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Now that we’re familiar with the project files and directories, let’s discuss the first step to building a face recognition system for your Raspberry Pi. From there feel free to hack it up for your own project purposes.
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We’re going to review it later in this post so you understand the code and what’s going on under the hood.
![raspberry pi craigslist auto poster raspberry pi craigslist auto poster](https://i1.wp.com/www.techjunkie.com/wp-content/uploads/2017/04/How-to-use-Craigslist-posting-software-without-being-flagged-or-deleted3.jpg)
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From there, copy the zip to your Raspberry Pi (I use SCP) and let’s begin. If you want to perform facial recognition on your Raspberry Pi today, head to the “Downloads” section of this blog post and grab the code. There are only a handful of tickets remaining, and once I’ve sold a total of 200 I won’t have space for you. You’ll even be able to socialize with attendees during evening events. You’ll meet others in the industry that you can learn from and collaborate with. Would you like to receive live, in-person training from myself, Davis King, Adam Geitgey, and others at PyImageSearch’s very own conference in San Francisco, CA?īoth Davis King (creator of dlib) and Adam Geitgey (author of the Machine Learning is Fun! series) will be teaching at PyImageConf 2018 and you don’t want to miss it! You’ll also be able to learn from other prominent computer vision and deep learning industry speakers, including me! PyImageConf 2018, a PyImageSearch conference
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If you’re wondering who Davis King is, check out my 2017 interview with Davis!įrom there, simply use pip to install Adam Geitgey’s face_recognition module: $ workon # optionalĪnd don’t forget to install my imutils package of convenience functions: $ workon # optional
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Next, let’s install Davis King’s dlib toolkit software into the same Python virtual environment (provided you are using one) that you installed OpenCV into: $ workon # optional You can follow my instructions linked on this OpenCV Install Tutorials page for the most up to date instructions. Let’s configure our Raspberry Pi for today’s blog post.įirst, go ahead and install OpenCV if you haven’t done so already. Configuring your Raspberry Pi for face recognition In the first part of today’s blog post, we are going to discuss considerations you should think through when computing facial embeddings on your training set of images.įrom there we’ll review source code that can be used to perform face recognition on the Raspberry Pi, including a number of different optimizations.įinally, I’ll provide a demo of using my Raspberry Pi to recognize faces (including my own) in a video stream. This post assumes you have read through last week’s post on face recognition with OpenCV - if you have not read it, go back to the post and read it before proceeding. Looking for the source code to this post? Jump Right To The Downloads Section Raspberry Pi Face Recognition To learn more about using the Raspberry Pi for face recognition, just follow along.
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non-threaded)Īll of these considerations and associated assumptions are critical when performing accurate face recognition on the Raspberry Pi - and I’ll be right here to guide you through the trenches.
![raspberry pi craigslist auto poster raspberry pi craigslist auto poster](https://i.ebayimg.com/images/g/ChMAAOSwgTVbcZlm/s-l300.jpg)
Namely, when performing face recognition on the Raspberry Pi you should consider:
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In last week’s blog post you learned how to perform Face recognition with Python, OpenCV, and deep learning.īut as I hinted at in the post, in order to perform face recognition on the Raspberry Pi you first need to consider a few optimizations - otherwise, the face recognition pipeline would fall flat on its face. Click here to download the source code to this post