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.
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
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
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 P
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
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
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!