Take some time to make sure the focus is correct before proceeding. If you have an HDMI cable plugged in, you’ll see what the camera can see in real-time. This will record ten seconds of video to your microSD card. ![]() From the command line, run the following: ![]() Once installed, boot up your Raspberry Pi 4 and test the camera is working. Connect the ribbon cable as instructed in /HQCameraGetStarted. Be sure to connect the camera to your Raspberry Pi 4 with the power off. This project will work well with the original Raspberry Pi Camera, but the new official HQ Camera will give you much better results. Finally, go into settings by running sudo raspi-config and enable the camera in ‘Interfacing Options’. Make sure you’re on the network, have set a new password, enabled SSH if you need to, and updated everything with sudo apt -y update & sudo apt -y full-upgrade. To keep as much resource as possible available for our project, we’ve gone for a Raspberry Pi OS Lite installation with no desktop. The extra memory will make all the difference. ![]() Face recognition using machine learning is hard work, so the latest, greatest Raspberry Pi 4 is a mustįor face recognition to work well, we’re going to need some horsepower, so we recommend a minimum of Raspberry Pi 3B+, ideally a Raspberry Pi 4.
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