Real-time object detection on the Raspberry Pi with the Movidius NCS - PyImageSearch

Today's post is inspired by Danielle, a PyImageSearch reader who emailed me last week and asked: I'm enjoying your blog and I especially liked last week's post about image classification with the Intel Movidius NCS. My project involves object detection with the Raspberry Pi where I'm using my own custom Caffe model. The benchmark scripts you supplied for applying object detection on the Pi's CPU were too slow and I need faster speeds. Would the NCS be a good choice for my project and help me achieve a higher FPS? The short answer is yes, you can use the Movidius NCS for object detection with your own custom Caffe model. You'll even achieve high frame rates if you're processing live or recorded video. I told Danielle that she'll need the full-blown Movidius SDK installed on her (Ubuntu 16.04) machine. I also mentioned that generating graph files from Caffe models isn't always straightforward. Inside today's post you will learn how to: After going through the post you'll have a good understanding of the Movidius NCS and whether it's appropriate for your Raspberry Pi object detection project. To get started with real-time object detection on the Raspberry Pi, just keep reading. Today's blog post is broken into five parts.