The Running TensorFlow Lite Object Recognition on the Raspberry Pi 4 guide has been updated to work with Raspberry Pi Bullseye and the new picamera2 library. It has also been updated to use a newer version of TensorFlow Lite, version 2.10.0.
Want to up your robotics game and give it the ability to detect objects? Maybe implement a security camera that can see and identify certain items? Now that the Raspberry Pi is fast enough to do machine learning, adding these features is fairly straightforward.
This guide will show you the steps to get TensorFlow 2 installed on your Raspberry Pi 4 and perform some object detection using the TensorFlow Lite Python Interpreter, which is faster than the full TensorFlow interpreter.
There are two main setup paths to choose from. The first option is with a PiTFT if you want to have a larger display. The second option is with the BrainCraft HAT, which has a built-in display and audio along several other components such as DotStar LEDs, a Joystick, and ports.
No comments:
Post a Comment