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Raspberry Pi for Computer Vision from the PyImageSearch.com team

Raspberry Pi for Computer Vision from the PyImageSearch.com team

Raspberry Pi for Computer Vision is a brand new book from Adrian Rosebrock and the PyImageSearch.com team — this book is the most in-depth, comprehensive, and hands-on guide to learning embedded Computer Vision and Deep Learning.

The text is filled with intuitive explanations and thoroughly documented code. Furthermore, all code and datasets are included in the text, enabling you to download your copy and start learning immediately.

Along with learning how to deploy practical computer vision applications to the RPi, you also get hands-on experience with Intel's Neural Compute Stick (NCS) and the OpenVINO toolkit (including how to use OpenCV and OpenVINO together to make developing embedded CV projects a breeze).

The book is divided into three volumes, called "bundles":

  • Hobbyist Bundle: A great fit if this is your first time working with computer vision, Raspberry Pi, or embedded devices.
  • Hacker Bundle: Perfect if you want to learn more advanced techniques, including deep learning on embedded devices, working with the Movidius NCS and OpenVINO toolkit, and self-driving car applications. You'll also learn tips, suggestions, and best practices when applying computer vision to the RPi.
  • Complete Bundle: Includes everything in the Hobbyist Bundle and Hacker Bundle, plus 19 additional bonus chapters/case studies, and access to private community forums for additional help and support.

Below you can find a sample of some of the topics and projects that are covered in the text:

  • How to configure your RPi for CV and DL
  • How to use the PyImageSearch pre-configured Raspbian .img file with OpenCV, OpenVINO, TensorFlow, Keras, etc. pre-installed (just download the .img file, flash it to your SD card, and boot!)
  • Building a Time Lapse Capture Camera
  • Creating a Remote Wildlife Detector
  • Streaming video from the RPi to your Web Browser or Phone
  • Detecting Tired, Drowsy Drivers Behind the Wheel of Vehicles
  • Creating a People/Footfall Counter
  • YOLO and SSD Object Detection on the RPi
  • Building a Smart Attendance System
  • Automatic Vehicle Detection, Tracking, and Speed Estimation
  • Deep Learning on the RPi
  • Face Recognition on the RPi with the NCS and OpenVINO
  • Building Smart Attendance Systems for Classrooms
  • Training and deploying custom image classification and object detection models with the NCS (TensorFlow and Caffe)
  • ...and much more!

To learn more about the book, and grab a free PDF of the book's table of contents and sample chapters, be sure to check out the official Raspberry Pi for Computer Vision webpage.