6/16/2023 0 Comments Run syncovery on raspberry pi![]() I’ll then demonstrate how to use multiprocessing to create an alternate method to object detection using the Raspberry Pi. This benchmark will come from the exact code we used for our laptop/desktop deep learning object detector from a few weeks ago. In the first part, we’ll benchmark the Raspberry Pi for real-time object detection using OpenCV and Python. Today’s blog post is broken down into two parts. Looking for the source code to this post? Jump Right To The Downloads Section Raspberry Pi: Deep learning object detection with OpenCV In the remainder of today’s blog post we’ll be reviewing two methods to perform deep learning-based object detection on the Raspberry Pi. If you’re attempting to detect objects that are quickly moving through your field of view, likelyīut if you’re monitoring a low traffic environment with slower moving objects, the Raspberry Pi could indeed be fast enough. ![]() …but only if you set your expectations accordingly.Įven when applying our optimized OpenCV + Raspberry Pi install the Pi is only capable of getting up to ~0.9 frames per second when applying deep learning for object detection with Python and OpenCV. A few weeks ago I demonstrated how to perform real-time object detection using deep learning and OpenCV on a standard laptop/desktop.Īfter the post was published I received a number of emails from PyImageSearch readers who were curious if the Raspberry Pi could also be used for real-time object detection.
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