry Pi → https://goo.gle/3lDe9DO
Make object detection run faster by using Coral → https://goo.gle/3EuH3xn

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

#TensorFlow #MachineLearning #ML #RaspberryPi

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

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