{"id":20817,"date":"2021-02-07T12:46:24","date_gmt":"2021-02-07T11:46:24","guid":{"rendered":"https:\/\/www.recantha.co.uk\/blog\/?p=20817"},"modified":"2021-02-07T12:46:24","modified_gmt":"2021-02-07T11:46:24","slug":"autonomous-driving-object-detection-on-the-raspberry-pi-using-opencv-tensorflow-lite-and-deep-learning","status":"publish","type":"post","link":"https:\/\/www.recantha.co.uk\/blog\/?p=20817","title":{"rendered":"Autonomous driving object detection on the Raspberry Pi using OpenCV, TensorFlow Lite and deep learning"},"content":{"rendered":"

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Ethan Dell is a full-time computer vision engineer who enjoys developing and experimenting with the Raspberry Pi. He has documented a great method of using the Pi (in this case, a Raspberry Pi 4) to do object detection when driving at speed. He has accomplished this by using OpenCV, so-called “deep learning” and TensorFlow Lite together with Python to take pictures from a Camera Module and identify road traffic objects while driving along. Just to keep things real, he’s attached everything to an empty tissue box, proving you don’t need a complicated case for it to go in. The results are outstanding and you can see how the detection gets better the closer the objects get to the driver.<\/p>\n

You can read a tutorial on how to do it on GitHub here<\/a>, view a deeper look at the “learning” methodology here<\/a> and you can also learn about the project and see the results by watching the video<\/a> below.<\/p>\n