Create a Raspberry Pi Smart Security Camera
$50
Overview
This title is part of the Python Mini-Degree – 12 Courses to Learn and Master Python
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 Mini-Degree
The Python Mini-Degree is a bundle of 12 online video courses, that go all the way from teaching you how to code in Python while making a game, to building your own Artificial Intelligence (AI) and Internet of Things (IoT) applications using Computer Vision, Machine Learning and Deep Learning.
Learn more and enroll HERE.
Curriculum
Intro 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 1-10 Comparison of MSE and SSIM 2-1 Raspberry Pi 2-2 Handling Videos in OpenCV 2-3 Frame-by-frame Security Camera 2-4 Improved Security Camera 2-5 Twilio 2-6 Security Camera Notification with Twilio ConclusionRequirements
This course builds up on the concepts covered in our course Learn Python Image Processing.
You need to have Python 2.7 installed.
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.
