Table of Contents – Raspberry Pi for Computer Vision

A couple of days ago I mentioned that on Wednesday, April 10th at 10AM EDT I am launching a Kickstarter for my new book, Raspberry Pi for Computer Vision.

As you’ll see later in this post, there is a huge amount of content I’ll be covering, so I’ve decided to break the book down into three volumes called “bundles”.

A bundle includes the eBook and source code for a given volume (as well as a pre-configured Raspbian .img file with all the computer vision + deep learning libraries you need pre-installed).

Each bundle builds on top of the others and includes all content from lower bundles. You should choose a bundle based on how in-depth you want to study CV and DL on the Pi, which projects/chapters interest you the most, along with your particular budget:

  • Hobbyist Bundle: A great fit if this is your first time you’re working with computer vision or the Raspberry Pi. Here you’ll learn basic computer vision algorithms that can easily be applied to the Pi. You’ll build hands-on applications including a wildlife monitor/detector, home video surveillance, pan/tilt servo tracking, and more!
  • Hacker Bundle: Perfect for readers who want to learn more advanced techniques, including deep learning, working with the Movidius NCS, OpenVINO toolkit, and self-driving car applications. You’ll also learn my tips, suggestions, and best practices when applying computer vision on the Raspberry Pi.
  • Complete Bundle: The full Raspberry Pi and computer vision experience. You’ll have access to every chapter in the book, video tutorials, a hardcopy of the text, and access to my private community and forums for additional help and support.

The complete Table of Contents for each bundle is listed in the next section.

Hobbyist Bundle

Figure 1: Raspberry Pi for Computer Vision – Hobbyist Bundle

The Hobbyist Bundle includes the following topics.

Working with the Raspberry Pi

  • Why the Raspberry Pi?
  • Configure your Raspberry Pi for computer vision + deep learning (including all libraries, packages, etc.)
  • Or, skip the install process and use my pre-configured Raspbian .img file which comes with everything you need pre-installed! Just flash the .img file and boot.
  • Streamline your development process and learn how to optimally write code on the Raspberry Pi (including suggested IDEs and recommended settings/configurations)
  • Access both your USB webcam and/or Raspberry Pi camera module on the Pi
  • Work with the NoIR camera module
  • Learn how to utilize multiple cameras with the Raspberry Pi

Getting Started with Computer Vision on the Raspberry Pi

  • Gain experience with OpenCV and your Raspberry Pi camera by creating time lapse videos on the Pi
  • Build an automatic bird feed monitor that detects when birds are present
  • Build an automatic prescription pill identification system (and reduce the 1.2 million injuries and deaths each year that happen due to taking the incorrect pill)
  • Learn how to stream frames from a Raspberry Pi to your web browser

Computer Vision and IoT projects with the Raspberry Pi

  • Review hardware considerations and suggestions when using the Raspberry Pi in IoT applications
  • Learn how to work in low light conditions, including camera and algorithm suggestions
  • Build and deploy a remote wildlife monitor, capable of detecting wildlife and saving clips of wildlife activity
  • Learn how to automatically run your computer vision applications on boot/reboot on the Pi
  • Send txt message (including messages with images and video) to your phone from the Pi
  • Create a vehicle traffic and pedestrian footfall counting system capable of detecting and counting the number of vehicles on a road/people entering and leaving an area

Servos and PID

  • What’s a PID?
  • Learn how to track faces and objects with pan/tilt servo tracking

Human Activity and Home Surveillance

  • Build a basic video surveillance system and detect when people enter “unauthorized” zones
  • Deploy your Raspberry Pi to vehicles and detect tired, drowsy drivers (and sound an alarm to wake them up)
  • Build an automatic people/footfall counter to count the number of people entering and leaving a store, house, etc.

Tips, Suggestions, and Best Practices

  • Learn about OpenCV optimizations, including OpenCL and how to access all four cores of the Raspberry Pi, boosting your system performance
  • Discover my blueprint on how to design your own computer vision + Raspberry Pi applications for optimal performance
  • Increase your FPS throughput rate using threading and multiprocessing

Hacker Bundle

Figure 2: Raspberry Pi for Computer Vision – Hacker Bundle

The Hacker Bundle includes everything in the Hobbyist Bundle. It also includes the following topics.

