Create a Raspberry Pi Smart Security Camera
$50
Overview
This title is part of the Python Computer Vision Mini-Degree
This course will guide you through creating a fully-functional and smart security camera, using a Raspberry Pi or the webcam on your device. The purpose of the application in this course is to detect movement in the video footage and subsequently execute an action, such as sending out an email or an SMS.
Sections covering both the theory and practical applications are included in this course. The theory videos demonstrate the building blocks so that you can understand how it all works. Topics taught in this course include summation notation, image similarity metrics, and video processing. Image similarity is a set of tools that we can use to compare images, which then helps us determine how similar they are.
A Raspberry Pi is not required to benefit from this course. The program can be run using the webcam in your laptop or desktop computer.
Learning goals:
- Summation Notation
- Image Similarity Metrics:
- Sum Squared Errors
- Mean Squared Errors
- Structural Similarity
- Video processing
About the Python Computer Vision Mini-Degree
The Python Computer Vision Mini-Degree is an on-demand curriculum featuring 8 professional-grade courses that are suitable for beginners and more advanced developers alike. This innovative program will teach you how to code in Python, master the fundamentals of Numpy, and understand the core concepts underlying computer vision, including how images are represented and can be manipulated, pattern detection, and video and optical flow.
With such an understanding of these powerful technologies, you’ll be prepared to take on the world as a well-informed and highly prepared developer.
Curriculum
Intro
Anaconda Development Environment
1-1 Summation Notation
1-2 Numpy Matrix Elements Sum
1-3 L1 Norm
1-4 Numpy L1 Norm
1-5 Sum of Squared Errors
1-6 Numpy Sum of Squared Errors
1-7 Mean Squared Error
1-8 Numpy Mean Squared Error
1-9 Structural Similarity
2-1 Raspberry Pi
2-2 Setting up our environment
2-3 Reading a Video Frame
2-4 Reading the Entire Video
2-5 Detecting an Intruder
2-6 Improving Efficiency
2-7 Twilio
2-8 Sending a Text Message
ConclusionRequirements
This course builds up on the concepts covered in our course Learn Python Image Processing.
Python 3 is used in this course.
It is recommended to take this course as part of the Python Mini-Degree, which includes 12 courses on Python, Computer Vision, Machine Learning, Deep Learning and much more.
