In fact, I would argue that it’s even more important to use threading on the Raspberry Pi 2 since resources (i.e., processor and RAM) are substantially more constrained than on modern laptops/desktops.Īgain, our goal here is to create a separate thread that is dedicated to polling frames from the Raspberry Pi camera module.
Using this multi-threaded approach, our video processing pipeline is never blocked, thus allowing us to increase the overall FPS processing rate of the pipeline. This speedup is obtained by (1) reducing I/O latency and (2) ensuring the main thread is never blocked, allowing us to grab the most recent frame read by the camera at any moment in time. In last week’s blog post we learned that by using a dedicated thread (separate from the main thread) to read frames from our camera sensor, we can dramatically increase the FPS processing rate of our pipeline. Increasing Raspberry Pi FPS with Python and OpenCV Note: A big thanks to PyImageSearch reader, Sean McLeod, who commented on last week’s post and mentioned that I needed to make the FPS rate and the I/O latency topic more clear. Looking for the source code to this post? Jump Right To The Downloads Section
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