Advanced Computer Vision and IoT projects with the Pi

  • Pipe frames from the Raspberry Pi camera to your laptop, desktop, or cloud instance, process the frames, and then return the results to the Pi
  • Build a neighborhood vehicle speed monitor that detects cars, estimates their speed, and logs driver activity
  • Reduce package theft by automatically recognizing delivery trucks and detecting package delivery

Advanced Human Activity and Facial Applications

  • Extend your video surveillance system to include deep learning-based object detection and annotated output video clips
  • Track your family members and pets throughout the house using multiple cameras and multiple Raspberry Pi’s
  • Utilize the Raspberry Pi to perform gesture recognition
  • Perform face recognition on the Raspberry Pi
  • Create a smart classroom and automatic attendance system capable of detecting which students are (and are not) present
  • Utilize TensorFlow Lite to perform Human Pose Estimation

Deep Learning on the Raspberry Pi

  • Learn how to perform deep learning on resource constrained devices
  • Utilize the Movidius NCS and OpenVINO for faster, more efficient deep learning on the Raspberry Pi
  • Perform object detection using the TinyYOLO object detector on the Pi
  • Utilize Single Shot Detectors (SSDs) on the Raspberry Pi
  • Train and deploy a deep learning gesture recognition model on your Pi
  • Reduce package theft by training and deploying a deep learning model to recognize delivery trucks
  • Use deep learning and multiple Raspberry Pis to create a network of “smart cameras”
  • Review my guidelines and best practices on when to use the Pi CPU, Movidius NCS, or stream frames to a more powerful system

Movidius NCS and OpenVINO

  • Discover OpenVINO and how can it dramatically improve inference time on a Raspberry Pi
  • Learn how to configure and install OpenCV with OpenVINO support
  • Configure the Movidius NCS development kit on your Raspberry Pi
  • Classify images using deep learning and the Movidius NCS on your Pi
  • Perform object detection on the Movidius NCS to create a person counter and tracker
  • Create a face recognition system using the Movidius NCS on the Raspberry Pi
  • Train custom Caffe + TensorFlow models for the NCS and deploy them to the RPi

Self-driving Car Applications and the Raspberry Pi

  • Discover the GoPiGo3 and how it can facilitate studies in self-driving cars with the Raspberry Pi
  • Learn how to drive your GoPiGo3 with a Raspberry Pi
  • Drive a course using the GoPiGo3 and Raspberry Pi
  • Recognize traffic lights with the Raspberry Pi
  • Drive to specific objects using the GoPiGo3 and a Raspberry Pi
  • Create a line/lane follower with the Raspberry Pi

Complete Bundle

Figure 3: Raspberry Pi for Computer Vision – Complete Bundle

The Complete Bundle includes everything in the Hobbyist Bundle and Hacker Bundle.

In addition, it also includes:

  • All additional bonus chapters, guides, and tutorials
  • Video tutorials and walkthroughs for each chapter
  • Access to my private Raspberry Pi and Computer Vision community and forums
  • A physical, hardcopy edition of the text delivered to your doorstep

Google Coral and the Raspberry Pi

  • Configure your Google Coral USB Accelerator
  • Perform image classification with the Google Coral
  • Create real-time object detectors with the Coral
  • Train and deploy your own custom models using the Coral

NVIDIA Jetson Nano hands-on tutorials and guides

  • Configure your Jetson Nano
  • Perform image classification with the Nano
  • Real-time object detection with the Jetson Nano
  • Train and deploy your own custom models to the Nano

There you have it — the complete Table of Contents for Raspberry Pi for Computer Vision. I hope after looking over this list you’re excited as I am!

I also have some secret bonus chapters that I’m keeping under wraps until the Kickstarter launches. Stay tuned for this details.

To be notified when more Kickstarter announcements go live (including ones I won’t be publishing on this blog), be sure to signup for the Raspberry Pi for Computer Vision Kickstarter notification list!

24 Responses to Table of Contents – Raspberry Pi for Computer Vision

  1. David Bonn April 5, 2019 at 12:02 pm #

    This looks great, Adrian.

    Can’t wait to see it!

    • Adrian Rosebrock April 7, 2019 at 6:09 am #

      Thanks David!

  2. Chandan sharma April 5, 2019 at 1:18 pm #

    Dear Adrian

    Thank you for the wonderful work. Will your books also have info on what else to buy apart from res pi to compelte the listed projects? And hope easily available and not too expensive.


    • Adrian Rosebrock April 7, 2019 at 6:10 am #

      Yes, I will be providing a list of parts/hardware you will need. All code will be compatible with a Raspberry Pi and a Pi camera module or a USB webcam. The additional components, such as any HATs, will be optional but I also provide code on how to use those HATs as well for those who want to use them.

  3. Santosh Tamhane April 8, 2019 at 11:04 am #

    Dear Adrian,
    1. Not clear how the topics and examples in this ToC are much different from the various RaspberryPi tutorials you have already published on your blog. Is the book a collection of your blog articles on the topic?
    2. Can the Pis be used in production environment? Does the book cover how to scale up to production(hardware/software) if one builds some interesting usecase after learning from the book? 🙂

    • Adrian Rosebrock April 12, 2019 at 12:33 pm #

      1. No, the content is essentially brand new. There are a few example tutorials/blog posts I reference, but again, it’s new material.

      2. Yes, RPis can be used in production. I cover my tips and suggestions there as well.

  4. He April 9, 2019 at 11:53 am #

    Adrian wrote <>

    I’m kind of intrigued by the CompleteBundle, but won’t have much time for the next couple of months. Is there a time limit on the forum access?


    • Adrian Rosebrock April 12, 2019 at 12:20 pm #

      There is no time limit on the forum access, you would have “lifetime” access to it.

  5. koji May 8, 2019 at 2:47 pm #

    Hi Adrian,

    One quick question.
    Hacker Bundle covers Hobbyist Bundle’s contents?


    • Adrian Rosebrock May 9, 2019 at 6:26 am #

      Correct, the Hacker Bundle includes all chapters/content from the Hobbyist Bundle.

  6. Tihomir Sasic May 9, 2019 at 3:07 am #

    Adrian , wish you a great success with Kicstarter campaign. I’ve reserved my Hacker bundle + CV book and could not wait to put my hands on it & start to learn new stuff.
    Great work!

    • Adrian Rosebrock May 9, 2019 at 6:27 am #

      Thank you, I really appreciate your support and helping this book come to life, Tihomir!

  7. DeepNet July 4, 2019 at 5:55 am #

    Hi Adrian,
    Thanks a lot for keep updating post and very usefully books.
    I have a recommend for you about the new books.
    If possible don’t consider the cv2.dnn module for demonstration of running applications over embedded devices. In my opinion you consider one of keras/tensorflow framework, and cover both two things:

    1-How to train the best networks for machine vision task such as classification , detection , segmentation and etc on own datasets over embedded devices.
    2-How to improve the speed of the trained network over embedded devices with apply some techniques such as TensorRT / OpenVINO , …

    Regard the Best,

    • Adrian Rosebrock July 4, 2019 at 10:08 am #

      1. Yes, I will be covering all of those topics.
      2. I’ll be using the “dnn” module for Intel’s NCS only as OpenVINO is now Intel’s preferred method to interact with the NCS.

  8. nima July 16, 2019 at 7:41 am #

    hi dear adrian
    what model of nvidia jetson i need buy for using this book?
    or what version of jetson nano?
    i dont have any information about jetson so please
    give me some advice to buy correct model and suppliment like camera and sd card or etc
    thank u so much

    • Adrian Rosebrock July 25, 2019 at 9:59 am #

      This book covers using the Jetson Nano (NOT the TX1 or TX2).

  9. Jonathan A August 18, 2019 at 10:27 pm #

    Hey Adrian,

    I ordered the hacker bundle and would like to know if there may be an option to upgrade to the full bundle sometime in the future? Sorry if you covered this elsewhere but I didnt find any info on the matter. Thank you for your work.

    • Adrian Rosebrock September 5, 2019 at 11:02 am #

      Absolutely! Just send me an email when you’re ready to upgrade and I will get you the upgrade link.

  10. Juan September 16, 2019 at 10:12 pm #

    Dear Adrian,

    I am a current customer of your DL4CV book, and I am a BIG fan.

    Currently I find myself trying to decide which bundle to purchase for the Raspberry Pi Book. Is there a list of all the hardware components and costs required to complete each of these bundles?

    I am particularly interested in all the components required to make the Coral TPU accelerator projects work.

    Thanks in advance,


    • Adrian Rosebrock September 19, 2019 at 10:02 am #

      Hey Juan — there are two hardware lists. A bare essentials list and the complete list. Most readers only need the base essentials list. You can then pick and choose which hardware you want from the master list if you want to replicate a given project down to the T.

  11. shariq October 26, 2019 at 3:51 am #

    Hello Adrian,
    Please find my apologies to ask but i find kickstarter not responding/opening for some unknown reasons, thus i am unable to reach the pages to decide on buying the courses.
    I humbly request you to kindly provide any alternative links , i might go for the hacker’s bundle if thats available.

    Thanks and much Regards,

    • Adrian Rosebrock November 7, 2019 at 10:42 am #

      Hey Shariq — the Kickstarter campaign is over so if you would like to purchase a copy of Raspberry Pi for Computer Vision you should refer to the official RPi4CV page.

  12. Olayiwola December 18, 2019 at 4:33 am #

    Hello Adrian. The Raspberry Pi for CV hobbyist bundle has been a great help so far. However, I am trying to train a deep learning model to perform human pose estimation on video frame from pi camera while determining the optimum parameters for speed accuracy trade off on a Raspberry pi 4. Does the hacker bundle cover such content?

    • Adrian Rosebrock December 18, 2019 at 9:41 am #

      Thanks Olayiwola, I’m glad you’re enjoying it. You would actually want the Complete Bundle of Raspberry Pi for Computer Vision. The Complete Bundle includes how to perform human pose estimation on the RPi. If you would like to upgrade your bundle just send me an email or use my contact form.

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